Newsletter of HoloGenomics

Genomics, Epigenomics integrated into Informatics:


A Compilation by Andras J. Pellionisz, see Contact, Bio and References here

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2007 Post-Encode

2007 Pre-Encode




The Decade of Genomic Uncertainty is Over

The FractoGene Decade (2002-2012)

Pellionisz' FractoGene, 2002 (early media coverage)

Pellionisz' "FractoGene" patent, priority date 2002, patent issued in 2012 (see 2002 priority date, 2007 CIP filing in Google Patents 8,280,641 , and also recursive fractal iteration utility disseminated in peer-reviewed paper and Google Tech Talk YouTube (Is IT Ready for the Dreaded DNA Data Deluge?), both in 2008, presented in September 2009 in Cold Spring Harbor. The issued patent is in force till late March, 2026. The invention drew utility from RELATING genomic- and organismic fractal properties. "Methods" were as described in the body of application, plus ~750 pages of "Incorporation by Reference" ("should be treated as part of the text of the application as filed", see US Law 2163.07(b)). State of Art Methods beyond CIP of Oct. 18, 2007 are handled as "Trade Secrets", as customary in the strongest combination of Intellectual Property Portfolios.

"Evidence for" and/or "Consistent with"??

As evident from the title of the paper above, authors clearly refer to "evidence". Other, and after the initial decade an escalating number of particular authors of independent experimental investigations consider their results "consistent with" the fractal organization found either in the genome, and/or in physiological/pathological (e.g. cancerous) organism(s).

With the significance of claims rapidly gaining a very different value ("evidence for" becoming extremely precious, while "consistent with" generally regarded as almost meaningless) authors are respectfully requested to clarify their (sometimes unclear or ambiguous) claims if they consider themselves in the valuable category of "providing evidence for" - or almost meaningless "consistent with" general class. Clarification to HolGenTech_at_gmail_dot_com will help proper citation, if any. - Dr. Pellionisz

By 2012, independent researchers arrived at the break-through consensus, overdue since 2002. First, ENCODE 2007, followed by ENCODE 2012 replaced the mistaken axioms of "Junk DNA" and "Central Dogma" by the "nolo contendere assumption" of "The Principle of Recursive Genome Function, 2008" (requiring the experimentally found "nearest neighbor organization" of the Hilbert-fractal of genome, at the later date of 2009). The independent illustration above of both the genome as well as organisms exhibiting fractal properties put the challenge plainly in their RELATION. Methods, as e.g. relating genomic fractal defects to the fractality of tumors in the genome disease of cancer, constitute secured intellectual property:

Eric Lander (Science Adviser to the President and Director of Broad Institute) et al. delivered the message
on Science Magazine cover (Oct. 9, 2009) to the effect:

"Mr. President; The Genome is Fractal !"

Proof of Concept (Clogged Fractal Structure Linked to Cancer) was already available
at the Hyderabad Conference (February 15, 2012)
Dozens of additional Independent Experimental Proof of Concept Papers were cited in
Hyderabad Proceedings

The genome is replete with repeats. If the fractal structure is compromised
(see laser beam pointing at where the "proximity" is clogged)
syndromes are already linked to cancer(s), autism, schizophrenia, auto-immune diseases, etc.

Table of Contents

(July 01) Genome-based Personalization Industry
(May 22) De-Bullshitting Big Data (Stanford-Oxford, USA-Asia) - says Greg Kovacs
(May 8) Your Genes Are Obsolete
(Apr 30) Small non-coding RNAs could be warning signs of cancer
(Apr 14) The Brave New World of Medicine
(Apr 09) Russia Wakes UP to Genomics
(Mar 31) Dr. Erez Aiden named newest McNair Scholar at Baylor College of Medicine
(Mar 30) Google invites geneticists to upload DNA data to cloud
(Mar 22) Getting Cancer Wrong [Newsweek; cancer cries for mathematics of nonlinear-dynamics]
(Mar 22) Fractal geometry to help diagnose cancer [Fractals in India]
(Mar 22) Designing Fractal Nanosctructured Biointerfaces for Biomedical Applications [Fractals in China]
(Mar 21) The New York Genome Center and IBM Watson Group Announce Collaboration to Advance Genomic Medicine
(Mar 18) A novel mechanism for fast regulation of gene expression
(Mar 15) S. Korea announces $540 million post-genome project
(Mar 12) Hacking Your DNA
(Mar 12) Really? One does not understand the genome by having sequenced it all?
(Mar 04) No longer junk: Role of long noncoding RNAs in autism risk
(Mar 04) Craig Venter's Latest Startup Gets $70 Million to Sequence Loads of Genomes
(Mar 02) GE Ventures support RainDance’s vision to make liquid biopsy a commercial reality
(Mar 01) Google Launches Genomics Effort, Joins Global Alliance
(Feb 25) Google Could Disrupt These 3 Medical Industries Within 10 Years
(Feb 19) Sony’s new genome analysis company is not playing catch-up with Calico
(Feb 16) SAP Pushes Easy-to-Use Software at Hub to Compete With Facebook
(Feb 15) Genome Interpretation Appliance; Designed in California, Develped in Europe & Mexico, Manufactured in Asia?
(Feb 07) Patent War-Weary Samsung Inks Cross-Licensing Deal with Cisco
(Feb 06) These 3 Tech Titans Could Revolutionize Health Care
(Feb 02) ILLUMINA Claims New Sequencer Transcribes 18,000 Genomes per Year at $1,000 Each
(Jan 26) LincRNA, once believed useless, plays role in genome
(Jan 24) Sony forms genome analysis company [with Illumina] in move towards personalized medicine
(Jan 18, 2014) Pulse of J.P. Morgan 2014: Interviews with 17 biopharma execs
(Dec 31, 2013) Eric Schmidt's 2014 predictions: big genomics and smartphones everywhere
(Dec 31) We should be looking at a complete paradigm shift
(Dec 30) "The Last Mohican" of "Junk DNA" Obsolete Axiom
(Dec 12) Breakthrough Towards Deciphering Genomic Code of Life is Likely to Come from Mathematics
(Dec 06) 23andMe to only provide ancestry, raw genetics data during FDA review
(Dec 05) Fractal Genome and its Chaotic Regulation?
(Dec 02) Gates Foundation to Double Donation [Bill Gates and Francis Collins]
(Nov 26) FDA warns Google-backed 23andMe to halt sales of genetic tests
(Nov 20) Mandelbrot, the Genius of Fractals - Born 89, Passed Away 3 Years Ago
(Nov 21) Would He Do It Again?
(Nov 17) Junk Genes Of Protein Codes Might Be Helpful To Understand Cancer
(Nov 07) HolGenTech Board of Advisers News - in Perspective
(Nov 07) The Genome Is Fractal - Distance function through loops of "Recursive Genome Function"
(Oct 27) Junk DNA as "Doing Nothing" became a Laughing Matter - Fractal Recursive Genome Function is the Prevailing Paradigm
(Oct 18) Improving Genome Interpretation ("Genomics is Mired in Misunderstanding")
(Sep 18) All Bets Are Off: Silicon Valley Goes For IT Google-Style!
(Sep 01) Most Assumptions in Molecular Biology are Wrong - Mattick says
(Aug 28) Genomic Dreams Coming Through in China
(July 31) Foundation Medicine seeks $86.3M IPO amid chase for reimbursement
(June 20) The Impact of Human Genome Program Nearing $1 Trillion - Battelle 2013
(May 23) Interpreting the Human Genome (Pioneers on a Shoestring)
(May 21) Professor John Mattick, Executive Director of the Garvan Institute: "the dam is about to burst"
(May 12) Non-coding RNA .. is acutely regulated .. in schizophrenia..!
(May 10) Metaphores of Fractal Dynamics to Multi-dimensional Systems
(Apr 25) Francois Jacob, Nobelist with Monod and Lwoff in 1965 for Operon gene regulation dies at 92
(Apr 25) Celebrate the Unknowns [Nature COMMENT on the 60th]
(Apr 14) Can Cancer Cells Solve the Puzzle of Junk DNA?
(Mar 29) Grappling with Cancer
(Mar 29) Genomic Science - A Possible Nobel Prize?
(Mar 13) Complete Genomics acquired by BGI of China on Sequoia Capital money from Silicon Valley, USA
(Mar 01) A Genetic Code for Genius? In China, a research project
(Feb 21) Breakthrough Prize on YouTube (and everywhere... spilling to BRIC)
(Feb 20) Breakthrough Prize in Life Sciences ($3 M each, for 5 scientists per year - list of first 11)
(Feb 08) Young Chinese scientists will map any genome
(Jan 24) Non-coding Mutations May Drive Cancer
(Jan 15) DNA pioneer James Watson takes aim at "cancer establishments"
(Jan 08) China, Regulation and Securing the Operating System of Life
(Jan 04) Playing Well with Others [When Industrialization of Genomics is no longer Academic Play
(Jan 01) The Decade of Genomic Uncertainty is Over (R.I.P. 2002-2012)
(Dec 31) National Medal of Science Awarded to Leroy Hood
(Dec 25) [A Compelling Case for Fractal Analysis of Cancer and DNA] Is the Cure for Cancer Inside You?
(Dec 25) The FractoGene Decade (2002-2012)
(Dec 20) Illumina Stock Leaps On Roche Acquisition Reports
(Dec 19) Fractal Organization of Human T-cell
(Dec 17) Land Rush
(Dec 10) 2012 After a Decade of Uncertainty, Genomics is at Crossroads
(Nov 29) Genome Data Analysis Summit, San Francisco
(Nov 25) Architecture Reveals Genome’s Secrets
(Nov 23) Thanksgiving - with blessings counted it is time to address "horror vacui"
(Nov 23) Formula Unlocks Secrets of Cauliflower's Geometry
(Nov 12) Szentagothai Centenary Tribute in New York City
(Nov 14) Software developers analyzing patterns to boost odds against cancer
(Nov 10) Genomics Industrialized. Patents Drive Innovations
(Nov 07) FractoGene Emerges in a Global, Scalable Business Model, Protected IP and an Avalanche of Proof of Concept Results
(Oct 08) FractoGene Patent Licensed to Seven in Southern California in its First Week
(Oct 02) US Patent Office Issues FractoGene Patent to HolGenTech Founder Pellionisz
(Sep 06-15) ENCODE Gets out from a 40-Year Dead-End; up to a New Era of Global Industrial Genomics
(Aug 15) What Went Wrong and When?
(July 04) A Quest for Clarity [or Understanding?]
(Jun 26) Summer Solsctice in Industrialization of Genomics
(Jun 10) The Lost Decade; Too Many Genomic Melt-downs (We Could Do Better)
(May 30) Chromosome structure fractal defects implicated in cancer
(May 18) In half a year, third independent experimental Proof of Concept that fractal defect of Copy Number Variation is implicated in cancer
(Apr 22) A Decade after Genomics was Declared to be Informatics; Vistas by Andras Pellionisz (Part II)
(Apr 18) Well, This Is Awkward
(Apr 12) Moore's Law versus Javon's Law: Drawning in the Dreaded DNA Data Deluge is mandated by law, unless we change for better algorithmic architectures
(Apr 09) Just in Weeks, Second Independent Experimental "Proof of Concept" of Fractal Defects Causing Cancer
(Mar 14) Recent CDx, NGS Deals Signal Siemens' Increasing Interest in Genomics Arena
(Mar 02) The Creative Destruction of Medicine
(Feb 29) A scalable global business model and a (sub)continent offers support of Pellionisz' Fractal Approach
(Feb 06) Roche’s Illumina Bid May Spur Buying in DNA Test Land Grab
(Jan 31) Genome Informatics Globalized - USA - China - Korea - India
(Jan 14) UNESCO’s Memorial Year Honours János Szentágothai
(Jan 02) Power in Numbers [Eric Lander: math must grab genomics, beneath neuroscience – AJP]
(Jan 01) Paired Ends: Lee Hood, Andras Pellionisz - 2012 a Year of Turing and theYear of Turning
(Dec 27) The genetic code, 8-dimensional hypercomplex numbers and dyadic shifts
(Dec 10) Biophysicists Discover Four New [Fractal - AJP] Rules of DNA 'Grammar
(Dec 07) Francis Collins [Head of NIH of the USA in Bangalore, India -AJP]
(Dec 06) Paired Ends: Lee Hood, Andras Pellionisz
(Dec 03) ELOGIC Technologies (Bangalore) to launch Genome Analytics Service (See Binet - Genome)
(Dec 02) DNA Sequencing Caught in Deluge of Data
(Dec 01) The FDA’s confusing stance on companies that interpret genetic tests is terrible for consumers
(Nov 30) ELOGIC Technologies Private Limited Bangalore, India [Pellionisz unites Silicon Valley-s of USA/India - AJP]
(Nov 29) The Search for RNAs
(Nov 28) High order chromatin architecture shapes the landscape of chromosomal alterations in cancer ["Fractal Defects" as root causes of cancer -AJP]
(Nov 14) Recursive Genome Function of the Cerebellum. Geometrical Unification of Neuroscience and Genomics
(Nov 12) Altered branching patterns of Purkinje cells in mouse model for cortical development disorder
(Oct 31) Geometric Unification of Neuroscience and Genomics
(Oct 27) ...Initially Jobs sought alternatives to surgery
(Sep-Oct) Bio-IT World; Savoring an NGS Software Smorgasbord
(Sep 23) A DNA Tower of Babel
(Sep 10) Sam Waksal, Pfizer Venture Investments, and More: Moderator Looks Forward to All-Star Chat at New York Life Sciences 2031
(Sep 05) Lost In Translation? Andy Grove blasts "Change the System!" in his Anti-Medical School Course at UC Berkeley
(Sep 03) W.M. Keck Foundation awards Jefferson scientists with $1M medical research grant [Rigoutsos - AJP]
(Sep 02) Samsung Launches Genome Analysis Service, Offers Free Genome
(Aug 20) Comment by Andras J. Pellionisz to New York Times "Cancer's Secrets coming into Sharper Focus"
(Aug 17) Everything Scientists Thought They Knew About Cancer Might Be Totally Wrong
(Aug 15) Spit and know your future [This time, for India... AJP]
(Jul 31) Researchers uncover a new method of checking for skin cancer
(Jul 17) A surge of top-quality papers pointing into "methylation-defects" as predicted by FractoGene as culprits for cancer
(Jul 21) How accurate is the new Ion Torrent genome, really? [Gordon Moore sequenced twice - AJP]
(Jul 21) [Former Intel President] Grove Backs an Engineer’s Approach to Medicine
(Jul 20) Loophole found in genetic traffic laws [Experimentaly Proven Death Certificate of Crick's "Central Dogma" - AJP]
(Jul 16) Editing the genome - Scientists unveil new tools for rewriting the code of life
(Jul 15) Clue to kids' early aging disease found [The Colossal Paradigm-Shift - AJP]
(Jul 14) Researchers Use Genome Editing Methods to Swap Stop Codons in Living Bacteria
(Jul 09) The Mathematics of DNA [is Fractal - says Dr. Perez]
(Jul 08) Cell Surface as a Fractal: Normal and Cancerous Cervical Cells Demonstrate: Different Fractal Behavior of Surface Adhesion Maps at the Nanoscale
(Jul 08) China genomics institute outpaces the world
(Jul 06) Searching For Fractals May Help Cancer Cell Testing
(Jul 01) A quest for better genetics [from Moscow...]
(Jun 30) Study Suggests Widespread Loss of Epigenetic Regulation in Cancer Genomes
(Jun 27) "So What?" - if you separate Fractal Defects from Structural Variants of Human Diversity? - In Vivo Genome Editing!
(Jun 24) 23andMe-Led Team Reports on Findings from Web-Based Parkinson's GWAS
(Jun 23) Researchers Develop Methylation-Based Model for Predicting Age from Spit DNA
(Jun 20) Goodbye, Genetic Blueprint
(May 30) Cells may stray from 'central dogma'
(May 23) The fractal globule as a model of chromatin architecture in the cell
(May 22) The Principle of Recursive Genome Function: Quantum Biophysical Semeiotics clinical and experimental evidences
(May 22) The Myth of Junk DNA - an issue fallen from science in 2006 to a rejected ideology for the masses to chew on as an Amazon bestseller
(May 16) Eric Schadt Joins Mount Sinai Medical School [Dir. of Institute for Genomics AND Multiscale Biology]
(May 12) Battelle Study: The $796 Bn Economic Impact of the Human Genome Project
(May 08) In an improbable corner of China, young scientists are rewriting the book on genome research [Newsweek]
(May 04) Systems Biology 'Makes Sense of Life' [Once the System is Identified - AJP]
(May 01) Virginia Tech partners with NVIDIA to “Compute the Cure” for Cancer
(Apr 30) Breast cancer prognosis goes high tech [Fractal - AJP]
(Apr 16) FractoGene (2002) and Fractal Frenzy set off by The Principle of Recursive Genome Function, YouTube (2008) [AJP]
(Apr 12) The Structural Struggle - [vs. Fractal Algorithmic Elegance - AJP]
(Apr 11) Cancer center builds Texas-sized cloud [private cloud!]
(Apr 11) Cancer as Defective Fractal Recursive Genome Function (Pellionisz and Lander et. al trigger escalation of fractal approach)
(Apr 07) The Trouble with Genes [Article Gets Prize - Mattick joins leaders to admit that basic premises were all wrong - AJP]
(Mar 27) Eric Schadt Extreme Science [and other kooks - AJP]
(Mar 25) Global Scaling Institute of Germany explores roots of fractals with Euler
(Mar 24) Avesthagen launches Whole Genome Scanning [India blows away FDA -AJP]
(Mar 15) Complementing Private Domain Genome Sequencing Industry - the Birth of Genome Analytics Industry
(Mar 15) Scientists need new metaphor for human genome [or better yet, science for industrialization of the new paradigm - AJP]
(Mar 15) RNA regulation of human development, cognition and disease (Mattick in Dubai)
(Mar 14) Hamdan Bin Rashid to inaugurate HGM 2011 Monday
(Mar 01) DRC Computer Invites Dr. Andras Pellionisz to Advisory Board
(Feb 20) NHGRI Celebrates Tenth Anniversary of Human Genome Sequence [what went wrong - Green]
(Feb 19) Initial impact of the sequencing of the human genome [what went wrong according to Sci. Advisor of the President]
(Feb 14) Primates' Unique Gene Regulation Mechanism: Little-Understood DNA Elements Serve Important Purpose

For archived HoloGenomics News articles see Archives above

Latest News

Genome-based Personalization Industry

2014 July 1st, amidst of a deafening silence that ensued the crashing collapse of the twin-towers of ENCODE I and II, marks a crucial transition of genomics as a branch of Academia to Genome-based Personalization Industry. A tell-tale sign was a Report (by April, 2014) of the Personalized Medicine Coalition.


4 2014

where the agenda was made rather obvious:

Common wisdom had it, till today, that Government-supported Academia, working together with Big Pharma will deliver. The thesis here is that the assumptions are no longer true. It will be "Genome-based Personalization Industry", once the ecosystem matures, that will "create or buy" the IT-based pharma, to compete for the new market of personalized medicine. The turning point today is Germany. While for too long Germany was a "DNA ultraconservative superpower", they are rich enough to afford the super-expensive new anti-cancer drugs, yet smart enough not to let their government-supported socialized health-care waste money on 75% of the drugs that are, in a particular case, ineffective. This is an absolute, global "game changer" [AJP]

'Game-Changing' Cancer Benefit Launching

SAP will soon be offering employees a first-of-its-kind personalized tumor-analysis and treatment-option benefit. Experts weigh in on its prognosis.

By Kristen B. Frasch

Tuesday, July 1, 2014

Walldorf, Germany-based SAP will soon be launching a first-ever, company-sponsored cancer-analysis tool that -- if SAP has anything to say about it – could soon become commonplace as an employee benefit.

Called TreatmentMAP and developed by The Woodlands, Texas (U.S.)-based MolecularHealth, it will essentially offer a personalized treatment option to SAP employees fighting cancer -- starting as a pilot in two countries and eventually spreading companywide.

Using next-generation-sequencing genetic testing, TreatmentMap will create tumor analyses and clinical interpretations of the genomic-patient data to help employees' doctors and oncologists establish individualized treatment options in much less time than medicinal trials, such as chemotherapy.

In light of today's personalized-medicine trend, says Dr. Natalie Lotzmann, SAP's chief medical officer, "it's just a matter of time" before other companies adopt similar programs to help their employees with cancer fight the disease with the greatest possible outcome. (Indeed, SAP's own press release about says the company "hopes to convince other employers" to consider offering such a benefit.)

"Receiving a cancer diagnosis is a personal tragedy" that all companies will have to bear at some point, Lotzmann says. "The need for this tool will only increase [and] I believe will one day be the standard for all medical benefits at all companies."

Mind you, this is not a cure. But it could be a game-changer. Huge amounts of data generated from each tumor analysis would be processed with an ultra-fast genome-alignment algorithm -- part of the SAP Genomic Analyzer -- and would be used to assemble the full DNA sequence in three minutes, about 300 times faster than the alignment software previously used. From that data, the tool then immediately matches that specific genetic makeup with all the research available in the world indicating what was tried to treat this particular type of cancer.

"It's a decision-making tool," says Lotzmann, adding that the information attached to it is continually changing and being augmented. "This ensures the cancer patient gets the latest and greatest of treatments, the treatment that has been proven to work best," rather than one physicians or cancer centers must arrive at through trial and error.

So game-changing is this, says Dr. Friedrich von Bohlen, chairman of MolecularHealth, that "with the advent of information-based molecular-genetic diagnosis, cancer can be individually and precisely profiled, and potentially transformed from a terminal to a chronic disease."

And this, he adds, is a win-win, "supporting both the employee and his or her organization during the challenge of working and living with cancer."

In fact, Laura Housman, senior vice president and chief commercial officer in MolecularHealth's Boston office (the company's global headquarters are still in Heidelberg, Germany) sees this cancer-analysis benefit as a "competitive differentiator ... that can have a real impact on the employer and can impact shareholders" as well.

"That your company has the generosity and forethought, and is at the forefront to anticipate these needs going forward, that speaks volumes to current and prospective employees," she says, "and can enhance your reputation in general."

Traditional testing methods are only taking patients so far, says Housman, who agrees more insurers and employers will no doubt be providing something like the new tool SAP is using in the near future in their benefits programs.

"From an employer perspective," she says, "cancer is an increasing burden for both employers and patients." Indeed, the Alexandria, Va.-based American Society for Clinical Oncology anticipates a 45-percent increase in new cancer cases by 2030, and a 35-percent increase between now and 2020 in the number of cancer survivors due to better treatment.

"You have to figure, a significant number of these people will be employees somewhere," Housman says.

So what should HR leaders be keeping in mind about this latest chapter in the ongoing and never-ending employee-benefits evolution? Both Lotzmann and Housman note that privacy with employees' genetic profiles needn't be a concern, as TreatmentMap facilitates the knowledge share with clinicians and oncologists, but doesn't store the genetic information.

"MolecularHealth is a [Health Insurance Portability and Accountability Act]-compliant provider," Housman says, "and this information is only shared between provider and patient -- and as far as payment goes, [the parties] are de-identified."

Though total cost was not discussed, both say early adoptions such as this are always more expensive and should be reduced over time as familiarity and use increase. They also stress the importance of gaining C-level buy-in before jumping on any bandwagon, and making sure HR and benefits leaders are involved.

Of course, as with anything this new, "the clinical efficacy of such tumor analyses needs ongoing study," says Thomas Parry, president of the San Francisco-based Integrated Benefits Institute.

Matching drugs to patients may still depend on clinical trials, he says, just on a "broader range of people and perhaps of outcomes that are important both to employees and to their employers -- as in absence from work, disability and performance."

The notion that tumor analysis may eliminate trials and experiments, he adds, "ignores the fact that prior research is needed to understand how to get the right match of drugs to patients."

Send questions or comments about this story to

De-Bullshitting Big Data (Stanford-Oxford) - says Greg Kovacs

On May 21-23 at Stanford University (co-anchored by Oxford) the major "Big Data in Biomedicine" rather exclusive top-level world-conference took place.

Some highlights were the "jaw-dropping" presentation by Stanford professor Greg Kovacs who summed-up the Big Agenda o

f by a single pithy word ("Algorithms." - albeit framed in a language that one may find offensive, though a sense of frustration is palpable and perhaps even read with empathy):

It is unclear at this minute if the Agenda will pan out as pictured below:

A reason for interest was another "game changer" presentation of Google Genomics (by David Glazer). A publicly available posting (below, viewed by 95,135) by a team-player of Google Genomics (David Konerding, present, but not presenting) raised a question (voiced by momentarily third party to both Google or BGI, found "deep"). The question was if reverse-engineering of Nature-made systems is similar to reverse-engineering of totally man-made (and algorithmically transparent) systems, such as the Internet.

[The conspicuous presentation by Prof. Kovacs of Stanford University will be posted by mid-June on the BigData website. Viewers will thus determine for themselves how a perhaps frustrated tone in 2014, after the fact of the almost mindless rush for "The Dreaded DNA Data Deluge" that consumed billions of dollars worth of data-gathering (and loss of valuation of data-gathering companies), can be compared to a whistle-blowing in 2008; focusing on the public question broadcast as a Google Tech Talk YouTube "Is IT Ready for the Dreaded DNA Data Deluge?" As for an entire category of "Algorithms", The Principle of Recursive Genome Function (and utility of its subset of Fractal Iterative Recursion) has been put forward in 2008 and IP is now in force till late March, 2026 - AJP]

Your Genes Are Obsolete

Pacific Standard

The Science of Society

BY MICHAEL WHITE • May 02, 2014 • 8:00 AM

Genes don’t consistently do what we once thought they would, so it’s time to reconsider what we mean when we say the word.

[Some established and already international award-winning informatics specialists never believed either of the disarmingly naive "Central" or "Junk DNA" dogmas - and mathematically redefined the genome in the non-Euclidean geometrical software-enabling terms of nonlinear dynamics, drawing the consequences of the utility of "Fractal genome grows fractal organisms". Now that "Junk DNA is anything but" and "Genes are obsolete", it may be worthwile to turn to FractoGene, see timeline of its first decade since 2002 here.]

Today, DNA is central to modern biology, but scarcely a century ago biologists were debating whether or not genes actually existed. In his 1909 textbook on heredity, Danish botanist Wilhelm Johannsen coined the term gene to refer to that hereditary “something” that influences the traits of an organism, but without making a commitment to any hypothesis about what that “something” was. Just over a decade later, a prominent biologist could still note that some people viewed genes as “a convenient fiction or algebraic symbolism.”

As the century progressed, biologists came to see genes as real physical objects. They discovered that genes have a definite size, that they are linearly arrayed on chromosomes, that individual genes are responsible for specific chemical events in the cell, and that they are made of DNA and written in the language of the Genetic Code. By the time the Human Genome Project was initiated in 1988, researchers knew that a gene was a segment of DNA with a clear beginning and end and that it acted by directing the production of a particular enzyme or other molecule that did a specific job in the cell. As real things, genes are countable, and in 1999 biologists estimated that humans had “80,000 or so” of them.Yet, when the dust from the Human Genome Project cleared, we didn’t have nearly as many genes as we thought. By the latest count, we have 20,805 conventional genes that encode enzymes and other proteins. Our inflated gene count, though, wasn’t the only casualty of the Human Genome Project. The very idea of a gene as a well-defined segment of DNA with a clear functional role has also taken a hit, and as a result, our understanding of our relationship with our genes is changing.

One major challenge to the concept of a gene is the growing evidence that many genes are shapeshifters. Instead of a well-defined segment of DNA that encodes a single protein with a clear function, we should view a gene as “a polyfunctional entity that assumes different forms under different cellular states,” according to University of Washington biologist John Stamatoyannopoulos. While researchers have long known that genes are made up of discrete subunits called “exons,” they hadn’t realized until recently the degree to which exons are assembled—like Legos—into sometimes thousands of different combinations. With new technologies, biologists are cataloging these various combinations, but in most cases they don’t know whether those combinations all serve the same function, different functions, or no function at all.

Our concept of a gene is also challenged by the fact that much of the function in our DNA is located outside of conventionally defined genes. These “non-coding” functional DNA segments regulate when and where conventional protein-coding genes operate. For our biology, non-coding regulatory DNA elements are as consequential as genes, but their properties are even more difficult to define because their function isn’t based on the well-understood Genetic Code and their boundaries are even fuzzier than gene boundaries. As a result, non-coding regulatory DNA elements are much more difficult to count. One consortium of researchers put the number of regulatory DNA segments in the human genome between 580,000 and 2.9 million, while just last month a different consortium claimed that there are only 43,000. Regardless of how you count them, it’s clear that these non-gene regulatory DNA elements far outnumber conventional genes. It is hard not to wonder, then, what good is the concept of a gene if it doesn’t include most of our functional DNA?

In the aftermath of the Human Genome Project, biologists are struggling with the definition of a gene, but why should this matter to anyone else? It matters because the molecular concept of the gene that has dominated biomedical research for the last half-century is increasingly ill-suited for our efforts to understand the role of genetics in human biology. Giving a physical meaning to the concept of a gene was a triumph of 20th-century biology, but as it turns out, this scientific success hasn’t solved the problems we hoped it would.

The Human Genome Project was conceived as part of a research program to develop a set of clear molecular explanations for our biology. The idea was to inventory all of our genes and assign each of them a function; with this annotated inventory in hand, we would possess a molecular explanation of our genetic underpinnings and discover druggable target genes for specific diseases. While this gene-focused approach has been successful in many cases, it’s increasingly clear that we will never understand the role of genetics in our biology by merely making an annotated inventory of those DNA entities that we call genes.

Life isn’t so simple, and perhaps Wilhelm Johannsen’s more agnostic definition of a gene is a better match to the mixed bag of genetic elements in our genomes. The molecular concept of a gene was supposed to explain the influence of our DNA on our biology, our behaviors, and our ailments. That explanation is much more elusive than we hoped, and the role of DNA in our lives is more complex and subtle than we expected.

[Indeed, see the non-trivial but software-enabling algorithmic elaboration here]

Small non-coding RNAs could be warning signs of cancer

HEIDELBERG, 17 February 2014 – Small non-coding RNAs can be used to predict if individuals have breast cancer conclude researchers who contribute to The Cancer Genome Atlas project. The results, which are published in <em">EMBO reports, indicate that differences in the levels of specific types of non-coding RNAs can be used to distinguish between cancerous and non-cancerous tissues. These RNAs can also be used to classify cancer patients into subgroups of individuals that have different survival outcomes.

Small non-coding RNAs are RNA molecules that do not give rise to proteins but which may have other important functions in the cell. “For many years, small non-coding RNAs near transcriptional start sites have been regarded as ‘transcriptional noise’ due to their apparent chaotic distribution and an inability to correlate these molecules with known functions or disease,” explains Steven Jones, one of the lead authors of the study, a professor at Simon Fraser University and the University of British Columbia, and a distinguished scientist at the BC Cancer Agency. “By using a computational approach to analyze small RNA sequence information that we generated as part of The Cancer Genome Atlas project, we have been able to filter through this noise to find clinically useful information,” adds Jones. “The data from our experiments show that genome-wide changes in the expression levels of small non-coding RNAs in the first exons of protein-coding genes are associated with breast cancer.”

The scientists were able to distinguish between the many different small non-coding RNAs that are found near the transcriptional start sites of genes in healthy individuals and patients with breast cancer (in this case, breast invasive carcinoma). They mapped these RNA molecules to specific locations on the DNA sequence and looked for correlations between the non-coding RNAs that were strongly expressed and the disease status of the patients from whom the tissue samples were isolated. The researchers then tested if the expression of the small RNAs in genomic locations that they were able to identify could be used to predict the presence of disease in another group of tissue samples obtained from patients known to have breast cancer. The test efficiently predicted the correct disease status for the samples in the new study group.

“The potential to predict cancer status is restricted to only a subset of the many small non-coding RNAs found near transcription start sites of the genes. What’s more, these RNA locations are highly enriched with CpG islands,” says Athanasios Zovoilis, the first author of the study. CpG islands are genomic regions that contain a high frequency of cytosine and guanine. The presence of these RNAs in these islands may implicate their involvement with DNA methylation processes and the onset of disease but additional experiments are needed to explore and prove this link.

“This is the first time that small non-coding RNAs near the transcription start site of genes have been associated with disease,” says Jones. “Further work is required but based on our data we believe there is considerable diagnostic potential for these small non-coding RNAs as a predictive tool for cancer. In addition, they may help us understand better the mechanisms underlying oncogenesis at the epigenetic level and lead to potential new drugs employing small non-coding RNAs.” The researchers also note that this class of small non-coding RNAs may be useful in predicting the existence of other types of cancer or disease.

The generation of data by The Cancer Genome Atlas project, which now provides access to large amounts of sequencing information for diseased and normal tissues, made the work possible. The Cancer Genome Atlas is now one of the largest resources for small non-coding RNAs in existence.

The Brave New World of Medicine

Vivek Wadhwa

For The Washington Post

Monday, April 14, 2014

Health care is a misnomer for our medical system. It should be called sick care. Doctors, hospitals and pharmaceutical companies only make money when we are in bad health. If we could instead prevent illness and disease, it would turn the entire medical system on its head and increase the quality of our lives.

The good news is that technology is on its way to letting us do this. It is now moving so rapidly that within a decade the small handheld medical reader used by Dr. Leonard McCoy in Star Trek — the tricorder — will look primitive. We are moving into an era of data-driven, crowd-sourced, participatory, genomics-based medicine. Just as our bathroom scales give us instant readings of our weight, wearable devices will monitor our health and warn us when we are about to get sick. Our doctors — or their artificial intelligence replacements — will prescribe medicines or lifestyle changes based on our full medical history, holistic self and genetic composition.

It wasn’t long ago when our only recourse when we doubted our doctor’s prescription was to seek a second opinion. Now when we need information about an ailment we search on the Internet. We have access to more medical knowledge than our doctors used to have via their medical books and journals, and our information is more up-to-date than those medical books were. We can read about the latest medical advances anywhere in the world. We can visit online forums to learn from others with the same symptoms, provide each other with support and discuss the side effects of our medicines. We can download mobile applications that help us manage our health. All of this can be done by anyone with a smartphone.

Our smartphones also contain a wide array of sensors, including an accelerometer that keeps track of our movement, a high-definition camera that can photograph external ailments and transmit them for analysis, and a global positioning system that knows where we have been. Wearable devices such as Fitbit, Nike and Jawbone are commonly being used to monitor the intensity of our activity; a heart monitor such as one from Alivecor can display our electrocardiogram; several products on the market can monitor our blood pressure, blood glucose, blood oxygen, respiration and even our sleep. Soon we will have sensors that analyze our bowel and bladder habits and food intake. All of these will feed data into our smartphones and cloud-based personal lockers. Our smartphone will become a medical device akin to the Star Trek tricorder.

When we get sick, we won’t need to go — in high temperature and in severe pain — to our doctors’ offices, only to wait in line with patients who have other diseases that we may catch. Our doctors will come to us, over the Internet. Telemedicine is already a fast-growing field; doctors have been assisting people in remote areas by using two-way video, email and smartphones. They will increasingly assist us in our homes. Our smartphone and body sensors will provide them with better medical data than they usually have today.

Then our smartphones will evolve further and do part of the job of doctors.

The same type of artificial intelligence technology that IBM Watson used to defeat champions on the TV game show Jeopardy will monitor our health data, predict disease and advise on how to improve our health. Already, IBM Watson has learned about all the advances in oncology and is better at diagnosing cancer than our human doctors. Watson and its competitors will soon learn about every other field of medicine, and will provide us with better, and better-informed, advice than our doctors do. They will take a more holistic view of our bodies, lifestyles and symptoms than our doctors can. They will, after all, have our full medical history from childhood, know where we have been, and keep track of our medical data on a minute-by-minute basis. Most doctors still work from brief, unintelligible, hand-scribbled notes and try to make a judgment about what medicines to prescribe us in a 10- to 15-minute consultation; they treat symptoms of interest but can overlook the bigger picture of where the treatment leads.

Artificial intelligence technologies will also analyze continual data from millions of patients and on the medications that they have taken to determine which of these truly had a positive effect; which simply created adverse reactions and new ailments; and which did both. This will transform the way in which drugs are tested and prescribed. In the hands of independent researchers, these data will upend the pharmaceutical industry — which works on limited clinical-trial data and sometimes chooses to ignore information that does not suit it.

This is just the tip of the iceberg.

We learned how to sequence the genome about a decade ago, and sequencing it cost billions. Today a full human genome sequence costs as little as $1,000. At the rate at which prices are dropping, it will cost less within five years than a blood test does today. So it is now becoming affordable to compare one person’s DNA with another’s, learn what diseases those with similar genetics have had in common, and discover how effective different medications or other interventions were in treating them. Today, medicines are prescribed on a one-size-fits-all basis. In the future, you can expect to see doctors tailor treatment for diseases on the basis of an individual’s genomic information and lifestyle.

We can also now “write” DNA. In the emerging field of synthetic biology, researchers and even high-school students, are creating new organisms and synthetic life forms. Entrepreneurs have developed software tools to “design” DNA. These technologies provide the ability to generate designer drugs, therapeutic vaccines and microorganisms. Like all technologies that modify fundamental biology without a complete understanding of how environment, DNA, protein production and cell biology interact, this introduces new risks because we could engineer dangerous new organisms. But, used appropriately, this field may dramatically affect the development of novel, and more effective, therapeutics.

Ultimately, disease prevention is about lifestyle and habits as well as about genome and exposure to disease. Technology combined with good habits can create the health care system that we really need. We’re not dependent on Big Pharma, the medical establishment, or even the Food and Drug Administration. Medicine has become an information technology. The advances in health care are being developed by entrepreneurs and scientists all over the world. There is no stopping this.

Vivek Wadhwa is a fellow at Rock Center for Corporate Governance at Stanford University, director of research at Duke University, and distinguished scholar at Singularity and Emory universities.

RUSSIA WAKES UP TO GENOMICS - IBinom introduces revolutionary genomic data interpreter that's fast, efficient, user-friendly, and affordable


MOSCOW, RUSSIA - Mar 26, 2014 - Moscow startup iBinom has released the beta version of a cloud-based SaaS solution for clinical interpretation of human genome and exome data. 

As more clinicians and researchers come to rely upon genetic data in their quest to combat thousands of devastating human diseases and conditions, accurate and speedy analysis of that constantly expanding body of data becomes increasingly critical. Geared to the physician or geneticist who isn't necessarily a computer geek - and that would probably describe most professionals in those fields - iBinom's beta version is currently available for free at

This should be welcome news to medical centers, research centers, and sequence providers everywhere, notes iBinom's co-founder, Valery Ilinsky.

Ilinsky explains, "iBinom has developed one of the most precise algorithms presently available to determine rare pathogenic mutations among millions of non-pathogenics. Our solution is the fastest available as well - only 30 minutes from start to results." At present, he adds, tools offered by his firm's closest competitor take at least three hours to accomplish only part of the task that iBinom's data interpreter completes in half an hour. In addition, iBinom provides users with a clear report that does not require a programmer or a bioinformatician to understand.

Co-founded Ilinsky and the company's CEO Andrey Afanasyev, iBinom currently has offices in Moscow and St. Petersburg in Russia, as well as in Los Angeles. The firm has assembled a group of highly skilled programmers, several of whom have won global competitions in algorithms and programming, such as TopCoder, CodeForces, ACM, ICPC, IPSC, Google Code Jam. Ilinsky says iBinom anticipates a brisk demand for its service as prospective customers discover the advantages it provides over tools currently in use.

Ilinsky explains that iBinom was designed to address a dual problem faced by genetics researchers and clinicians alike: an overabundance of data, and a need to make sense of that data. "The number of sequenced genomes is growing exponentially, and if it keeps increasing at the current rate, approximately 25 million genomes will have been sequenced by 2016," he says. "The incorporation of whole-genome and whole-exome sequencing into clinical practice will undoubtedly change the way genetic counselors and other clinicians approach genetic testing."


Many clinicians are limited by currently available tools because human genome sequencing for clinical purposes is associated with detailed and precise Big Data analysis, Ilinsky notes. Initial raw data includes approximately 200GB of genetic data per patient, which is analyzed using either desktop applications or SaaS. However, Ilinsky says, current methods require special knowledge to interpret this massive amount of data, and do not provide medical reports. This greatly delays total turnaround time and decreases the sequencing capacity of service providers, as genome analyzers currently in use can take many hours to generate raw data for only one humangenome.

By contrast, iBinom offers a simpler, faster - and ultimately more affordable - means of genomic data interpretation. The user-friendly interface was designed for physicians and geneticists, but no special programming or bioinformatics expertise is required, and a medical report may be downloaded in one click. In addition to its fast proprietary algorithms of data analysis, the use of Amazon and Yandex IaaS (Infrastructure as a Service) has provided iBinom with the edge that allows production of a single human genome analysis in only half an hour.

Pricing is expected to be flexible and affordable compared to what is currently available. iBinom's SaaS business model allows customers to pay a fixed price for each analysis and a monthly fee for storage.

Says Ilinsky, "iBinom has devoted a great deal of time, effort, and expertise to developing advanced algorithms for accurate, speedy analysis of all of 30 000 human genes that could be linked to an estimated 3,000 inherited conditions with known genetic origin. We anticipate that iBinom will finally take next-generation sequencing out of the laboratories and into the hospitals and clinics, who will finally be able to routinely use exome sequencing and whole genome sequencing to diagnose their patients and manage their care."

[In itself, a Moscow-based start-up (with an office in Los Angeles...) may not appear such a strategic shift as it signals. The Moscow-based company, using "proprietary algorithms" apparently for exomics at this early time-point, is likely to be "stealth", under the radar. Similarly, not so many thought ahead of the game when in a dilapidated shoe-factory Beijing Genome Institute started to receive $Bn-s of government subsidy since "we are not interested in the white people's disease, but we are interested in the Chinese people's disease - besides, Genomics is of strategic interest". Russia is rather obviously waking up these days to her own "strategic interests". Why would be the Russian (Slavic) genome be strategically so important? Most importantly (similar to the genome of about 9 Chinese tribes), the homogeneity, and thus vulnerability of Slavic/Chinese genomes is orders of magnitude more exposed - compared to the rather extremely heterogeneous genome-pool of e.g. India (an answer why they spend much less on genomics compared to Pakistan). The American genome-pool is one of the most heterogenous "salad bowl" on the Earth - but it has access to practically all specific "genomes", and at the moment might still be in the lead to understand and thus deploy "genome regulation" with unexpected precision. Are the Chinese and the Russians (etc) interested in advanced IT "proprietary solutions"? You may want to note that Mr. Snowden, after a stop-over in China and now in Russia appears to be on his way to become a "Honorary Doctor" of a University of Germany. Interesting. - AJP]

From 23-28 June 2014, the Institute of Cytology and Genetics, Novosibirsk, Russia, will conduct the regular International Conference on Bioinformatics of Genome Regulation and Structure\Systems Biology (BGRS\SB-2014).

[Akademgorodok, the "scientific research center tucked safely away" is 20 miles from Novosibirsk, "Capital of Siberia". With a supercomputer available also for genomics, they have recently obtained an additional $1Bn. - Dr. Pellionisz]


Google invites geneticists to upload DNA data to cloud

SFgate, March 18, 2014

Stephanie M. Lee

Updated 5:04 am, Tuesday, March 18, 2014

Googling a person is about to take on a completely new meaning.

The Mountain View search giant recently invited geneticists to upload information to the company's cloud infrastructure. Google also provided scientists with instructions on how to import, process, store and, of course, search DNA data that could unlock clues to curing diseases.

Google's foray into genomics could open big markets for a company that has already made substantial investments in health care.

"This whole area, by the way of genome analysis, is really in general a hot area," said George Geis, an adjunct professor who specializes in technology mergers and acquisitions at UCLA's Anderson School of Management.

A MarketsandMarkets report valued the global genomics market at $11 billion in 2013 and predicted it will reach $19 billion by 2018. The North American health care cloud-computing market is also expected to grow fast in that time, up 30 percent to $6.5 billion.

Enormous databases

Sequencing the human genome can reveal deadly mutations as well as pathways for life-saving drugs. Since one individual's genome can add up to about 100 gigabytes of data, researchers must perform rigorous analysis to pry insights out of enormous databases.

At the same time, scientists and companies must answer questions about where to store the information, who should have access and how to protect privacy.

To help address those concerns, Google recently joined the Global Alliance for Genomics and Health, a coalition of health care providers, research universities, life science firms and others. The group, which met for the first time this month, is trying to encourage the industry to pool resources and establish standards on how to manage the data.

Expanding into health

For now, Google is providing the genetics community with Web services for free. But "it could very well be something that provides a top-line revenue for them going forward," Geis said.

The company is quickly expanding into health and medicine. Google owns Calico, a biotech company developing technologies to extend human life. In January, Google unveiled a prototype contact lens designed to help diabetics monitor their blood glucose. It also uses aggregated search data to estimate flu activity in more than 25 countries, and once operated a personal health-record service that let users create profiles for their health conditions, medications, allergies and lab results.

Someday, Google could use genetic data to make its own medical discoveries, Geis said.

"It could very well transform Google into another type of company - it partners with a pharmaceutical company or licenses its discoveries and patents its discoveries," he said.

But Google faces competition from companies large and small already in the genomics-analysis field.

For two years, Amazon's cloud service has hosted the 1,000 Genomes Project, the world's largest database of human genetics. Although the data are public and free, Amazon does charge researchers to use its high-powered computing resources to run data calculations.

'Lots of room'

"Generally speaking, the cloud space is still in its infancy and there's lots of room, certainly, for industrial players to try to apply their particular implementation of cloud technologies to new areas," said Ramon Felciano, co-founder of Ingenuity Systems. The Redwood City company, which was recently acquired by Qiagen, makes software for analyzing biological data.

DNANexus in Mountain View also provides cloud storage for genetic data. Chief Cloud Officer Omar Serang said the company joined the Global Alliance for Genomics and Health because scientists and companies can't advance research without a common format.

"Information is incredibly siloed," Felciano said.

The sensitive nature of genetic data prevents easy collaboration due to patients' privacy concerns.

"The whole field of genetic research, especially genetic research based off large data sets or well-sequenced genomes, is ripe with privacy and ethical issues," said Lee Tien, a senior staff attorney at the Electronic Frontier Foundation in San Francisco.

Privacy standards

While hospitals and academic institutions must adhere to patient privacy rules, private companies do not necessarily follow those standards, Tien said.

Members of the Global Alliance for Genomics and Health are working to develop common policies that govern ethics, data storage and security. For its part, Google says genomic data stored in its cloud is secure.

"Private data remains private, public data is available to the community anywhere," the company said on its website.

Tien remans cautious.

"It may all go well," he said. "But in other cases there will be surprises - and you don't really want surprises with genetic data."

Stephanie M. Lee is a San Francisco Chronicle staff writer. E-mail:


March 24, 2014 | By Nick Paul Taylor

Google's ($GOOG) expansions into life sciences and genomics have raised two big, as yet unanswered, questions--how will they affect the industry, and what do they mean for the company? This week, the San Francisco Chronicle looked into possible answers to both questions.

In the past 6 months Google has set up a biotech focused on aging and a genomics cloud services platform, but both projects are still taking shape. It is still too early to tell whether they will succeed or join Google's big scrap heap of axed projects, but University of California, Los Angeles' George Geis sees reasons for optimism. Geis, who specializes in technology mergers and acquisitions, thinks Google Genomics has the potential to give the search giant new sources of revenues.

"It could very well transform Google into another type of company--it partners with a pharmaceutical company or licenses its discoveries and patents its discoveries," Geis told SF Chronicle. Such a scenario currently appears a distant prospect, but is one possible outcome of Google applying its mission to "organize the world's information and make it universally accessible and useful" to genomics.

Whether people are comfortable with Google organizing the world's genomic data is still questionable, though. Revelations of National Security Agency snooping on tech giants' data centers have made some people wary of trusting trusting the likes of Google with their search histories, let alone their genome data. And the results of a recent survey and the outcry over the English patient record database have shown many people are uncomfortable with companies profiting from their health data.

Earlier this month MedCity News reported on an exchange between technology columnist Kara Swisher and 23andMe CEO Anne Wojcicki at SXSW that sums up the concerns. "I don't like the idea of Google having my gut bacteria on file because they could monetize it, you know they could," Swisher said.

New details on brains and budget behind Google's Calico emerge

October 10, 2013 | By Nick Paul Taylor

Google ($GOOG) generated a deluge of headlines when it unveiled its antiaging venture Calico but gave very few details about the nuts and bolts of the company. Now, reports on the questions Calico will look into--and how much cash it will have to answer them--have started to emerge.

Calico is the brainchild of Google Ventures' managing partner Bill Maris, Fortune reports. Maris--a former biotech portfolio manager at Investor AB--noted a lack of companies trying to stop the degradation of genetic material that ultimately causes cells to fail. Efforts to raise cash for a company to fill this gap led to discussions with Google cofounder Sergey Brin and eventually a decision by the search giant to fund the entire project.

Exactly how much Google is committing to Calico is unclear, but sources told Fortune it is at the very least hundreds of millions of dollars. Google has indicated it views this as a long-term investment--with the payoff coming 10 to 20 years down the line--and there are suggestions it is creating more of a research institute than a traditional biotech. Calico is unlikely to be rushing a candidate into Phase I.

Instead, it will reportedly look into questions like what elements are shared by the genomes of thousands of healthy 90-year-olds from all parts of the world and how we can use this information to extend the lives of the broader population. The vision of Calico that has emerged in early media reports is one of a company underpinned by the genetic breakthroughs of the past decade and likely to use computing power to extract fresh insights from the data.

[UCLA Professor George Geis is absolutely right. The "ecosystem" of genomics has changed forever. As pharma-guru Karoly Nikolich cited (at 1:04 minutes of my Churchill Club YouTube of Genome Computer panel); "sooner of later a big IT company, like Google, will buy or build their own "pharma"". Now it is up to Samsung, Sony/Olympus/Illimina, Siemens, Google, Apple, GE health, Cisco, Calico, Longevity etc. "to leverage" Old Pharma. The magazine Newsweek, however, is also absolutely right - "you can not cure what you can not understand". Thus, as all IT know, without buying/building the algorithmic IP the blood bath ahead might be similar to the Internet "search engine legacy" (let the best algorithm rule not only understanding of the net, but ruling the business - the core question may be what is the (fractal recursive) mathematical algorithm of genome function?). "Privacy" is not the name of the game in cancer - "Survival" (precision medicine) would be a more likely answer by e.g. the late Steve Jobs. - Pellionisz]

Dr. Erez Aiden named newest McNair Scholar at Baylor College of Medicine

Glenna Picton

(713) 798-7973

Houston, TX - Mar 26, 2014

Award-winning scientist Dr. Erez Aiden has been named the newest McNair Scholar at Baylor College of Medicine.

The McNair Scholar program at Baylor identifies established and rising stars in biomedical research to be recruited to Baylor. The program is supported by the Robert and Janice McNair Foundation and managed by the McNair Medical Institute.

Aiden and his collaborators invented the Hi-C method for three-dimensional genome sequencing and Aiden subsequently led the team that reported the first three dimensional map of the human genome. His lab continues to develop powerful new technologies and methods for interrogating genomes in three dimensions.

With funding from the McNair Scholar Program and the Cancer Prevention and Research Institute of Texas, Aiden was recruited to Baylor as an assistant professor of genetics. He holds a joint appointment as an assistant professor of computer science and applied mathematics at Rice University.

Aiden received his undergraduate degree from Princeton University; completed a Master of Arts degree in history from Yeshiva University; and completed a Master of Arts degree in Applied Physics as well as a Ph.D. in Applied Math and Health Sciences and Technology from Harvard University and the Massachusetts Institutes of Technology in Cambridge. Subsequently, Aiden was a fellow at the Harvard Society of Fellows and a visiting faculty member at Google, Inc.

His research has won numerous awards including the Lemelson-MIT prize for best student inventor at MIT; membership in Technology Review's 2009 TR35, recognizing the top 35 innovators under 35; and a National Institutes of Health New Innovator Award.

In 2012, he received the President's Early Career Award in Science and Engineering, the highest government honor for young scientists, awarded by the President of the United States. His work has been featured on the front page of the New York Times, the Boston Globe, and the Wall Street Journal, and his online talks have been viewed over a million times. Fast Company recently called Aiden “America's brightest young academic.”

[Some readers may become confused about "discovery of genomes in three dimensions". Now that old axioms have fallen to the degree that "modern genomics is a well-dressed gentleman with no shoes", anything overthrew the three-dimensional "double helix" (Franklin, Watson, Wilkinson and Crick, 1953?). The reader may rest assured that the three-dimensional "double helix" stands strong as ever! So what is the fuss about "three dimensionality"? Actually, nothing was discovered lately about "three dimensional folding of the DNA strand", since Grosberg's papers some two decades ago. The spectacular invention by the genius (Erez Aiden) is the so-called "Hi-C method" (see reference below) to map out the functional proximity of parts of the 2m-long human DNA noodle; arriving at the astonishing proof that the linearly distant parts are functionally extremely close. The FractoGene approach to genome function (by Pellionisz, "fractal genome grows fractal organism) since 2002, see timeline, explicitly required by The Principle of Recursive Genome Function (2008) that the genome is red in a massively parallel fashion (and it was a total misunderstanding that just because the DNA strand is arranged and transcribed linearly, it would follow that the function would have to serial as well). Just like a book where letters are arranged one-by-one from cover-to-cover, the page-system of organization permits to jump from the Table of Contents to the middle or end-part of the book, with basically identical ease (see more elaborate explanation at "Mr. President - the Genome is Fractal!)]

J Vis Exp. 2010 May 6;(39). pii: 1869. doi: 10.3791/1869.

Hi-C: a method to study the three-dimensional architecture of genomes.

van Berkum NL1, Lieberman-Aiden E, Williams L, Imakaev M, Gnirke A, Mirny LA, Dekker J, Lander ES.

Author information


The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, into close spatial proximity (2-6). Deciphering the relationship between chromosome organization and genome activity will aid in understanding genomic processes, like transcription and replication. However, little is known about how chromosomes fold. Microscopy is unable to distinguish large numbers of loci simultaneously or at high resolution. To date, the detection of chromosomal interactions using chromosome conformation capture (3C) and its subsequent adaptations required the choice of a set of target loci, making genome-wide studies impossible (7-10). We developed Hi-C, an extension of 3C that is capable of identifying long range interactions in an unbiased, genome-wide fashion. In Hi-C, cells are fixed with formaldehyde, causing interacting loci to be bound to one another by means of covalent DNA-protein cross-links. When the DNA is subsequently fragmented with a restriction enzyme, these loci remain linked. A biotinylated residue is incorporated as the 5' overhangs are filled in. Next, blunt-end ligation is performed under dilute conditions that favor ligation events between cross-linked DNA fragments. This results in a genome-wide library of ligation products, corresponding to pairs of fragments that were originally in close proximity to each other in the nucleus. Each ligation product is marked with biotin at the site of the junction. The library is sheared, and the junctions are pulled-down with streptavidin beads. The purified junctions can subsequently be analyzed using a high-throughput sequencer, resulting in a catalog of interacting fragments. Direct analysis of the resulting contact matrix reveals numerous features of genomic organization, such as the presence of chromosome territories and the preferential association of small gene-rich chromosomes. Correlation analysis can be applied to the contact matrix, demonstrating that the human genome is segregated into two compartments: a less densely packed compartment containing open, accessible, and active chromatin and a more dense compartment containing closed, inaccessible, and inactive chromatin regions. Finally, ensemble analysis of the contact matrix, coupled with theoretical derivations and computational simulations, revealed that at the megabase scale Hi-C reveals features consistent with a fractal globule conformation.

Getting Cancer Wrong

By Alexander Nazaryan / March 20, 2014 1:23 PM EDT

[Newsweek cover, March 28, 2014]

[I am sorry, I could not resist inserting at this time-point a symbolic diagram of my fractal-chaotic approach to genome (mis)regulation (2012), priority date 2002 Aug. 1., the reversal of junk/central dogmas (2008, 2008 Google Tech Talk YouTube) the concept of fractal iterative recursion reaching back to my book chapter 1989 - Dr. Pellionisz]

From his fourth-floor window at Tampa's Moffitt Cancer Center, Robert A. Gatenby can look down to where patients stand waiting for valets to retrieve their cars. They have gone through chemotherapy, biopsies, radiation. They are pale, anxious, resolute. Some will live and some will die: a young woman with short hair, clutching her partner's hand; an older man, alone. Students from the nearby University of South Florida pop out of patients' cars. Peppy and dressed in blue vests, these cheerful valets look as if they could be working at a luxury hotel in the tropics. But nobody here is on vacation.

Gatenby says he sometimes sees patients retching after chemotherapy, which reminds the 62-year-old radiologist that his Integrated Mathematical Oncology Department—the only full-scale outfit of its kind in the nation—does not have the luxury of time. Mathematics is not generally known for urgency. Few lives hinge on proof of the twin prime conjecture, but the mathematicians and oncologists Gatenby has assembled in Tampa are trying to tame the chaos of cancer in part through the same differential equations that have tortured so many generations of calculus students. By mathematically modeling cancer, they hope to solve it, to make its movements as predictable as those of a hurricane. The patients down there, fresh from treatment, need shelter from the storm.

Gatenby's small corner of Moffitt bears little resemblance to a medical center: There are no white-coated doctors frantically rushing to save patients or synthesizing miracle cures deep into the night. You might think you've found yourself in a sleepy academic department where abstract ideas are kicked around like a soccer ball on the college green. Which, come to think of it, is actually a pretty accurate description of what goes on in Gatenby's lab, though not at all a pejorative one. The mathematicians in his employ are convinced that we do not really understand cancer and that, until we do, our finest efforts will be tantamount to swinging swords in utter darkness. As far as these Tampa iconoclasts are concerned, your average cancer doctor is trying to build a jetliner without having grasped aerodynamics: Say, how many wings should we slap on this thing?

A Malicious Green Cloud

We have been fighting the War on Cancer since 1971, when President Richard M. Nixon declared that the "time has come in America when the same kind of concentrated effort that split the atom and took man to the moon should be turned toward conquering this dread disease." Four decades later, 1,665,540 Americans per year hear the dreaded diagnosis, and about 585,720 die annually from some variety of the disease, according to the American Cancer Society. Smallpox and polio have been cured or largely eradicated, but cancer remains the same scourge it was 4,500 years ago, when the Egyptian doctor Imhotep mused, in what may have been civilization's first stab at oncology, about how to treat "bulging masses on [the] breast." Modern oncology makes incremental advances, with a melanoma drug that extends survival by three months passing for a major breakthrough. This is nobody's fault, but everybody's problem.

Gatenby is tired of a fight we keep losing. After 30 years, he has come to the uneasy conclusion that cancer is smarter than we are, and will find ways to evade our finest medical weaponry. The weary warrior wants to make peace with cancer's insurgent cells—though on his own terms, terms that would spare the lives of many more patients. To some within the medical establishment, this might seem preposterous, but Gatenby relishes the role of the outsider.

Gatenby grew up in the Rust Belt town of Erie, Pa., where 12 years of Catholic school instilled in him "an incredible hatred of dogma." At Princeton University, he studied physics with some of the greatest scientific minds of the 20th century. Figuring he wasn't fated to join the physics pantheon, Gatenby turned to medicine. But medical school at the University of Pennsylvania was dismayingly similar "to the rote learning of catechism" he remembered from Saint Luke School. It felt like he was "going backwards."

Whether in the lab, the classroom or the clinic, Western medicine relies on cautious experimentation, its zeal for breakthroughs tempered by the Hippocratic injunction to do no harm. But that can foster a frustrating incrementalism that is itself injurious. David B. Agus, one of the nation's most prominent oncologists and a professor at the University of Southern California, explains that "you are not rewarded, in general, for taking risk. It's very scary to do something radically new."

Gatenby specialized in radiology and, after receiving his medical degree in 1977 and completing a residency, went to work in 1981 for the Fox Chase Cancer Center in Philadelphia. Fox Chase is to cancer research what the Boston Garden was to professional basketball. It was home to David A. Hungerford, one of two researchers responsible for discovering the Philadelphia Chromosome, a major clue to cancer's birth within the human genome. Among its current éminences grises is Alfred G. Knudson Jr., whose "two-hit" hypothesis holds that cancer is triggered by an unfortunate accumulation of errant genes, harmful outside events (too much sun, too much red meat) or a combination of the two.

The study of genes did not interest Gatenby back then, nor does it interest him now, even though much of medicine is now in the thrall of genomics. Gatenby wanted to discover cancer's "first principles," [Why not consider The Principle of Recursive Genome Function as a reasonable hypothesis? - AJP] the basic ideas behind the seemingly sudden explosion of cells that want to kill the very body that nourishes them. Sure, you could know the BRCA1 gene better than you know your own mother, but unless you had some insight into why it caused a furiously impervious breast cancer, you were trying to find your way out of a forest by studying the bark of a single tree. Gatenby sought to understand cancer with the same totality that Newton had understood gravity.

As with Newton's famous laws of motion, mathematics seemed to hold the key. Math had been used to model the weather and financial markets, which like the human body are fickle and incredibly sensitive to outside forces (a run on Greek banks; a low-pressure system moving down from Canada). Gatenby saw no reason the same could not hold true for cancer. He spent a year reading math, which puzzled his colleagues. Then, while visiting the Cloisters museum in upper Manhattan with his family, he took a sheet of stationery and started scratching down equations he thought could get him closer to cancer's fundamental truths.

"To say they hated it would not do justice," Gatenby says of the response of his Fox Chase colleagues. Other oncologists told him that "math modeling is for people too lazy to do the experiment" and that "cancer is too complicated to model." The latter is a refrain that, 30 years later, still dogs Gatenby and his staff at the Integrated Mathematical Oncology Department, which includes five mathematicians with no formal experience in medicine.

Among those five is Sandy Anderson, a young Scotsman who dresses as if he were on the way to a Beck concert. There is a bottle of single malt on his desk. "Of course cancer is complex," Anderson tells me, brogue rising. "But how can you say it's too complex? That complexity should be viewed as a challenge that we have to try and tackle. And just because there's complexity doesn't mean there aren't simple rules underlying it.

"What we'd love to do is have everybody's own little hurricane model for their cancer," he explains. This is less a metaphor than you may imagine. Anderson shows me computer models of a breast cancer's growth, the cells spreading like a malicious green cloud across the screen. Different versions of the model show what happens when different treatments are applied: Sometimes the cancer slows, but sometimes it explodes. This seems like an intuitively rational approach to the disease, predicting how it responds to a variety of treatments. But it isn't common. There are about a dozen drugs for breast cancer approved by the Food and Drug Administration. Depending on which form of the disease is diagnosed and at what stage it's discovered, there's a maddening number of viable drug combinations. Best practices exist, but these can be anecdotal, doctors simply doing what they think works. The War on Cancer is fought by competing bands with their own weapons, cancer's chaos exacerbated by our own dismaying disorder. Anderson would like to provide the onco-soldiers with battlefield maps.

Wrong But Useful

Weather often came up during my time in Tampa, and not only because a wet dreariness lingered in the Florida skies. In 1961, Edward N. Lorenz of the Massachusetts Institute of Technology tried to create computer models for weather, only to stumble into the field of chaos theory. He saw that weather was entirely dependent on initial conditions, so that if he altered his inputs by even a fraction of a percentage, the weather model would fluctuate to an unexpected degree, in unexpected directions. Yet patterns did emerge. This would come to be called "deterministic chaos," for the way complex adaptive systems—the weather, the global economy, maybe cancer—can both hew to our expectations and routinely subvert them. Sometimes, autumn acts like autumn. But once in a while, in Lorenz's famous formulation, a butterfly causes a hurricane.

One refrain I heard several times at Moffitt was that "all models are wrong, but some are useful," a quip by the late mathematician George E.P. Box. A mouse injected with melanoma is only an imperfect model of human cancer; if it weren't, you wouldn't be reading this article today, for, as Anderson acidly notes, "We've solved cancer in mice a hundred thousand times." This is a model, too:

[here there is a simple equation, but as we know the "maddening complexity" of the Mandelbrot Set is just Z=Z^+C. Computers of IBM, Samsung, Sony, BGI, Google, Apple (etc) do and will only understand algorithms, and simply ignore "anecdotal lamenting on too much complexity" - AJP]

If that freaks you out, don't worry—it freaks out a lot of clinicians. Gatenby and his team are doing the math for them, convinced that their models of cancer strike the right balance between specificity and universality.

The other option is to keep chasing errant genes and trying to snuff them out, but that seems to many like a futile enterprise, sort of like trying to plug a leaking dam with wads of cotton. A tumor that weighs just 10 grams, Gatenby says, contains more cells than there are humans on earth. Nor are those cells a uniform gray mass, as the popular conception of cancer has it. As the tumor grows, different mutations may come to the fore, sort of the way a military assault may deploy infantry and artillery at different times in an attack. The cells of a single cancer differ within a single patient, and the same types of cancers differ from patient to patient. Talking about a prototypical cancer, then, is about as helpful as talking about a prototypical dog.

"It's almost like it's an intelligent opponent," says Donald A. Berry, who heads the biostatistics department at the M.D. Anderson Cancer Center in Houston. "It has many, many paths that it can take." Mathematics, Berry says, can "provide answers where biology runs into a wall."

One of those walls is the sheer amount of information cancer researchers would need to map every possible genetic mutation possible for the 200 cancers that can ravage the human body. Researchers have spent $375 million to create the Cancer Genome Atlas, which is based on the screening of 10,000 cancer samples for the responsible genes. Some think that until we've sorted through about 100,000 samples, the cancer gene compendium will be woefully incomplete. "It would be crazy not to have the information," the geneticist Eric S. Lander told The New York Times.

But information brings its own delusions. Gatenby laments the "vast industry that's developed over molecular data." He is frustrated by the narrow focus of many of his colleagues. The bookshelves in his office don't hold the standard medical tomes; they are instead lined with rare physics texts from the early 20th century, including several volumes of the Annalen der Physik, which published the pioneering work of Einstein, Hertz and Planck. Nestled among these is a copy of Everyone Poops—Gatenby recently became a grandfather.

The most curious (and most telling) book on Gatenby's shelf is The Truth in Small Doses: Why We're Losing the War on Cancer-and How to Win It. Having survived Hodgkin's lymphoma as a young man, Clifton Leaf decided to investigate why cancer medicine had made so few advances in recent years. The resulting Fortune article in 2004, as well as his book last year, offers little cause for optimism, with their depiction of a medical culture whose caution has gradually ossified into maddening inertia.

"I like big thinkers," Leaf told me when I asked him about Gatenby's work. "He's a guy who doesn't get stuck in orthodoxy." As Leaf writes in his book, the whack-a-gene approach to cancer has its finest success story in Gleevec, which, since its introduction about a decade ago, has proved an adept warrior against chronic myelogenous leukemia. It does exactly what proponents of the genetic approach to cancer hope, seeking out the tyrosine kinase enzymes that drive the growth of the once-deadly blood cancer. Time magazine put Gleevec on its cover in 2001, asking, "This little pill targets cancer cells with uncanny precision. Is it the breakthrough we've been waiting for?"

Unlike most solid-tumor cancers, the type of leukemia Gleevec cured is spurred by a single "driver" mutation. Render it inert, as Gleevec does, and the cancer is largely defeated. But few other iterations of the disease are so simple. The closest successor drug is Herceptin, which targets breast cancer tumors with the HER2-positive genetic alteration. Otherwise, targeted therapy has not fulfilled its promise; chasing after errant genes through the body is like trying to catch a school of tuna with a Ziploc bag.

And so Gatenby and his team have taken the opposite tack, going way big and trying to understand all of cancer, instead of just one or two genes. Gatenby told me a story about a cancer conference in Toronto where all attendees were introduced by the name and the molecule they were studying. He chuckles at this myopia, divorced from any greater vision of the Brobdingnagian disease.

'A Blind, Emotionless Alien'

Gatenby knows that all his equations will mean nothing if they don't help patients. Ultimately, he will have to convince the very clinicians who frustrate him that his abstractions can have real-world benefits. He needs to not only predict the hurricane but also save the cities in its path.

In 2000, Gatenby went to the University of Arizona and was named the head of radiology at its College of Medicine in 2005. It was here in the desert of Tucson that he had an intellectual conversion. He had been publishing mathematical models of cancer during the past two decades at Fox Chase, but now he began to understand the role that evolution plays in carcinogenesis. The first principles of cancer that he had been trying to find, Gatenby surmised, lay in the Darwinian concept of natural selection.

Gatenby's insight was brilliantly counterintuitive: Cancer is really, really good at evolution. So damn good that our bodies nourish it, even as it hijacks blood vessels and nutrients. It fools the immune system, nestling so deep within normal tissue that we can't easily extract it. And then, in what amounts to suicide, it kills the very body in which it has taken root. The writer Christopher Hitchens once described the esophageal cancer that would soon kill him as a "blind, emotionless alien." But that alien is actually a native son.

Math could provide a map of cancer's movements; Gatenby now understood that only Darwin could explain why that movement was so hard to arrest. We were unwittingly helping that evolution along, turning all too many cancers into hurricanes. Worst of all, we were doing it in the name of saving lives.

Gatenby was convinced by studying pest management, of all disciplines. By the early 1970s, the agricultural industry had come to realize the limit of synthetic pesticides, which had been famously demonized by Rachel Carson's Silent Spring in 1962. They were not only potentially harmful to humans but possibly not all that good at protecting crops. If used indiscriminately, chemical agents would indeed kill plenty of insects, but those that survived had a resistance to the toxic substance, which could do nothing against the remaining pests, which were free to breed. This was the evolutionary version of the cliché about how the thing that doesn't kill you makes you stronger. Our efforts to vanquish the bugs forced evolution's hand.

A little more than a month after signing the National Cancer Act on December 23, 1971, Nixon addressed Congress on the nation's environmental challenges. Among the initiatives he introduced was Integrated Pest Management, which promised "judicious use of selective chemical pesticides in combination with nonchemical agents and methods," like the deployment of natural predators. Instead of trying to kill all bugs, Integrated Pest Management would try to control the population, less concerned with annihilation than watchful containment. There would always be some bugs; the goal was to keep them from spreading, often by using less than the maximum dosage of pesticide.

The War on Cancer sold the American public (and much of the medical establishment) on the idea that cancers must be vanquished entirely, that no stalemate was possible. Thus the endless rounds of chemo a patient faces today, killing good cells with the bad. Gatenby thought that Integrated Pest Management offered a rejoinder to that all-or-nothing mentality. The bug guys had realized what the cancer guys hadn't: You raze an entire enemy city, and those who remain will be hardened insurgents with a lust to kill. But trim away strategically at the enemy's forces, and the rest of the population will be kept at bay. Treatment, in other words, may aggravate a cancer's growth by stripping away the easy-to-kill cells and leaving behind hardened carcinogenic warriors.

"Evolution will win this game," Gatenby tells me. Malignant cells will eventually evolve beyond the capacity of any drug to hold them at bay. Even the patients of wonder drug Gleevec face an eventual recrudescence of chronic myelogenous leukemia. The question is whether a mathematical understanding of how cancer progresses can lead to treatments that are less prone to aggravating resistant cells into proliferation.

Gatenby came to Moffitt in 2008 to fix the radiology department. Though he continues to do clinical rounds one day each week, his intellectual energies have clearly shifted to the Integrated Mathematical Oncology Department, which has six full-time members and about a dozen postdoctoral and graduate students. They know that many think they are on a quixotic quest. They know that the money is in drug development. They know that too many people are dying. And yet there they are, jovially scrawling equations on a blackboard.

Ravaged by Rambo

So how do you defeat a disease that is constantly evolving a resistance to our weapons?

Maybe by turning your swords into plowshares. In 2009, Gatenby published a paper in Cancer Research called "Adaptive Therapy." Gatenby posited that a tumor consisted, in essence, of chemo-sensitive cells, fast to proliferate, and chemo-resistant cells, more reluctant to grow. The standard practice of giving the maximum tolerated dose of chemo would clear out the sensitive cells, leaving behind a tough nugget of impervious cells, the al-Qaida rebels of the bunch. These previously dormant cells would now pour out of their caves, suddenly finding both space and nourishment to grow. And grow they would, with the barrier of the sensitive cells gone. In essence, cancer therapy was killing "good" cancer cells while leaving behind "bad" ones.

Gatenby used both mathematical models and in vivo experiments to show that adaptive therapy, which kept some of cancer's petty criminals around, actually held the most dangerous cells in abeyance. One of his co-authors on the 2009 paper was Ariosto S. Silva, a mathematician now at Moffitt. Silva, who is Brazilian, likes to explain cancer through the Rambo film First Blood, about a bloodthirsty Sylvester Stallone protagonist who is made an especially vicious killer because of the suffering he endured in Vietnam. Our approach to chemotherapy is turning cancer cells into Rambos, Silva explained when I met him in Tampa.

A recent innovation is the use of ersatzdroges, or "fake drugs," which target chemo-resistant cells without killing them. In a draft paper titled "Sweat but No Gain," Gatenby and his Moffitt colleagues describe how multi-drug-resistant cells "continue to activate their membrane pumps to extrude the ersatzdroge as though it were a cytotoxic agent," that is, an actual chemotherapeutic drug. But it isn't. The cells don't know that, however, working furiously to defend themselves, "thus causing a decrease in fitness by limiting available resources for proliferation and invasion." While research into ersatzdroges is relatively new, Gatenby's paper suggests that tiring cells out instead of killing them does slow tumor growth. Instead of evolving with their resistance, the cells expend all their energy staying afloat.

Some oncologists are skeptical of Gatenby's approach. Robert Weinberg, the MIT cancer researcher who discovered the first cancer-causing gene, does not believe mathematical oncology is a fruitful pathway because it "lacks predictive powers that extend beyond predictions made from simple, intuitive assessments of future behavior," as he told me in an email. Others say that while Gatenby's evolutionary portrait of cancer is a clever analogy, it is not instructive for treatment of the disease. Marc B. Garnick, a urologic cancer specialist at the Beth Israel Deaconess Medical Center and Harvard Medical School, says Gatenby's ideas mirror the practice of metronomic therapy, which "has been around for decades." (Gatenby disputes this claim.)

But for clinicians frustrated with the current pace of progress in the War on Cancer, Gatenby at the very least offers a new way of thinking about a disease that has perplexed humanity for thousands of years.

Athena Atkipis, an evolutionary biologist and co-founder of the Center for Evolution and Cancer at the University of California, San Francisco (and a sometime colleague of Gatenby's), likes to think of the different approaches to the War on Cancer in terms of Greek mythology. "My name is Athena, I know," she says by way of disclaimer before launching into an explanation: The god of war, Ares, understandably "likes a good fight." Athena, meanwhile, is a master strategian, always scheming about how to outwit the enemy. Her namesake would know better, Atkipis implies, than trying to "intimidate the cancer into retreating."

In Tampa, Gatenby and I went to dinner at a Cajun restaurant with Anderson and Silva, two of Moffitt's mathematicians. Downing his first drink, Anderson indicated his distaste for most of what passes for oncology today: "We keep measuring s**t without getting anything out of it." Everyone laughed. Gatenby complained about how the first fancy car he'd ever purchased had had its cool compromised by the installation of a car seat. Everyone laughed again. It was like the scene in The Untouchables when Eliot Ness, the famed Prohibition enforcer played by Kevin Costner, takes his lawmen out for a celebratory dinner after a huge cache of booze has been found and summarily destroyed. They are drunk with elation, but also a little anxious: The main target, Al Capone, remains at large. So it was in Chicago. So it was in Tampa, only with drinks.

"I've never seen a dogma I didn't hate," Gatenby told me. That was true at the Catholic school in Pennsylvania. And it is true today, at the hospital in Florida, where the cancer patients are waiting.

[Finally, we have a leading weekly (Newsweek) having made quite a turn-around! Of course, quite soon many will say (in retrospect...) that "we have never believed in the Central Junk Dogmas". It was "understandable" that prior to conclusion of ENCODE in 2007 when the US government came out with refutation of the dogma of Junk, our manuscript to Science, authored by 25 experts worldwide, went "unpublished without review" (2006). It was less understandable that the Old Newsweek in 2007 totally censored out a brilliant article by Princeton's Prof. Lee Silver from its USA/Canada edition (that appeared in European, South American and Asian Editions). Now, just a fortnight after Newsweek's eye-opener article (Hacking Your DNA, see in this column), the USA appears to wake up to the biggest paradigm-shift in science/technology/health-care/defense (of HoloGenomics) - ever! Not entirely surprisingly, the US was also a bit tardy with the paradigm-shift with nuclear science/technology, until (the Hungarian Dr. Szilard, driven by Teller to Einstein) alerted the establishment to get going "American Industry Style". As the two articles below show, both China and through an award-winning lecture-tour by AJP to India, the Asian world-powers, along with Samsung of Korea and Sony of Japan, are actually ahead at this time - though the US expresses its interest by dishing out encouraging prizes; most recently the Hertz Fellowship to Erez Lieberman-Aiden, for his pioneering the fractal genome in 2009. - Dr. Pellionisz]

Fractal geometry to help diagnose cancer

The Times of India
TNN | Feb 20, 2014, 03.12AM IST

NAGPUR: Human organs cannot always be represented through geometrical shapes. That is why several scientists have felt the need to widen the scope of science to include non-linear mathematics. A team of oral pathologists from city's VSPM Dental College and Research Centre have come up with a solution for this in a study about utilizing fractal geometry that has the ability to quantify irregular and complex objects by finding symmetry in them.

Though the study is still in its initial phase, it has already been presented at King George Medical University of Lucknow where it bagged the first prize in the poster competition at International Oral Pre-Cancer and Cancer Congress 2014. If utilized properly, fractal geometry can be a helpful diagnostic tool. By establishing a standard or normal range of fractal dimension, this measure can be used for diagnosis of oral cancer. Fractals are objects formed from sub-parts that resemble the whole object exactly or statistically.

[Pellionisz received an Award from India for his Fractal Approach to Genomics, presented in a Guest of Honor Lecture Tour - 2012]

Designing Fractal Nanostructured Biointerfaces for Biomedical Applications

[See full .pdf of Chinese Fractals, 2014]

Pengchao Zhang[a, b] and Shutao Wang*[a]

[a] Dr. P. Zhang, Prof. S. Wang

Beijing National Laboratory for Molecular Sciences (BNLMS)

Key Laboratory of Organic Solids, Institute of Chemistry

Chinese Academy of Sciences (ICCAS), Beijing, 100190 (P.R. China)

Fax: (+86) 010-82627566


[b] Dr. P. Zhang

University of Chinese Academy of Sciences

Beijing 100049 (P.R. China)

Conclusions and Outlooks

Fractal structures can provide a unique “fractal contact mode”

that ensures an outward, 3D, and spatial contact for biomarkers,

a reduced diffusion length for small biomarkers to the surface

of the sensor, and enhanced topographic interaction by

matching the fractal dimensions of the tumor cells, which

makes biomarkers easily accessible to probes and consequently

promotes detective efficiency and sensitivity. Fractal nanostructured

biointerfaces have been proven to be effective for

the ultrasensitive detection of various biomarkers with extremely

low abundances in clinical samples, and this paves the

way for the further exploitation of these nanostructures in biomedical

applications. Moreover, the successful detection of disease-

relevant biomarkers, such miRNA, CA-125, and MCF7 cells,

from unpurified cell lysates and from the blood of patients

makes these nanostructures promising for practical clinical use.


We thank the National Research Fund for Fundamental Key Projects

(2012CB933800), the National Natural Science Foundation

(21121001, 21127025, 21175140, and 20974113), the Key Research

Program of the Chinese Academy of Sciences (KJZD-EW-M01), the

National High Technology Research and Development Program

of China (863 Program) (2013AA031903), and the National Instrumentation

Program (NIP) (2013YQ190467) for financial support.

The New York Genome Center and IBM Watson Group Announce Collaboration to Advance Genomic Medicine

IBM Selected as First Technology Partner for Leading Genomic Research Institution; Project aims to Apply Advanced Analytics to Genomic Treatment Options for Brain Cancer Patients

IBM-NYC GENOME CENTER "HoloGenome" effort (0:30 sec)

NEW YORK, N.Y. - 19 Mar 2014: The New York Genome Center (NYGC) and IBM (NYSE: IBM) today announced an initiative to accelerate a new era of genomic medicine with the use of IBM’s Watson cognitive system. IBM and NYGC will test a unique Watson prototype designed specifically for genomic research as a tool to help oncologists deliver more personalized care to cancer patients.

NYGC and its medical partner institutions plan to initially evaluate Watson’s ability to help oncologists develop more personalized care to patients with glioblastoma, an aggressive and malignant brain cancer that kills more than 13,000 people in the U.S. each year. Despite groundbreaking discoveries into the genetic drivers of cancers like glioblastoma, few patients benefit from personalized treatment that is tailored to their individual cancer mutations. Clinicians lack the tools and time required to bring DNA-based treatment options to their patients and to do so, they must correlate data from genome sequencing to reams of medical journals, new studies and clinical records -- at a time when medical information is doubling every five years.

This joint NYGC Watson initiative aims to speed up this complex process, identifying patterns in genome sequencing and medical data to unlock insights that will help clinicians bring the promise of genomic medicine to their patients. The combination of NYGC’s genomic and clinical expertise coupled with the power of IBM’s Watson system will enable further development and refinement of the Watson tool with the shared goal of helping medical professionals develop personalized cancer care.

The new cloud-based Watson system will be designed to analyze genetic data along with comprehensive biomedical literature and drug databases. Watson can continually ‘learn’ as it encounters new patient scenarios, and as more information becomes available through new medical research, journal articles and clinical studies. Given the depth and speed of Watson’s ability to review massive databases, the goal of the collaboration is to increase the number of patients who have access to care options tailored to their disease’s DNA.

“Since the human genome was first mapped more than a decade ago, we’ve made tremendous progress in understanding the genetic drivers of disease. The real challenge before us is how to make sense of massive quantities of genetic data and translate that information into better treatments for patients,” said Robert Darnell, M.D., Ph.D., CEO, President and Scientific Director of the New York Genome Center. “Applying the cognitive computing power of Watson is going to revolutionize genomics and accelerate the opportunity to improve outcomes for patients with deadly diseases by providing personalized treatment.”

First Watson Application in Genomic Research

Watson will complement rapid genome sequencing and is expected to dramatically reduce the time it takes to correlate an individual’s genetic mutations with reams of medical literature, study findings, and therapeutic indications that may be relevant. The intention is to provide comprehensive information to enable clinicians to consider a variety of treatment options that the clinician can tailor to their patient’s genetic mutations. It will also help NYGC scientists understand the data detailing gene sequence variations between normal and cancerous biopsies of brain tumors.

“As genomic research progresses and information becomes more available, we aim to make the process of analysis much more practical and accessible through cloud-based, cognitive innovations like Watson,” said Dr. John E. Kelly III, Senior Vice President and Director of IBM Research. “With this knowledge, doctors will be able to attack cancer and other devastating diseases with treatments that are tailored to the patient’s and disease’s own DNA profiles. If successful, this will be a major transformation that will help improve the lives of millions of patients around the world.”

The goal is to have the Watson genomics prototype assist clinicians in providing personalized genomic analytics information as part of a NYGC clinical research study. The solution has been under development for the past decade in IBM’s Computational Biology Center at IBM Research.

New York State’s Investment in Genomic Medicine

New York State is at the forefront of advancing medical science and commercialization. Governor Andrew M. Cuomo recently proposed $105 million to fund a partnership between NYGC and the University at Buffalo’s Center for Computational Research to advance genomics research. This investment to enhance the state’s genomic medicine capabilities, together with NYGC’s acquisition of Illumina’s state-of-the-art HiSeq X Ten whole human genome sequencing system, will accelerate the availability of valuable genomic information in New York.

“New York State’s investment in cutting-edge innovative industries is creating jobs and growing the economy in Western New York and across our state,” said Governor Cuomo. “This collaboration between the New York Genome Center and IBM will help make the region a new hub for the growing bio-tech industry.”

IBM is NYGC’s Founding Technology Member and will advance the organization’s goals of translating genomic research into clinical solutions for serious disease through the collaboration of medicine, science and technology. As biology increasingly becomes an information science, the promise of genomics is closer to reality with the help of data-driven analytics methods and more powerful computing systems. IBM and NYGC’s computational biology experts are renowned for accelerating life sciences discoveries using deep analytical approaches and next generation information technologies.

Learn more about this story at

To view a Flickr image gallery that illustrates today’s news please click here.

For additional perspectives on this story, please watch this video.

To join the social conversation on Twitter use the hashtag #NYGCWatson.

Journalists and bloggers can download broadcast video, b-roll and photos about the Watson and New York Genome Center collaboration at The video is available in HD, standard definition broadcast and streaming quality.

About the New York Genome Center

The New York Genome Center (NYGC) is an independent, nonprofit at the forefront of transforming biomedical research and clinical care with the mission of saving lives. As a consortium of renowned academic, medical and industry leaders across the globe, NYGC focuses on translating genomic research into clinical solutions for serious disease. Our member organizations and partners are united in this unprecedented collaboration of technology, science, and medicine. We harness the power of innovation and discoveries to improve people’s lives - ethically, equitably, and urgently. Member institutions include: Albert Einstein College of Medicine, American Museum of Natural History, Cold Spring Harbor Laboratory, Columbia University, Cornell University/Weill Cornell Medical College, Hospital for Special Surgery, The Jackson Laboratory, Memorial Sloan-Kettering Cancer Center, Icahn School of Medicine at Mount Sinai, New York-Presbyterian Hospital, The New York Stem Cell Foundation, New York University, North Shore-LIJ, The Rockefeller University, Roswell Park Cancer Institute and Stony Brook University. For more information, visit:

About IBM Watson

Named after IBM founder Thomas J. Watson, Watson was developed in IBM’s Research labs and is now being accelerated into market by the new Watson Group. Watson represents a new class of software, services and apps that think, improve by learning, and discover answers and insights to complex questions from massive amounts of Big Data. Watson’s ability to answer complex questions posed in natural language with speed, accuracy and confidence is transforming decision-making across a variety of industries, including health care, financial services and retail. IBM has advanced Watson from a game-playing innovation into a commercial technology. Using natural language processing and analytics, Watson processes information akin to how people think, representing a major shift in an organization’s ability to quickly analyze, understand and respond to Big Data. Now delivered from the cloud and able to power new consumer and enterprise services and apps, Watson is 24 times faster, smarter with a 2,400 percent improvement in performance, and 90 percent smaller – IBM has shrunk Watson from the size of a master bedroom to three stacked pizza boxes. IBM is investing $1 billion to introduce a new class of cognitive computing services, software and apps, and investing $100 million to spur innovation for software application providers to develop a new generation of Watson-powered solutions. Learn more about IBM Watson at Learn more about IBM Research at

Learn more about IBM healthcare at

[IBM just about completes the list of Samsung, Sony/Olympus/Illumina, Google, Google & Apple (Calico, Inc.), BGI/Complete Genomics and other IT Giants - Dr. Pellionisz]

A novel mechanism for fast regulation of gene expression


March 18, 2014

Our genome, we are taught, operates by sending instructions for the manufacture of proteins from DNA in the nucleus of the cell to the protein-synthesizing machinery in the cytoplasm. These instructions are conveyed by a type of molecule called messenger RNA (mRNA).

Francis Crick, co-discoverer of the structure of the DNA molecule, called the one-way flow of information from DNA to mRNA to protein the "central dogma of molecular biology."

Yehuda Ben-Shahar and his team at Washington University in St. Louis have discovered that some mRNAs have a side job unrelated to making the protein they encode. They act as regulatory molecules as well, preventing other genes from making protein by marking their mRNA molecules for destruction.

"Our findings show that mRNAS, which are typically thought to act solely as the template for protein translation, can also serve as regulatory RNAs, independent of their protein-coding capacity," Ben-Shahar said. "They're not just messengers but also actors in their own right." The finding was published in the March 18 issue of the new open-access journal eLife.

Although Ben-Shahar's team, which included neuroscience graduate student Xingguo Zheng and collaborators Aaron DiAntonio and his graduate student Vera Valakh, was studying heat stress in fruit flies when they made this discovery, he suspects this regulatory mechanism is more general than that.

Many other mRNAs, including ones important to human health, will be found to be regulating the levels of proteins other than the ones they encode. Understanding mRNA regulation may provide new purchase on health problems that haven't yielded to approaches based on Crick's central dogma.

Is gene expression regulated directly?

Ben-Shahar's original objective was to better understand how organisms maintain their physiological balance when they are buffeted by changes in the environment.

Neuroscientists know that if you warm neurons in culture, he said, the neurons will fire more rapidly. And if the culture is cooled down, the neurons slow down. Neurons in an organism, however, behave differently from those in a dish. Usually the organism is able to cushion its nervous system from heat stress, at least within limits. But nobody knew how they did this.

As a fruit fly scientist, Ben-Shahar was aware that there are mutations in fruit flies that make them bad at buffering heat stress, and this provided a starting point for his research.

One of these genes is actually called seizure, because flies with a broken copy of this gene are particularly sensitive to heat. Raising the temperature even 10 degrees sends them into seizures. "They seize very fast, in seconds," Ben-Shahar said."When we looked at seizure (sei) we noticed that there is another gene on the opposite strand of the double-stranded DNA molecule called pickpocket 29 (ppk29)," Ben-Shahar said. This was interesting because seizure codes for a protein "gate" that lets potassium ions out of the neuron and pickpocket 29 codes for a gate that lets sodium ions into the neuron.

Neurons are "excitable" cells, he said, because they tightly control the gradients of potassium and sodium across their cell membranes. Rapid changes in these gradients cause a nerve to "fire," to stop firing, and to repolarize, so that it can fire again.The scientists soon showed that transcription of these genes is coordinated. When the flies are too hot, they make more transcripts of the sei gene and fewer of ppk29. And when the flies cooled down, the opposite happened. If the central dogma held in this case, the neurons might be buffering the effects of heat by altering the expression of these genes.

One problem with this idea, though, is that gene transcription is slow and the flies, remember, seize in seconds. Was this mechanism fast enough to keep up with sudden changes in the environment?

Does RNA interference regulate gene expression?

But the scientists had also noticed that the two genes overlapped a bit at their tips. The tips, called the 3' UTRs (untranslated regions), don't code for protein but are transcribed into mRNA.

That got them thinking. When the two genes were transcribed into mRNA, the two ends would complement one another like the hooks and loops of a Velcro fastener. Like the hooks and loops, they would want to stick together, forming a short section of double-stranded mRNA. And double-stranded mRNA, they knew, activates biochemical machinery that degrades any mRNA molecules with the same genetic sequence.

Double-stranded RNA binds to a protein complex called Dicer that cuts it into fragments. Another protein complex, RISC, binds these fragments. One of the RNA strands is eliminated but the other remains bound to the RISC complex. RISC and its attached RNA then becomes a heat-seeking missile that finds and destroys other copies of the same RNA. If the mRNA molecules disappear, their corresponding proteins are never made.

It turned out that heat sensitivity in the fly is all about potassium channel, said Ben-Shahar. What if, he thought, the two mRNAs stuck together, the mRNA segment encoding the potassium channel was bound to RISC and other copies of the potassium channel mRNA were destroyed. This was another, potentially faster way the neurons might be controlling the excitability of their membranes.

A designer fly provides an answer

Which is it? Is regulation occurring at the gene level or the mRNA level?

To find out, the scientists made designer fruit flies that had various combinations of the genes and their sticky noncoding ends. One of these transgenic fly lines was missing the part of the gene coding for the ppk29 protein but still made lots of mRNA copies of the sticky bit at the end of ppk29. When there were lots of these isolated sticky bits, sei mRNA levels dropped. This fly was as heat sensitive as a fly completely missing the sei gene.

This combination of genotype and phenotype held the answer to the regulatory problem. First of all, mRNA from one gene (ppk29) is regulating the mRNA of another gene (sei). And, second, the regulatory part of ppk29 is the untranslated bit at the end of the mRNA. When this bit sticks to a complete transcript of the sei gene (including, of course, its sticky bit), the RISC machinery destroys any copies of the sei mRNA it finds.

So the gene that codes for a sodium channel regulates the expression of the potassium channel gene. And it does so after the genes are transcribed into mRNA; it's mRNA-dependent regulation.

The interaction between sei and ppk29 is unlikely to be unique, Ben-Shahar said. The potassium channel is highly conserved among species, and analyses of the genome sequences in flies and in people show that two of three fly genes for this type of potassium channel and three of eight human genes for these channels have overlapping 3' UTR ends, just as do sei and ppk29.

Why does this regulatory mechanism exist? Ben-Shahar hates getting out in front of his data, but he points out that transcribing DNA into mRNA is a slower process than translating mRNA into protein. So it may be, he said, that neurons maintain a pool of mRNAs in readiness, and mRNA interference is a way to quickly knock down that pool to prevent the extra mRNA from being translated into proteins that might get the organism in trouble.

["Facts do not kill theories - only a more advanced theory can take place of an obsolote one" - said Einstein. Crick's rather ridiculous "Central Dogma" (named, since as he confessed, did not know what the word "Dogma" meant :-) has died of a million wounds of facts. Indeed, John Mattick has long labeled the Junk/Dogma interlocking fatal errors "the biggest mistake in the history of molecular biology". The question remains, therefore, "what do we have, as mathematically well-formulated theories that can (indeed, must) take place of the obsolete "old school" of DNA>RNA>PROTEIN (with information "never" recursing :-) Since the science paper apparently is yet to come, perhaps the authors will look into existing literature. As detailed in The Principle of Recursive Genome Function (2008) peer-reviewed paper and its popularization by 2008 Google Tech Talk YouTube , by reversing both mistaken axioms those companies that are set to deploy software-enabling algorithmic approaches to interpretation of genome function (most importantly, hologenome-regulation), will arrive at the conclusion that recursive algorithms, most particularly Pellionisz' fractal iterative recursion (FractoGene) are a leading candidate today. The "best methods" were revealed in the above publications. More recent "best methods" are indicated by interpretation of the RNA-system as a dual functor, that both "makes" proteins (by DNA of exons, through cRNA and Proteins), as well as "measures" already built proteins (by ncDNA transcription factors emanating ncRNA). Mathematically, this dual representation is the key to understanding, thus utilizing, hologenome regulation. - Dr. Pellionisz]

S. Korea announces $540 million post-genome project

2014/02/19 12:00

SEJONG, Feb. 19 (Yonhap) -- The South Korean government announced Wednesday the official launch of a post-genome project that seeks to develop and commercialize new genomic technologies.

The project consists of five major goals that include the creation of a standardized human genome map. It also aims for developing indigenous technologies for analysing human genes and for genome-based diagnosis and disease treatment.

The health and welfare ministry, the Rural Development Agency and four other government offices will spend some 578 billion won (US$542 million) over the next eight years, starting with 45.5 billion won in 2014 alone.

The latest endeavor follows the human genome project, an international research project concluded in 2003 to identify the sequence of chemical base pairs that make up human DNA and total genes of the human genome.

"The genomic industry has been showing the fastest growth in the 21st century, but the country's investment and technology in that area are far behind those in other industries," the Ministry of Science, ICT and Future Planning said.

"Now is time when the country urgently needs an active strategy to catch up with the rest of the world."

Genomic technologies have dramatically improved over the past 20 years, partly on the development of information technology, the ministry noted.

In 1990, decoding and analyzing a human genome required up to 15 years and US$3 billion. In 2013, the same task took only one day and $1,000, according to the ministry.

Still, the level of South Korea's genomic technologies remain at 57.7 percent of that of the United States.

The launch of the post-genome project follows a three-year feasibility study from scientific and economic perspective, the ministry said.

[South Korea may have 57.7 percent of the level of genomic technologies of the United States. However, the USA not only has a "zero dollar post-genome project", but never had (and is unlikely to have anytime soon) a "National Genome Program", for instance compared to NASA for Aeronautics and Space, or National Genome Programs of even rather tiny countries, for instance Estonia. As a Senior National Research Council Associate of the National Academy to NASA (Ames Research Center) with the (first) "launching of the Decade of Brain" I put together back in 1990 a study program how the underused and overspending government facilities could have played a lead-role at that time in the Neurosciences, and one could easily outline in the present global competition how the US government could measure up, e.g. not to slide to become second after China. In 2006, twenty-five of the leading scientists of the International Hologenomics Society worldwide (yes, including one from South Korea...) submitted a manuscript to Science to launch a "Post-Genetics Program" (unpublished). In 2014 genome industry is globalized, with players like Samsung, Sony/Illumina, BGI/Complete Genomics, Google/Apple (Calico), GE Health, Siemens, etc., etc., with different government-subsidy in each global player. Personally, I believe that Intellectual Property will play an increasingly crucial role; perhaps even small part with patents, but an ever-growing part with "know-how" and "trade secrets" - Dr. Pellionisz]

Hacking Your DNA


By David Ewing Duncan / March 12, 2014 12:58 PM EDT

Keeping track of what we reveal about ourselves each day—through email and text messages, Amazon purchases and Facebook "likes"—is hard enough.

Imagine a future when Big Data has access not only to your shopping habits, but also to your DNA and other deeply personal data collected about our bodies and behavior—and about the inner workings of our proteins and cells. What will the government and others do with that data? And will we be unaware of how it's being used—or abused—until a future Edward Snowden emerges to tell us?

Consider this scenario: A few years from now the National Security Agency hires a young analyst trained in cyber-genetics. She is assigned to comb through millions of DNA profiles in search of markers that might identify terrorists and spies and other persons of interest. It's simple enough, since almost every American and billions of other people have deposited their complete genomes—every A, C, T and G in their cells—into one of the huge new digital health networks, the new Googles and Verizons of medical data.

Sequencing a person's entire DNA profile will be as cheap as getting a car wash. High-end automobiles and hotels are likely to have installed photonic (light) sensors—devices that quickly read small segments of DNA in a customer's skin cells to confirm their identity—to unlock doors. Banks may offer DNA-secure accounts that can only be accessed by a person with the correct genetic code.

People in this future world will be accustomed to genetics guiding treatments and saving lives, even as they remain uneasy about who exactly has access—Employers? Insurers? The government? Their spouse or lover?

With her top-secret clearance, the NSA's new analyst discovers that the agency has accessed the genetic records of not only suspected terrorists, but also heads of state and leaders in industry, academia, the arts and the news media. Troubled by what she has learned, the analyst announces that she's taking a vacation, and flies to a neutral country carrying top-secret cyber-genetic documents stored on an encrypted nanochip. Like Edward Snowden, she gives her data to a reporter, with the hope of rectifying the injustices she has witnessed.

For better or worse, we're not there yet. In 2014, neither the government nor the public sector are anywhere near having a World Wide Web for genetic and other personal molecular data, or a global wireless network that can access anyone's genetic data from anywhere. If this were the Internet, the technology would be in about 1985—at the very beginning.

Physicians, however, are already using genomics to predict and diagnose diseases such as breast cancer and macular degeneration. Thousands of parents use prenatal genetic tests to check if their embryo or fetus carries genes for devastating diseases such as Tay-Sachs or Fragile X syndrome. Researchers have discovered genetic markers that can identify mutations in cancerous tumors that allow doctors to target specific chemotherapy drugs to match a patient's mutations in their own DNA—leading, in some cases, to astonishingly high rates of remission.

In the past two decades, the drug industry and government agencies like the National Institutes of Health have plowed hundreds of billions of dollars into turning genetics from a research project into something real. AT&T

, Verizon, IBM and other IT giants are developing digital health networks and products, while thousands of start-ups are in a mini-frenzy to create new digital health networks and apps.

Some companies, including Google-backed 23andme, have begun to provide customers with access to their own genetic data. (23andme actually stopped providing customers with genetic health data after being warned by the FDA that they need approval for some of these tests—the company says that they are working to fix this). Labs and companies are also in the very early stages of developing devices that read short DNA sequences using light waves, or a simple pinprick of blood.

In January, San Diego-based Illumina, a gene-sequencing company, announced that it can now sequence an entire genome for only $1,000. This may sound pricey, but just a decade ago a single human genome cost hundreds of millions of dollars to sequence. The price is likely to get even less expensive in future years.

This year, the number of people having their genomes sequenced could top 50,000, and that number should increase exponentially over the next few years as governments and health-care systems announce projects to sequence hundreds of thousands of people. Last year the U.K. announced plans to sequence 100,000 citizens by 2017. In the U.S., Kaiser Permanente has teamed up with the University of California at San Francisco to sequence 100,000 patients.

Eventually the mountains of data generated by our DNA and digital health records will be linked to Facebook and Twitter pages (or the future equivalent), and to those pink suede shoes you just bought and shared on the latest incarnation of Instagram. We may not like it, but the reality is that we give up this type of information to these companies every day. And if people want to keep getting the services they provide, they're going to keep trading data for it.

The result in a few years will be staggeringly complex statistical models designed to predict your behavior and to identify personality types, including those prone to violence or terrorism. Congress has passed a law barring health insurers and employers from using DNA to discriminate. Beyond this, however, we have few protections.

Genetic predictions will not be perfect or deterministic. It turns out that DNA is only part of the equation that makes you who you are or will be. Using genetic profiling for identifying terrorists or other personality types will also be imprecise and fraught with errors. Yet the more data amassed about individuals over time, the more accurate the modeling that creates the predictions.

For instance, scientists in a 2008 study associated a variant of the MAOA gene—the so-called "warrior gene"—to a predilection for violent behavior in some people. The statistical strength of this correlation is weak, and even if you have that genetic marker, you may in fact be a full-on pacifist. But let's say that one afternoon you as a carrier of this gene variant "liked" an essay by a former Palestinian commando-turned-diplomat. An hour later you got curious about Al-Qaeda and did a quick Google search. What if some search algorithm at the NSA then connected your social media data to your DNA? The next thing you know, the Transportation Security Administration is stopping you from boarding your flight home for the holidays.

This is just one hypothetical example. As we rush into an era of bigger and better data being crunched by legions of government and public sector employees, we may have to get used to our health information being hacked and interpreted incorrectly or in ways that might work against us. Of course, it would be better to have an open debate and transparent policies about this type of data now.

Failing that, we may wake up one morning to read that the NSA once again has been spying on us—only this time, it won't be about who we called or texted, but the secrets buried deep inside our cells that tell us a great deal about who we are and who we might be in the future.

COMMENTS: Pellionisz • a minute ago

David is a well known expert - and his sense of urgency imho is correct. I am also afraid, however, that his warning will be similarly disregarded by many as my 2008 YouTube "Is IT Ready for the Dreaded DNA Data Deluge?". Billions of dollars of investments into mere sequencing lost tremendous valuation, without matching analytics. Now, again, it is very clear what to do. Mere data, pervasive as they will be, will be rather useless without those who know what to do with it. When the emerging nuclear industry yielded immense power, the "knee-jerk reaction" of the World was a mad rush to buy up the experts, even at hyper-escalating prices. A global competition is already afoot. Those powers that don't wake up to genomics, will slide, others will rise high, to the losers' expense. Juan Enriquez said it all in his 2001 best-seller "As the future catches you". We have been warned... - comment by Dr. Pellionisz

Really? One does not understand the genome by having sequenced it all? - Now we learn from JAMA

["War and Peace" in Russian has a thousand times fewer letters than the human genome - try to understand either by "reading it" from cover-to-cover!]

Clinical Application of Whole-Genome Sequencing - Proceed With Care

William Gregory Feero, M.D., Ph.D. [JAMA]

Clinical Interpretation and Implications of Whole-Genome Sequencing

Frederick E. Dewey, MD1,2,3,4; Megan E. Grove, MS1,2,3,4; Cuiping Pan, PhD4,5; Benjamin A. Goldstein, PhD6; Jonathan A. Bernstein, MD, PhD7; Hassan Chaib, PhD4,5; Jason D. Merker, MD, PhD8; Rachel L. Goldfeder, BS9; Gregory M. Enns, MB, ChB7; Sean P. David, MD, DPhil6; Neda Pakdaman, MD6; Kelly E. Ormond, MS5,10; Colleen Caleshu, MS1,2,3,7; Kerry Kingham, MS11; Teri E. Klein, PhD5; Michelle Whirl-Carrillo, PhD5; Kenneth Sakamoto, MD3,6; Matthew T. Wheeler, MD, PhD1,2,3,4; Atul J. Butte, MD, PhD7,12; James M. Ford, MD, PhD11; Linda Boxer, MD6; John P. A. Ioannidis, MD, PhD6,12,14,15; Alan C. Yeung, MD2,3; Russ B. Altman, MD, PhD5,6,16; Themistocles L. Assimes, MD, PhD2,3; Michael Snyder, PhD2,4,5; Euan A. Ashley, MRCP, DPhil1,2,3,4,5; Thomas Quertermous, MD1,2,3,4

[-] Author Affiliations

1Stanford Center for Inherited Cardiovascular Disease, Stanford, California

2Stanford Cardiovascular Institute, Stanford, California

3Division of Cardiovascular Medicine, Stanford University, Stanford, California

4Stanford Center for Genomics and Personalized Medicine, Stanford, California

5Department of Genetics, Stanford University, Stanford, California

6Department of Medicine, Stanford University, Stanford, California

7Department of Pediatrics, Stanford University, Stanford, California

8Department of Pathology, Stanford University, Stanford, California

9Biomedical Informatics Training Program, Stanford University, Stanford, California

10Stanford Center for Biomedical Ethics, Stanford, California

11Division of Medical Oncology, Stanford University, Stanford, California

12Division of Systems Medicine, Stanford University, Stanford, California

14Stanford Prevention Research Center, Stanford, California

15Department of Health Research and Policy, Stanford University, Stanford, California

16Department of Bioengineering, Stanford University, Stanford, California

JAMA. 2014;311(10):1035-1045. doi:10.1001/jama.2014.1717.

Importance Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication.

Objectives To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings.

Design, Setting, and Participants An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings.

Main Outcomes and Measures Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up.

Results Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001).

Conclusions and Relevance In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

[Predictably, the JAMA study and editorial created a "media-frenzy" all over the net. The one below is just one of the those too many to list - presently the number of related popular articles is 145. One wonders just how many it takes, since in my Google Tech Talk YouTube six years ago I warned about the "Dreaded DNA Data Deluge". In the talk, I also disclosed for the general public my peer-reviewed science paper The Principle of Recursive Genome Function; offering an alternative to junk/dogma. The paper has been downloaded thousands of times, with zero objection. Still, only the bravest dared to cite ... Pellionisz]


By Jason Koebler


Despite the promise of the $1,000 genome sequence, personalized medicine is likely to remain a luxury product—and not a very accurate one at that. For the foreseeable future, researchers will continue to struggle to overcome significant hurdles that make predicting someone’s propensity for disease expensive, time-consuming, and potentially unreliable.

A new study on the present-day feasibility of whole-genome sequencing for clinical use by researchers at Stanford University found that it will cost at least $17,000 per person to sequence a genome and interpret the results, and it’ll take roughly 100 man-hours to perform any sort of meaningful analysis.

“The gist of it is, we found that the results are generally not clinically acceptable,” said Frederick Dewey, lead author of the analysis, published in the Journal of the American Medical Association. “It’s a relatively sobering thought, and there are tough hurdles to get over before this is common.”

Dewey and his team completely sequenced the genomes of 12 people and analyzed them to predict their propensity for genetic diseases and other health concerns. The study was designed to test out some of the leading genome sequencing techniques and analysis methods. The expensive part, Dewey said, isn’t necessarily the sequencing of the genome (a cost that is constantly coming down) but the analysis after the fact. 

“The main challenge at this point, assuming you have technically valid data, is from a manpower perspective,” he said. “What we have learned is that a sequence doesn’t equal interpretation—there’s a significant manual interpretation job afterward.” 

But that’s not all. The reason the results were not deemed clinically acceptable in most cases is because, even with the most advanced sequencing techniques, the researchers found that, on average, between 10 and 19 percent of inherited disease genes “were not consistently covered at a read depth that was sufficient for a comprehensive survey of genetic variants.” In general, whole genome sequencing wasn’t great at picking up nucleotide insertion and deletion mutations—with one commonly used sequencing method, just one third were picked up. That’s important because those mutations are commonly medically relevant.

The study wasn’t all bad news, however. Of the dozen subjects whose genomes were sequenced and analyzed, the team found a woman with no family history of breast cancer who had a mutation in the BRCA1 gene that makes her much more likely to develop the disease. 

Dewey said that, although the results of this initial study suggest that personalized genomic medicine isn’t quite ready for primetime,  all of the problems the team found are ones that researchers are actively working on. 

“It’s remarkable how far we’ve come, and I would expect the pace of discovery and innovation will continue,” he said. “There’s a long way to go, but what we’ve done so far is far beyond anything we would have anticipated years ago.”


Andras Pellionisz · Member of Board of Advisers to DRCcomputer, Sunnyvale, California

Dr. Karp of the Simons’ Institute of Computer Theory of Berkely uses an interesting example how inexpensive it became to obtain a full human DNA sequence. Though the first cost $3 Bn, price plummeted to a couple of hundred dollars; “if the price of cars would have dropped similarly, the price of a Ferrari would be 40 cents”. We all understand cars – they get us somewhere. Where do 6.2 Bn A,C,T,G letters get us “if we only have letter squences without the mathematical understanding of their meaning"? Try understanding “War and Peace” in Russian, without knowing the language. The human DNA is about a thousand times longer and scientists are not sure if it has to be read linearly, parallel or in a “chaotic” manner. Increasing number of mathematicians/Institutes recognize that genome function is is essential in medicine. The naïve era when “genome theory” only consisted of “junk and dogma” is dead. With sufficient resources mathematical genomic theory will yield sophisticated recursive algorithms that will take us on a new path in medicine.

No longer junk: Role of long noncoding RNAs in autism risk

SFARI Simons Foundation Autism Research Initiative

Nikolaos Mellios, Mriganka Sur

4 March 2014

RNA acts as the intermediary between genes and proteins, but the function of pieces of RNA that do not code for protein has, historically, been less clear. Researchers have ignored these noncoding RNAs until recently for not complying with the central dogma of biology — that a straight line runs from gene to RNA (transcription) to protein (translation). However, noncoding RNAs are emerging as important regulators of diverse cellular processes with implications for numerous human disorders.

Extensive research has already examined the function of microRNAs, a category of small evolutionarily conserved noncoding RNAs about 22 to 24 nucleotides in length that target protein-coding genes in a sequence-specific manner. A plethora of microRNAs are important for brain function and neuropsychiatric diseases, including autism1.

In the past decade, long noncoding RNAs (lncRNAs), which extend longer than 200 nucleotides, have emerged as additional important players in the control of gene expression. They fine-tune the expression of numerous genes and direct the activity of complex regulatory pathways, often in a cell- and developmental-stage-specific manner.

They are found in many places in the genome: within genes, near gene regulatory regions or by themselves (intergenic noncoding RNAs). lncRNAs may overlap with the genetic code for a protein or be expressed in the opposite, or antisense, direction.

In addition to the diversity in their biogenesis, lncRNAs exhibit an impressive versatility of molecular functions. These range from passive influence on the transcription of nearby genes to limiting expression to a paternal or maternal chromosome, a process called imprinting, and inactivating one copy of the X chromosome.

They also interact with chromatin-modifying complexes, which regulate gene expression by changing the packaging of DNA, and with transcription factors that directly regulate gene expression. They may influence RNA splicing, stability and localization and play a role in the translation of RNA to protein and in protein activation. Finally, they may ‘sponge’ up certain microRNAs, thus blocking their function2, 3, 4, 5.

Molecular multitaskers:

The ability of lncRNAs to engage in such molecular multitasking may allow them to link multiple risk factors for genetic disorders into functional networks. This makes them attractive candidates for autism spectrum disorders, which are characterized either by interactions of multiple genes or by disruptions in a single gene that influences numerous molecular pathways.

Whether whole-genome DNA sequencing data will reveal strong genetic links with lncRNAs, as it has for microRNAs, is not yet clear. One thing, though, remains certain: We can no longer overlook such a substantial and active chunk of the transcriptome and characterize it as ‘junk’ or ‘transcriptional noise’ if we hope to fully understand complex disorders such as autism.

In the past few years, studies have found alterations in lncRNAs in brains from people with autism, suggesting that they contribute to autism risk. For example, MSNP1AS, a lncRNA transcribed from a region of chromosome 5 that carries an autism-associated variant, is elevated in the cortex of people with autism who also carry the disease-related variant6. MSNP1AS may regulate moesin, a gene important for the structure of neurons’ signal-receiving branches, or dendrites, and immune system activation.

Last year, a carefully conducted study identified numerous lncRNAs that are robustly dysregulated in autism postmortem brain samples7. Impressively, some disease-altered lncRNAs are found near important autism-linked genes such as BDNF and SHANK2.

Another lncRNA with potential implications for autism is LOC389023, which regulates DPP10, a gene linked to autism and other neurodevelopmental disorders. DPP10 controls the structure and function of neuronal junctions, or synapses, via its effects on potassium ion channels3.

Last year, researchers used a similar approach to study the expression of lncRNAs in a mouse model of Rett syndrome8. One lncRNA (AK081227) that is expressed at abnormal levels in these mice controls the expression of its host protein-coding gene, the gamma-aminobutyric acid receptor subunit Rho 2 (GABRR2), which has also been linked to autism.

Additional reports have linked other lncRNAs to autism, such those that travel antisense to the FMR19, 10 and UBE3A11, 12 genes. Mutations in these genes underlie fragile X syndrome and Angelman syndrome, respectively. Other studies have also uncovered a subset of lncRNAs expressed from the autism-linked PTCHD1 gene13 and the 7q31 chromosomal region14.

In addition, the lncRNA ZNF127AS has altered expression in the brains of people with Prader-Willi syndrome15. On a similar note, a cluster of small nucleolar RNAs — which despite their name are a category of lncRNAs — are encoded by the paternally inherited microdeletion at 15q11.2 that is also linked to Prader-Willi syndrome16.

Brain builders:

Previous work has identified a subset of lncRNAs that are important for regulating the birth of new neurons, or neurogenesis, and the process by which synapses adapt to experience, called synaptic plasticity.

Of particular importance is the finding that the intergenic noncoding RNA MALAT1, one of the most highly expressed lncRNAs in the brain, can regulate the formation of new synapses, or synaptogenesis. It does this by associating inside the nucleus with multiple RNA splicing factors and influencing the expression of autism-linked genes, such as NLGN117.

Intriguingly, there are several other links between MALAT1 and autism-associated factors. For example, beta-catenin — an important component of the WNT signaling pathway that has been linked to multiple neuropsychiatric disorders — activates MALAT1 transcription18. CREB, another transcription factor known for its role in activity-dependent gene expression, also binds to MALAT1. Notably, CREB may control MALAT1 transcription following exposure to the peptide hormone oxytocin, which has also been linked to autism19.

MALAT1 and another lncRNA, BDNFOS, which has the antisense, or opposite, code to that of the autism-linked BDNF gene, are expressed in conjunction with neuronal activity20. On the other hand, GOMAFU, a lncRNA whose levels are dampened in postmortem brains from people with schizophrenia, is significantly suppressed following the activation of mouse cortical neurons21.

Other lncRNAs run antisense to important synaptic plasticity-related genes, such as NRGN, CAMK2N1 and CAMKK122, 23. lncRNAs are also associated with genes linked to changes in the synapse that occur after exposure to cocaine24. Interestingly, a novel subset of lncRNAs are expressed from the regulatory elements of genes, such as c-FOS and ARC, that regulate gene transcription in response to neuronal activity25.

Adding to their important role in brain plasticity, lncRNAs are highly expressed during prenatal neurogenesis and are important for maintaining and differentiating the precursors to neurons: neural stem cells and neuronal progenitors26, 27. Of particular interest is the lncRNA EVF2, which runs antisense to the regulator gene DLX5,6 and plays a crucial role in the birth of neurons that dampen brain activity28. This adds another layer to the role of lncRNAs in cell-type-specific neuronal functions.

Despite these many threads, much more work is needed to determine the exact mechanisms of action and the physiological significance of lncRNAs for autism and other neurodevelopmental disorders.

Mriganka Sur is professor of neuroscience at the Massachusetts Institute of Technology, in Cambridge. Nikolaos Mellios is a postdoctoral fellow in his laboratory.

News and Opinion articles on are editorially independent of the Simons Foundation.


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25. Kim T.K. et al. Nature 465, 182-187 (2010) PubMed
26. Ng S.Y. et al. EMBO J. 31, 522-533 (2012) PubMed
27. Sauvageau M. et al. Elife 2, e01749 (2013) PubMed
28. Bond A.M. et al. Nat. Neurosci. 12, 1020-1027 (2009) PubMed

[A foot-note is, perhaps naive, that the barely nascent mathematical (software enabling) foundation of genomics may become a show-stopper to the zillion-dollar present investments into Globalized Industrial Genomics, maybe sooner than we think. (Can you picture nuclear industry without quantum mechanics - could have been orders of magnitude more expensive and very dangerous). In this spirit, see some further studies here, especially for the mathematical interpretation of the RNA system, and the already demonstrated implications of fractal defects in cancers, autism, schizophrenia and auto-immune disorders. A regular collective PubMed publication printed in 2014 is here - Dr. Pellionisz]

Craig Venter's Latest Startup Gets $70 Million to Sequence Loads of Genomes

by Bruce V. Bigelow, The Motley Fool Mar 4th 2014

J. Craig Venter, the human genome pioneer, today unveiled a new San Diego-based venture with an ambitious goal of providing whole genome sequencing and cell-therapy-based diagnostic services for patients.

Venter said he co-founded the company, Human Longevity, or HLI, with Robert Hariri, who oversaw Celgene Cellular Therapeutics and Peter Diamandis of the X Prize Foundation. The company already has raised $70 million in Series A venture financing that includes a Malaysian investment fund that also is the lead investor of another Venter venture, Synthetic Genomics, San Diego-based Illumina, and other individual investors.

Venter plans to serve as the chairman and CEO of both HLI and San Diego-based Synthetic Genomics, which he co-founded in 2005 to engineer genes within organisms so they can produce fuel, chemicals, medicines, and nutritional products.

The HLI effort, which Venter and others repeatedly described as "unprecedented" in a conference call this morning, will initially focus on basic research and development, sequencing every cancer patient who comes into the UC San Diego Moores Cancer Center, as well as other patients with diabetes, obesity, heart and liver diseases, and dementia.

In a statement this morning, HLI says it has established collaborative research and development partnerships with UC San Diego, Metabolon, and the J. Craig Venter Institute. North Carolina-based Metabolon is expected to provide information about patients' metabolytes, key chemicals in their blood.

HLI also has formed a Biome Healthcare division, led by Karen Nelson, to generate gene sequencing data of the microbiome for many patients. The microbiome consists of all the microbes that live in the human gut (and elsewhere in and on the human body). New research by Nelson and others suggest that such bacteria play a key role in human health and disease.

The early goal at HLI is to sequence 40,000 human genomes a year, and amass the world's largest database of human genome sequences. HLI plans to combine its human genome data with microbiome data and phenotype databases to develop new treatments, including stem cell therapies, for aging-related diseases. Eventually, HLI intends to sequence 100,000 human genomes a year.

"We will be using that [data] to make numerous new discoveries in preventative medicine," Venter said. "We think this will have a huge impact on changing the cost of medicine and broad human health."

HLI plans to make money by providing access to its database to pharmaceutical, biotechnology and academic organizations, gene sequencing, and by developing new medical diagnostics and therapeutics. As HLI's genome-sequencing capacity increases, the company plans to sequence people of all ages -- from infants to super centenarians -- including those who are healthy as well as those with disease.

Genomic data would be shared among researchers participating in the effort, although Venter said details about protecting patient privacy are still being worked out.

DFJ partner Steve Jurvetson, who said he's an investor in HLI, asked Venter during the call to compare the effort to BGI China, one of the world's premier gene sequencing centers. BGI says on its U.S. website that it has relationships with 17 out of the top 20 global pharmaceutical companies as part of its suite of commercial science, health, agricultural, and informatics services.

Venter answered that HLI will be working with more advanced gene sequencing equipment (Illumina's HiSeq X Ten Sequencing Systems) and will have higher throughput capabilities. But he added that there is plenty of room for gene sequencing services. In fact, Venter envisions a future where genome sequencing is done routinely for every patient admitted to a hospital.

"We cannot have enough players in the human genome sequencing field," Venter said. "We're just trying to elevate it to a new level."

With $70 million in initial funding, "We think that will carry us through the first 18 months as we build these operations," Venter said. HLI already is using laboratories in San Diego for high-throughput microbiome and human genome sequencing, and has plans to build a new facility near the UC San Diego campus. HLI plans to hire about 100 scientists and others over the next year, Venter said.

"This is a revolution in biomedical research," said David A. Brenner, vice chancellor for health sciences and dean of the UC San Diego School of Medicine. "This is the first time ever as physician-scientists that we have had the opportunity to handle very large datasets and to be able to compare the genetics of a patient with the microbiome, as Dr. Nelson said, and with the metabolytes in the blood to try to gain new insights into our understanding of disease pathogenesis, into diagnoses, and hopefully, into new therapies and cures."

[Knowing the players over a decade, Steve Jurvetson's question may have implied that "sequencing is a necessary but not sufficient condition to software analysis". BGI has had close to 10,000 software developers (average age 27, monthly salary $411). Brightest investors of Silicon Valley may ask how to outsmart such a competition by hiring 100 - Dr. Pellionisz]

GE Ventures support RainDance’s vision to make liquid biopsy a commercial reality

RainDance Technologies Closes Series E Financing with GE Ventures

March 2, 2014 2:02 AM

Business Wire

BILLERICA, Mass.–(BUSINESS WIRE)–March 3, 2014–

RainDance Technologies, Inc., an innovative genomics tools company making molecular testing of complex diseases more standardized and readily available, today announced that it has closed a $16.5 million Series E financing round extension. New investors include GE Ventures and Northgate Capital; all existing financial investors also participated in this round of financing.

The additional investment accelerates RainDance’s commercial expansion and assay development initiatives for the company’s products:

RainDrop™ digital PCR system, which provides unparalleled sensitivity for research into early detection and monitoring of cancers, viruses, pathogens and immune markers;

ThunderStorm™ targeted sequencing system, which advances research into and understanding of hereditary risk, inherited diseases and hematologic malignancies; and,

ThunderBolts™ Cancer Panel, which delivers an actionable, fast, simple and low cost sequencing profile of somatic tumor mutations in molecular biopsies or biobanked samples.

GE Ventures now becomes the second strategic investor in RainDance, following an investment from Myriad Genetics in 2013, and shares its mission of addressing healthcare issues by accelerating development and commercialization of products that improve patient care and save lives. The liquid biopsy method using readily accessible fluids currently in development by RainDance is minimally-invasive, and a low cost healthcare solution for patients.

“We believe technology will play a major role in transforming patient care and by partnering with leading innovators we can help scale the best new ideas in major industries like healthcare,” said Sue Siegel, CEO of GE Ventures and healthymagination. “We have followed RainDance’s progress for many years and are impressed with how the company’s cutting edge technologies are advancing the market and helping to bring in a new era of more accurate, non-invasive and cost-efficient testing for complex genetic disease research.”

Roopom Banerjee, RainDance President and CEO, noted, “We welcome GE Ventures and Northgate as new investors. GE brings an unparalleled global network of businesses and partners, and is a logical outgrowth of the work we have under way with industry and research leaders committed to making the world healthier. Our success bringing in strategic investors such as GE Ventures and Myriad Genetics demonstrates we are a trusted platform partner to large customers in advancing the understanding, detection and monitoring of cancer and other important diseases.”

RainDance has raised more than $100 million from investors including Mohr Davidow Ventures, Quaker BioVentures, Alloy Ventures, Acadia Woods Partners, Sectoral Asset Management, Northgate Capital and Capital Royalty Partners, to support the development and commercial expansion of its leading technologies for Digital PCR and Next-Generation Targeted Sequencing (NGS). The RainDrop Digital PCR System, which has 50x to 1000x the sensitivity of traditional quantitative PCR, enables researchers to analyze low-frequency alleles with true single molecule detection capability. Separately, RainDance’s ThunderStorm System enables commercial laboratory customers to develop their own proprietary next-generation sequencing panels for disease research. RainDance products generally feature an ‘open system’ that leverages decades and billions of dollars already invested in NGS and PCR chemistries and innovations.

Most recently RainDance announced that it has developed the ThunderBolts™ Cancer Panel, a comprehensive NGS panel, for profiling actionable cancer mutations. ThunderBolts enables researchers to rapidly and cost-effectively analyze precious biopsy specimens such as those contained in bio-banks worldwide. The ThunderBolts Cancer Panel is currently being made available to select First Access Program (FAP) participants. Researchers from FAP sites will present data at a workshop at the American Association for Cancer Research (AACR) Annual Meeting in April 2014 in San Diego, California. For more information, on the ThunderBolts Cancer Panel, please visit

Cowen Group 34th Annual Health Care Conference

Roopom Banerjee will be presenting more information on RainDance during the Cowen Group’s 34th Annual Health Care Conference on March 3, 2014 at 10:00am at the Boston Marriott Copley Place in Boston.

About GE Ventures

GE Ventures is committed to identifying, scaling and accelerating ideas that will make the world work better. Focused on the areas of software, advanced manufacturing, energy and healthcare, GE Ventures helps entrepreneurs and start-ups succeed by providing access to GE’s technical expertise, capital and opportunities for commercialization through GE’s global network of business, customers and partners. GE Ventures offers an unparalleled level of resources through its Global Research Center, including: 35,000 engineers; 5,000 research scientists; 8,000 software professionals; as well as 40,000 sales, marketing and development resources in over 100 countries. For more information, please visit

About RainDance Technologies

RainDance Technologies is making complex genetics simple. The company’s ultra-sensitive genomic tools are leading to new non-invasive liquid biopsy applications for more accurate, reliable, cost-effective and early detection of cancer, inherited and infectious diseases. Major research institutions and more than 70 leading translational, genetic and commercial laboratories around the world rely on RainDance systems’ superior performance. Based in Billerica, Massachusetts, the company supports customers using RainDrop Digital PCR and ThunderStorm Targeted DNA Sequencing Systems through its international sales and service operations as well as a global network of distributors and commercial service providers.

Google Launches Genomics Effort, Joins Global Alliance

GEN News HighlightsMore »

Mar 3, 2014

Alex Philippidis

[Looks familiar? Progress is often characterized by a "7-year cycle". Close to this timeframe (with 7 years ahead, perhaps reserving some bragging rights) Google Tech Talk YouTube predicted in 2008 at time 11:19 that the "parallel computing architecture" is not much of a challenge to Google - essentially a matter of time and/or money (buy/build). However, I also pointed out that while "Information Technology" is pretty much a given (with ample leveraging of Google/Amazon/Oracle/Sony/Samsung/Siemens/GE Health and zillions to join the fray, even Cisco not excluded - the global competition no longer gracious to permit further wasted decades) - "IT2" that I called "Information THEORY" of hologenomics had to built anew (The Principle of Recursive Genome Function peer-reviewed science paper was announced at the talk, cited thus far only by the top dozens would dare to adopt). Even two months ago (Dec. 30, 2013) there was still a retirded professor closer to the North Pole who publicly claimed "90 percent of the human genome was (still) JUNK"! As we see in the footer, having ventured into several aspects of genomics, Larry Page apparently decided the "must" in genomics; "focus is on the science". Is Google going to do "in house" breakthrough hologenome science? Since it takes less than 5 minutes to realize the (now) obvious, they might. If others innocently bring it "in house", even better... Would Google wait till NIH "cooperates with industry" at $150k levels? This definitely looks like an antiquated and now expired option! - Would a dominance be established by truly major player(s) on an exclusive or non-exclusive manner by securing IP? Dr. Pellionisz, Holgentech, Inc.]

Google has unveiled Google Genomics, a proposal for a web-based application programming interface (API) designed to import, process, store, and search genomic data at scale, while being simple to use.

At the same time, Google said it joined the Global Alliance for Genomics and Health, an international effort aimed at developing common approaches for responsible, secure, and effective sharing of genomic and clinical information in the cloud with the research and healthcare communities.

The internet search and services giant is one of 146 top technology, healthcare, research, and disease advocacy organizations worldwide in the global alliance, which vowed that its harmonized standards will meet the highest standards of ethics and privacy.

Established last year, the alliance has drawn numerous research institutions, five of which were named interim host institutions: the Broad Institute and Brigham and Women's Hospital, the Ontario Institute for Cancer Research, and the Wellcome Trust Sanger Institute / European Bioinformatics Institute.

The alliance has also drawn members that include drug developers (Amgen, Biogen Idec, and Merck & Co.), sequencing giants (BGI-Shenzhen and Illumina), and cloud-based genomic analysis firm DNAnexus – which in January said it closed on a $15 million Series C financing round co-led by Google Ventures.

Google Ventures has also invested in direct-to-consumer (DTC) genetic testing company 23andMe. And in September, Google extended its healthcare presence by launching Calico, a new company focused on developing technologies to fight aging and associated diseases. Calico is led by Arthur Levinson, the chairman of Roche’s Genentech subsidiary and former CEO before the company got bought, as well as chairman of Apple and former director of Google. Not all Google initiatives in healthcare have been successful. In 2011, the company shut down an electronic health records effort with the same goal as Calico, but which failed to catch on.

To launch Google Genomics, Google has previewed its implementation of the API built on its cloud infrastructure, including sample data from public datasets like the 1,000 Genomes Project, and made public a collection of in-progress open-source sample projects built around the common API.

In unveiling the API as a limited release for discussion by the research community, Google cautioned that not all of the interface’s functionality had been implemented yet, and that the company’s focus to date in launching Google Genomics had been the shape of the API more than its performance.

But Google also laid out what it sees as the benefits of its API to prospective users: It allows users to focus on science rather than tech details such as servers and file formats; store genomic data securely so that private data remains private, while public data is available to the community anywhere; and process as much data as they need, all at once. For example, the API would let users import data for entire cohorts in parallel, as well as search and slice data from many samples in a single query.

“With these first steps, it is our goal to support the global research community in bringing the vision of the Global Alliance for Genomics and Health to fruition,” Jonathan Bingham, product manager with Google, said in a post on the company’s research blog. “Imagine the impact if researchers everywhere had larger sample sizes to distinguish between people who become sick and those who remain healthy, between patients who respond to treatment and those whose condition worsens, between pathogens that cause outbreaks and those that are harmless. Imagine if they could test biological hypotheses in seconds instead of days, without owning a supercomputer.”

The blog post included a link allowing would-be users to request access to the API for their research, and requesting that they tell about themselves and their research interests: “We will let you know when we’re ready to work with more partners.”

“Together with the members of the Global Alliance for Genomics and Health, we believe we are at the beginning of a transformation in medicine and basic research, driven by advances in genome sequencing and huge-scale computing,” Bingham added.

[What to make of Google Life, 23andMe, Calico, Google Genome? Consult Dr. Pellionisz - Holgentech, Inc.]

Google Could Disrupt These 3 Medical Industries Within 10 Years

By Leo Sun
Motley Fool

February 1, 2014

[When will Larry Page "go fractal" (composed of self-similar repetitions)? - We all know that the Internet itself is fractal, see at 42:40 of Google Tech Talk YouTube, and that "fractal genome grows fractal organisms"; cancerous if the fractal has defects. Thus, the question is not if, but when. Larry Page need not be told that powerful algorithmic approaches yield the utmost utility - AJP]

Search giant Google (NASDAQ: GOOG) is a master market disruptor. Mobile devices, location-based services, online advertising, email, and news have all been disrupted by Google to some degree over the past 16 years.

One industry that hasn't been associated with Google, however, is the rapidly growing health care market.

Yet in my opinion, Google could take advantage of this convergence and disrupt three specific fields of health care over the next 10 years, disrupting the traditional business models of industry stalwarts like pharmaceutical giant Roche (NASDAQOTH: RHHBY) , medical device maker DexCom (NASDAQ: DXCM) , and EHR (electronic health records) provider Allscripts (NASDAQ: MDRX).

Google vs. the biopharmaceutical industry

Last September, Google created Calico (California Life Company), a new health care company focused on solving aging and related diseases. Calico's stated goals include extending the average human lifespan by 20 to 100 years and treating age-related diseases like Alzheimer's, cancer, and heart disease.

The quest to slow or reverse aging isn't a new one. In 2008, GlaxoSmithKline (NYSE: GSK) acquired Sirtris Pharmaceuticals for $720 million for its pipeline of sirtuins, a class of enzymes that are believed to be integral in slowing the aging process. So far, the technology has been a far cry from a "fountain of youth" -- a handful of studies testing sirtuin-based drugs on inflammatory diseases and type 2 diabetes have proved inconclusive.

However, Google has hired some of the brightest minds in the business to run Calico. Calico is led by Arthur Levinson, the former CEO of Genentech. Genentech, which was acquired by Roche in 2009 for $46.8 billion, today forms the core of Roche's cancer portfolio.

The blockbuster drugs that were developed while Levinson was Genentech's CEO -- Rituxan, Avastin, Tarceva, Herceptin, and many others -- not only improved the lives of cancer patients worldwide, but also define Roche as a company today. Together, those four aforementioned drugs generated over $20 billion in sales in fiscal 2013.

Hal Barron, Roche's former executive vice president, head of global product development, and chief medical officer, also joined Calico as its new president of research and development. David Botstein, the former head of Princeton University's Lewis-Sigler Institute of Integrative Genomics, is now Calico's chief science officer.

All of these hires indicate to me that Google is positioning Calico to become the next Genentech. While Calico's pipeline hasn't been revealed yet, in 10 years Calico could be manufacturing next-generation cancer drugs that could challenge Roche/Genentech's massive footprint in oncology.

Google vs. the medical device industry

Google has also been experimenting with smart medical devices. Its latest effort, the smart contact lens for diabetic patients, tries to read glucose levels from tears, which could render painful pinpricks obsolete. Google is also testing the lens' ability to synchronize wirelessly with a mobile device, similar to Johnson & Johnson's OneTouch Verio Sync Meter, which was approved in March 2013.

If Google's smart contacts are approved, companies that primarily make continuous glucose monitors, such as DexCom, could be in trouble.

DexCom is one of the fastest-growing names in the field -- last quarter, its product revenue surged 101% year over year to $42.5 million while its net loss narrowed from $0.25 to $0.08 per share.

More importantly, DexCom and Johnson & Johnson are partnered in the creation of a wearable artificial pancreas to compete against Medtronic's MiniMed 530G, a first-generation device that was approved last September.

Google's smart contacts could disrupt both devices, since they both use continuous glucose monitoring (CGM) technology integrated with insulin pumps. A smart contact lens would displace the need for a CGM device, since it could synchronize wirelessly to the insulin pump instead.

While Google's smart contacts are experimental, they represent the search giant's vision for medicine, which leapfrogs over the current generation medical devices. The secretive Google X Team, which developed Google Glass, driverless cars, Wi-Fi balloons, and the smart contacts, recently held a meeting with the FDA in regards to an unnamed medical device.

Whatever Google has in store won't immediately disrupt DexCom's or Medtronic's medical device businesses, but a new generation of tiny cloud-connected medical devices might alter the market landscape within a decade.

Google vs. the EHR industry

Last but not least, Google could unite the fragmented EHR market. EHRs are considered an essential part of modernizing hospitals, since digitally streamlining patient records can boost productivity and minimize errors.

Unfortunately, the current market is a fragmented mess. According to an annual presentation last May by SK&A, Allscripts is the overall market leader with a 10.6% share of the market, thanks to its dominance of small practices with four to 10 physicians. Meanwhile, privately-held Epic is the leader in large practices with 41 or more physicians, and holds an overall market share of 10.3%.

That fragmentation has made the EHR market a very tough one to unify. Google tried once, with Google Health in 2008, but the service was scrapped in 2011 due to the fragmented state of the market, administrative apathy, and a lack of users.

The good news is that EHR technology has considerably improved over the past two years thanks to Apple's iPad gaining prominence in hospitals. Just three iPads can replace a computer on wheels (COW) and save a hospital $6,000, according to CareCloud's Ahmed Mori.

In April 2012, Allscripts launched a native iPad EHR app (untethered to a desktop platform), named Allscripts Wand. Native iPad EHR apps offer more touch-friendly menus, use Siri for voice-to-text documentation, and take advantage of the iPad's onboard camera for easier patient documentation.

Google Glass, which is scheduled to launch later this year, is the key to disrupting this market. Regardless of the convenience of native iPad EHRs, iPads can never be a hands-free experience. Last October, Philips and Accenture teamed up to launch a proof of concept of Google Glass as a medical device. The proof of concept device was able to display vital patient data and synchronize wirelessly to Accenture's EHR service, offering a truly hands-free, voice-controlled EHR experience.

Therefore, regardless of the EHR provider, Google Glass -- which also has an onboard camera, voice recognition, and cloud connectivity -- could soon replace the iPad as the preferred method of accessing EHRs.

The Foolish takeaway

In conclusion, investors in tech and health care should keep a close eye on Google's growing footprint in these medical industries.

While Google's projects seem like "moon shots" (as the company likes to call them), they could grow into major pillars of growth for the company in a decade and disrupt unexpected fields like biotech, medical devices, and EHRs.

Sony’s new genome analysis company is not playing catch-up with Calico

By Graham Templeton on January 27, 2014

In a move that is becoming increasingly common for international technology giants, Sony will make a startling new push into an area of research that doesn’t seem to overlap at all with its current projects. Diversification is the corporate buzzword of the day, a frantic attempt to spread out a company’s weight as it tries to keep from falling through ever-thinning economic ice. The internet is threatening established media, display technology is advancing down all sorts of new paths, and the cloud is even bringing the necessity of physical processing hardware into question; even a company as diverse as Sony must look at its frankly incredible array of products and wonder whether it might still be just a few Kickstarter success stories away from total irrelevance.

That being the case, the company has decided to enter into a partnership with Japanese medical giant M3 and genetics pioneer Illumina to create a new company named P5. Though details are scarce right now, the new company will focus on creating a “genetic information platform,” which we can safely assume means a proprietary stab at making salable products out of the promise of personalized medicine. Almost certainly the first planned device is a cheap genetic sequencing and annotation tool meant for quick identification of genetic problems or warning signs.

The short-term target of the company is the research and testing industry, but sales direct to the public are an openly stated goal, as well. The biomedical industry is already one of the largest economic sectors there is, and that’s while working entirely through third parties (insurance companies and medical professionals). If technology could allow companies like Sony to safely cut out such inherent inefficiencies, the market could explode even further.

This differs from Google’s announcement of Calico in a few key ways. First, Sony has a robust history as a hardware company, while Google still primarily makes software. Second, Sony’s goals seem much less lofty than Google’s; all modern hospitals already house equipment with at least a few recognizable electronics logos, and Sony just wants a (bigger) piece of that action. That genetic analysis will undoubtedly have the effect of lengthening lifespans doesn’t mean the two projects have the same goal. Sony wants to fill a very specific niche, and has a direct plan to recoup expenses; Google seems to have a much more general understanding of the relationship between health and profit, and trusts that a more wide-based approach will work out in the end.

In late 2012, Sony announced a general plan to enter the health industry with the explicit aim of cornering an emerging market. They see medicine as a new frontier in technology that could work its way into the average home. Could they sell you a hardware-software health kit that tracks and advises on health the way a financial suite might do for your budget? Could they sell you a testing platform at a loss, then recoup that loss through monthly health monitoring fees? Will you have to pay for version upgrades capable of testing more accurately, or for a wider array of problems?

This sort of research need not confine itself to hypotheticals, however. The $664 million purchase of camera-maker Olympus was reportedly to gain control of its medical endoscope business, but the research necessary to improve those devices could also drive the development of Sony’s 4K TVs. There are multiple possible applications for virtually every sort of research, and there are few if any companies better positioned to take advantage of the full spectrum of applications for a new technology. With many of Sony’s traditional businesses struggling in recent years, last year saw the company take in a majority of its profit from the financial services branch – this is a company that knows full well the importance of embracing new and seemingly uncharacteristic ideas.

Genome analysis is one of the fastest-emerging fields in the world, recently passing the $1,000 milestone and continuing to advance with no sign of slowing. Quite literally, the $100 genome might not be far away — and any company not poised to exploit that market the instant it appears could easily find itself frozen out for good. Sony and Google have big plans to make sure that doesn’t happen. All that remains to be seen is who else will throw their hat into the ring.

Sony Corp. intends to make its medical sector a core part of its business through a foray into genome information analysis, according to sources.

August 29, 2013


Sony plans to establish a joint venture with Illumina Inc., the world’s largest gene analysis equipment maker, and its own group company M3 Inc. as early as October, the sources said. It would take on contracts to analyze blood samples provided by hospitals and other medical institutions.

The company also plans to accumulate analysis data separately from personal information of the patients, and sell it to pharmaceutical firms, research institutes and other establishments, the sources said.

Last October, Sony President Kazuo Hirai announced that his company will raise sales of its medical business from the current tens of billions of yen to 200 billion yen ($2.04 billion) by 2020.

Genome information analysis would give Sony’s medical sector expansion a burst of momentum. It is utilized in a rapidly expanding range of medical fields, such as predicting diseases a person is likely to develop.

Hollywood star Angelina Jolie made headlines in May by disclosing that she had undergone a double mastectomy to prevent likely carcinoma after genetic testing found she was at a high risk of contracting breast cancer.

Currently in Japan, genomic analyses are conducted mainly by the Riken national research institute in Wako, Saitama Prefecture, and other large research establishments.

A senior Riken official said an increasing number of companies will likely enter the genome analysis business.

“Genome analysis has become easier to conduct thanks to the introduction of more advanced equipment,” said Naoto Kondo, director of Riken’s Genome Network Analysis Support Facility.

M3, which has been supplying information on medical papers as well as other services for doctors, already has a number of established clients in Japan. Utilizing M3’s name recognition and solid customer base, Sony aims to receive as many orders as possible for its new business.

SAP Pushes Easy-to-Use Software at Hub to Compete With Facebook

Bloomberg News

By Aaron Ricadela and Cornelius Rahn February 12, 2014

SAP AG (SAP)’s founder Hasso Plattner said the largest business-software maker’s programs remain too cumbersome to impress a generation of users weaned on slick apps made by Google Inc. and Facebook Inc.

To help attract the talent SAP needs to keep pace with users’ expectations, Plattner today opened a development center outside Berlin to incubate technology and foster young programmers. The “Innovation Center” sits on a Potsdam lakeside 9 kilometers (5.6 miles) from the research institute that bears the SAP chairman’s name.

SAP plans to make the site a key development hub and will potentially double its staff to 150 to work closely with technology startups, said a person familiar with the matter, who asked not to be named because the plan isn’t public.

“The biggest weakness of SAP worldwide is the user interaction,” said the 70-year-old, who was joined by other top SAP executives. “We don’t want to leave anyone behind, but we have to move this franchise forward.”

The company Plattner co-founded 42 years ago is undertaking a tricky transition from programs for managing supply chains and financial systems installed on customers’ computer servers to newer cloud-computing applications delivered over the Internet. Hand in hand with the change is a database called Hana and new user interface that offer customers faster response times and a more Web-like look.

400 Kilometers

“SAP has to be closer to the 150,000 students in Potsdam and Berlin,” Plattner said, wearing a purple sweater and addressing a room full of staff, customers and journalists. “Not everyone wants to come to Walldorf.”

Plattner was referring to SAP’s headquarters more than 400 kilometers southwest of Berlin. “We have to retrain 20,000 developers inside SAP.”

To be sure, re-making the business software to attract new customers isn’t as simple as opening a shiny development center near the German capital, a point Plattner underscored when he swatted away questions about other parts of the world rivaling California’s Silicon Valley.

The shift to cloud computing is also hurting profit. SAP has already pushed back its goal of reaching an operating margin by two years to 2017 because rented Web software costs less upfront than the programs it traditionally offered.

The company’s revenue may reach 19.1 billion euros ($26 billion) in 2015, according analysts’ estimates compiled by Bloomberg. The company had forecast 20 billion euros in sales for that year.

Late Cloud

“SAP is thinking more optimistically about growth of its core than we are,” Rick Sherlund, a Nomura Securities analyst who recommends buying SAP shares, said in a Feb. 4 note. “SAP is late to the cloud.”

To bridge the gap, the company is pouring effort into a simpler user interface and developing products SAP can continually update online.

Those two things have been traditionally difficult for SAP, but we have been putting a lot of energy into that recently,” Vishal Sikka, SAP’s chief technology officer and a board member, said in a recent interview.

At the two-day event where Sikka also spoke, SAP is showcasing how its software can be applied to new areas -- such as personalized medicine and sports statistics analysis -- that can help with the transition.

Co-Chief Executive Officer Bill McDermott also appeared, saying that by 2025, more than 70 percent of workers would belong to the “millennial” generation born after the early 1980s.

Hana Growth

The data-crunching Hana software -- an acronym for high-performance analytic appliance -- rapidly processes millions of database records ranging from business data to genome sequences found in cancer patients’ blood. The vast quantity of information amassed by businesses, governments and universities that requires powerful computers for storage and analysis is often referred to as big data.

SAP’s chairman, with a fortune of $10.6 billion according to the Bloomberg Billionaires Index, has had a long-running professional feud with Oracle Corp. (ORCL:US) CEO Larry Ellison. Plattner incubated Hana, which competes with Oracle, using a small group of developers near Berlin. Sales of Hana grew 61 percent last year to 633 million euros ($864 million), and are a bright spot amid slower growth for traditional software.

The shares were little changed at 57.18 euros at 3:03 p.m. in Frankfurt, valuing the company at 70.3 billion euros.

McDermott, an American who will take over as sole CEO in May, told investors in New York last week that SAP is dedicating more salespeople to online software.

Plattner, who is SAP’s biggest shareholder with a 10 percent stake, also plans to address how the new center in Potsdam can work more closely with the Hasso-Plattner Institute, an academic research body he has personally endowed.

Genome Interpretation Appliance; Designed in California, Develped in Europe & Mexico, Manufactured in Asia?

[We are not there yet - but getting very close ... Pellionisz]


Students and faculty of the Polytechnic University of Tulancingo (UPT) participated in the presentation of the Italian researcher, Anna Carbone, who taught the short course "Fractals, Hurst exponent and applications" aimed at teachers of Full Time (PTC) College.

This training was aimed at providing a broad overview of the type of research being conducted in Europe but particularly in the type of research conducted by the Polytechnic of Turin.

Academics of the UPT I said that once completed the course the opportunity to make a working visit to the PTC's in the company of Dr. Carbone Italian Innovation Center gave - Mexican Manufacturing High Technology Hidalgo (CIIMMATH) located in Ciudad Sahagun, in order to analyze opportunity areas where knowledge transfer and human resources is made, in this case of spaces for students of the Polytechnic of Tulancingo to stay working.

Additionally, the researcher Carbone also provided a specialized postgraduate students of UPT, where he provided more detail about what a fractal is a structure which is repeated at different scales of observation course information.

The course also established the mathematical basis of the Hurst exponent which indicates that occurs in several areas of applied mathematics, including fractals and chaos theory, processes of long memory and spectral analysis, the estimated Hurst exponent has applied in areas ranging from biophysics to computer networking, added another application such as in the Deoxyribonucleic Acid (DNA) in predicting disease.

In a third talk, Anna Carbone gave the Conference "The Hurst exponent: applications in Finance and Genomics" to degrees and engineering students of this university, where he explained techniques derived from statistical mechanics developed by it for 10 years, these techniques are based on the fractal analysis or measurement of the state of disorder of a specific system, exemplified in his study two applications.

Based on measurements of the method proposed by the specialist, you can determine whether a person is healthy or ill, and identify the degree of vitality of a body and the second example stated in the financial areas using the method in fractal where helps determine the market trend, ie if it is on the rise or is presented with a negative investment trend. He later made a tour of the campus facilities, for equipment that are available visit.

Téllez Gerardo Reyes, Rector of UPT, said that thanks to the linkage with international institutions and the support of the Ministry of Public Education, the renewal of agreements with prestigious foreign institutions result in the exchange of knowledge and research by teachers recognized globally, which benefits students and faculty to enlarge the picture in their areas of education, said the Polytechnic of Turin in Italy is located as the third best institution of higher level in your country and the researcher Anna Carbone is shown that the quality of university.


Anna Carbone obtained the degree of Master of Science in 1988 and a PhD in Physics in 1993, both from the Polytechnic of Turin, since 1998 he is a researcher in the Department of Applied Science and Technology at the same University, where he directs the Laboratory Fluctuations and Noise.

His research is related to the theoretical and experimental analysis of noise and stochastic processes in different systems is the author of several research articles that have been published in international journals.

A member of International Scientific Committees and editor of magazines such as: Physica A, Frontiers in Fractal Physiology, among others, also she has collaborations in various European projects

[The "Genome Interpretation Appliance" - like everything else - is likely to be manufactured in Asia, see involvement of SONY and SAMSUNG already, for the key parallel chips NVidia GPU and or Xilinx FPGA, for multi-core chips Intel and/or AMD are contenders. Global integrators like Google AND Apple (Calico), Cisco, Amazon, HP, DELL are already lined up. Chinese BGI, Boston-based Broad-affiliated Foundation Medicine, Houston-based Baylor are already deep into (cancer) applications. The "hard part" is to build the new science of Genome Interpretation by software-enabling algorithmic approach. Fractals have no reasonable alternative. Moreover, a global cooperative effort is emerging - chalk up Mexico and Europe (Italy) - Pellionisz]

Patent War-Weary Samsung Inks Cross-Licensing Deal with Cisco

Feb. 7, 2014DH Kass | The VAR Guy

Maybe Samsung is a little punchy from fighting intellectual property wars on multiple fronts worldwide. The Korean manufacturer signed a new, 10-year cross-licensing deal with Cisco, giving each company access to the other’s current patent folders and to whatever product and technology IP each records over the agreement's lifetime.

The Korean manufacturer certainly seems in a patent peace-making frame of mind now.

Samsung's latest truce overture is a new, 10-year, broad cross-licensing deal with networking giant Cisco Systems (CSCO), giving each company access to the other’s current patent folders and to whatever product and technology IP each records over the agreement's lifetime. Neither party disclosed contract terms.

In a statement, the vendors called the agreement an “important industry step to enhance cooperation by curbing unnecessary patent litigation,” more of which has encumbered Samsung than Cisco of late. The deal marks Samsung’s third cross-licensing agreement in just the past few weeks, as the device maker appears to want to remove as much wireless patent clutter from its path as possible.

In January, Samsung ended a protracted patent battle with Ericsson (ERIC) when the two heavyweights agreed to cross-license each other’s cellular technologies, effectively ending a dispute stemming from the mobile network equipment maker’s lawsuit filed late in 2012 claiming the Korean device maker had infringed its intellectual property.

And, with overtones of its Cisco IP deal, Samsung earlier initiated a 10-year, global patent cross-licensing pact with Google (GOOG) that could include thousands of patents, not only for existing technologies and businesses but also for patents filed for the life of the agreement. Samsung and Google are regarded as longtime collaborators but until now the two had not signed a formal intellectual property deal.

Dan Lang, Cisco IP vice president, said the licensing agreement with Samsung will boost innovation for future products and services and lower the possibility that the vendors might sue each other over patent infringement conflicts.

"Innovation is stifled all too often in today's overly litigious environment," he said. "By cross-licensing our patent portfolios, Cisco and Samsung are taking important steps to reverse the trend and advance innovation and freedom of operation."

Dr. Seungho Ahn, Samsung Intellectual Property Center head, said the vendor expects the IP pact will “result in mutual growth and, ultimately, for the benefit of both companies' customers across the world."

[In the prolonged era when global health-care was dominated only by "Big Pharma", the increasingly globalized mergers and acquisitions of Pharma-companies could resolve precious intellectual property issues. With the new era of "Genome-based Information Technology" the (partial) list of global IT-companies listed below is expected to grow at a feverish rate. Chalk up Cisco to the list with the present announcement of a Cisco-Samsung agreement between a US-based and a Korea-based IT giant. While such alliances might reduce the workload of lawyers, it is unlikely that they will become unemployed anytime soon, however. Consider for example that Samsung now allied itself with Cisco of the USA - but it is also allied with Google! How would this affect e.g. Calico, Inc. that is in part Google, but Samsung's arch-enemy (Apple) is also involved? Given the $Trillion ticket of "intellectual property wars" (e.g. between Samsung/Apple), it may be imperative not only to form alliances to prevent "wars flaring up", but use the rather common practice of "gathering an Intellectual Property portfolio" also in the emerging market of "Genome-based economy". The legal bill of fighting over smartphone features is likely to be dwarfed by global battles over intellectual property used by "IT-Titans" - AJP]

These 3 Tech Titans Could Revolutionize Health Care

by Leo Sun, The Motley Fool Jan 28th 2014 

When most people think of Sony, Samsung Electronics or Google, they think of video games, smartphones, tablets, or search engines. These days, however, these tech giants are taking huge steps to expand their technological capabilities beyond the everyday consumer.

Sony, Samsung, and Google have all recently made unexpected moves into the health care industry -- a high-growth market where technology is merging symbiotically with life sciences and medicine.

Let's take a closer look at some fascinating ways that these three companies could revolutionize health care with their new investments.

Sony launches a genome information platform

Sony, the Japanese conglomerate best known for its electronics, video games, and media businesses, is now interested in genome sequencing.

Genome research, which analyzes human genetic data in comparison to other medical or scientific data, is widely believed to be the key to identifying the origins of diseases and developing personalized treatments for patients.

On January 23, Sony announced a partnership with Japanese medical portal M3and life sciences giant Illumina to launch a genome information company, known as P5, in Japan by the end of February. Sony and M3 will establish P5, with Illumina acting as a minority investor.

The goal of P5 is to provide a genome analysis service to medical and research institutions across Japan, with a long-term goal of the creation of personalized medicine and health care services.

The establishment of P5 comes at a time when the costs of human genome sequencing are dropping substantially -- earlier this month, Illumina broke the "genome sound barrier" with a new machine that can sequence the entire human genome for $1,000. To put that into perspective, the same process would have cost $250,000 a decade ago, and the process on current high-end machines still costs $3,000 to $5,000. 

Illumina's HiSeq X Ten system can sequence an entire human genome for $1,000. Source: Illumina.

Since Sony has partnered with M3, it's assumed that P5 will store the collected data in the cloud, which means that individual patients could eventually access their genetic records online.

Sony CEO Tadashi Saito stated that Sony was positioning the medical business as one of the company's "key growth pillars," which would be a huge change from the status quo. Today, Sony's tiny medical business is tucked away in its imaging equipment segment (including cameras), which accounts for 10% of its total revenue.

Samsung's quiet evolution into a medical giant

South Korean tech giant Samsung Electronics has similar goals, with an ambitious plan to become of the world's largest medical equipment companies by 2020.

Samsung forecast $400 billion in annual revenue by 2020, with $10 billion (2.5%) of its top line eventually being generated by medical devices. The company's big push started with its acquisition of ultrasound maker Medison in 2010, followed by health care equipment maker Nexus in 2011 and the medical imaging company NeuroLogica in 2013. All this inorganic growth culminated in the launch of GEO, Samsung's new line of digital radiology and in-vitro diagnostic equipment.

Samsung's medical device business is still relatively small -- it generated $300 million in sales in fiscal 2012, with an expectation for sales of $500 million in fiscal 2013. However, Samsung's growth plans could put it on a collision course with the Goliaths of the field -- General Electric, Koninklijke Philips, andSiemens -- which generated combined sales of nearly $50 billion in fiscal 2012.  

Samsung Electronics also owns a 40% stake in Samsung BioLogics -- a separate company that intends to become "a world leader in biologics development and manufacturing." Biologics are medicines synthesized biologically (vaccines, antibodies, proteins) and not chemically. They include some of the best-selling blockbuster drugs today, such as AbbVie's Humira,Johnson & Johnson and Merck's Remicade, and Amgen's Enbrel.

Last October, Roche signed a manufacturing agreement with Samsung Biologics to manufacture Roche's proprietary commercial biologic medicines in Incheon, South Korea. These ambitious investments in medical equipment and biologics put Samsung Electronics in a strong position to shake up the health care industry, as it has done with smartphones and tablets over the past five years.

Google's ambitious blitz on medical devices and medicine

Last but definitely not least, search giant Google's ambitious investments in health care could shake up the industry. Google Glass, which is scheduled to be released in April, has already been considered a next-generation tool for physicians, thanks to its onboard camera and Internet connectivity. Several major companies, such as Qualcomm and Phillips, are experimenting with different medical applications for Google Glass in idea incubators.

Google also recently announced that it was developing a smart contact lens for diabetics as a replacement for the daily pinpricks necessary for glucose monitoring. Google's approach is completely new -- it tests glucose levels through tears. If the project is successful, the lens could synchronize to smartphones or other devices, similar to newer glucose monitors like Sanofi's iBGStar, and render painful pinpricks obsolete.

In the biotech field, Google created Calico (California Life Company) last September. Calico is headed by former Genentech (now a Roche subsidiary) CEO Arthur Levinson. The company's goals are incredibly ambitious, with an ultimate goal to extend the average human lifespan by 20 to 100 years and treat age-related diseases such as Alzheimer's, cancer, and heart disease.

Google clearly isn't expanding into the health care industry because of an immediate need for profit, since its core revenue is still generated by search advertising. Yet that's what makes Google's efforts all the more fascinating. With nearly $55 billion in cash and equivalents, the sky's the limit for Google's medical ambitions.

The Foolish takeaway

Sony, Samsung, and Google only represent three companies benefiting from the convergence of the tech and medical industries could revolutionize the health-care industry.

With the increased use of medical portals, smartphones, and tablets in hospitals, it's likely that other tech companies, traditionally associated with consumer or business products, will also expand into the health-care market as well. When these top minds in tech and health care pool their efforts together, medical devices and biotechnology could improve the lives of patients worldwide.

Want to learn more about the tech and health care industries?

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[As Dr. Pellionisz widely disseminated in his 2008 prediction Google Tech Talk YouTube (Is IT Ready for the Dreaded DNA Data Deluge?), not only the enlisted three global IT-leader companies moved for a pivotal position. One could easily add GE Health, Amazon, Dell, HP and chip companies Intel, NVidia, AMD, Xilinx, Altera in the USA, and Siemens, Philips in Europe. A most interesting further global player might be Microsoft - with its new CEO totally aware of the global role that software development and clinical trials mean by India (perhaps in an alliance with Tata). Since Intellectual Property of Genome Analytics plays a key role (no matter what the hardware platform may be for a "Genome Appliance" to be used in US hospital systems e.g. for precision cancer therapy), FractoGene US patent 8,280,641 in an appropriate licensing agreement is leveraged globally, for the most lucrative US market - Pellionisz, HolGenTech_at_gmail_dot_com]


Written By: Jason Dorrier

Posted: 02/2/14 7:00 AM

Illumina, the biggest maker of genomic sequencing machines, say they’ve broken the “sound barrier” of sequencing. Their latest machine can transcribe 18,000 human genomes a year for $1,000 per genome - a mark dreamed of for over a decade.

When the human genome’s three billion molecular pairs were first fully transcribed (or sequenced) in 2003, it was deemed a seminal accomplishment, but one seemingly destined to be repeated only rarely. The project’s cost totaled $2.7 billion, and the first genomes were hundreds of millions of dollars apiece.

It was around that time that the $1,000 genome was first targeted. Why $1,000? Well, it’s a nice, round, pretty much arbitrary number - a sort of mile marker set by researchers. If ever it gets that cheap, scientists thought, we’ll be able to do anything.

In the early days, many experts thought it was an impossible target, Raymond McCauley, Chair of the Biotech Track at Singularity University, recently told Singularity Hub. But as costs began falling, the $1,000 genome started looking more realistic.

In 2006, the New York Times ran an article titled, “The Quest for the $1,000 Genome.” At the time, per genome sequencing costs had declined a full order of magnitude. Yet, despite a pace on par with Moore’s Law, if progress had continued along that line, the cost to sequence the human genome would still be over $1 million in 2014.

But it’s not. Not even close. Shortly after The New York Times article was published, next-generation sequencing hit the commercial market in a big way. What had, in the beginning, seemed an almost mythical goal started to look not only like a foregone conclusion - but one that would be realized far sooner than imagined.

Traditional sequencing (or Sanger sequencing) transcribes DNA using a complex, time-consuming, and costly chemical process. Next-generation machines, on the other hand, are more like supercomputers. They work in parallel, using brute force to simultaneously read millions of DNA base pairs at a time.

In the last six years, primarily on the back of next-generation sequencing technologies, costs have far outpaced Moore’s Law, falling four orders of magnitude from $10 million at the end of 2007 to under $5,000 at the end of 2013. 

Now, owners of Illumina’s $10 million HighSeq X Ten may run 18,000 genomes a year for $1,000 a pop. That’s about a fifth of all the genomes that have been sequenced in history at a fraction of the expense. 

It’s a staggering achievement a mere decade in the making. And as McCauley notes, “$1,000 is good base cost because it’s cheaper than an MRI; it’s cheaper than a lot of CT scans or a chest x-ray in some places.

But it’s worth a moment’s pause to discuss what Illumina’s claim really means.

As the name implies, the HighSeq X Ten isn’t really one machine. It’s ten. The supercomputer analogy is instructive here too. Though there are more transistors per chip these days, the fastest computers mainly get faster by packing more chips into more cabinets—they still fill entire rooms.

Also, the cost of sequencing is a sensitive, much hyped subject. The $1,000 genome has been just around the corner for roughly two years now. Beyond flashy PR claims, cost calculations can be controversial.

In the past, firms would include the expense of chemicals but exclude key line items like depreciation and labor, sparking fierce debates online—a fact, no doubt, Illumina knows well. They were careful to include chemicals, depreciation, and labor (albeit cheap labor, according to some) in their estimate.

McCauley says, “You can tell that they’ve been working on it and waiting to get that marginal cost of chemicals and reagents down below a certain figure where the all-in cost for materials, the depreciation on the machine, and all of that, is right about at $1,000.”

Even so, he went on to tell us, the numbers haven’t been nailed down yet.

The National Human Genome Research Institute (NHGRI) publishes the most referenced graph (see above) on sequencing costs. NHGRI uses the cost of sequencing reported in research papers. That is, instead of going by a firm’s initial claim, they wait to see how the machine performs in practical use.

According to Illumina, they’ve sold machines to Korean genomics firm, Macrogen, the Broad Institute in Cambridge, Massachusetts, and the Garvan Institute of Medical Research in Sydney, Australia. The machines are due to ship the first quarter of 2014, and of course, they’ll take time to ramp up to full capacity.

There’s one more item worth noting—and this point may be somewhat lost in the chatter—you or I can’t go to a clinic to get our genome sequenced for $1,000. Not yet at least.

Machines like the HighSeq X Ten focus on sequencing for research purposes, for scientists conducting broad studies of thousands and tens of thousands of human genomes at a time. By comparing a large number of genomes, researchers can associate conditions and diseases with particular genes. This research is crucial if we are to replace DNA transcription with understanding and fluency in the language.

At $1,000 per genome, such work will likely accelerate.

McCauley notes that for a million dollars we could sequence one genome six years ago. Four years ago we could sequence ten; three years ago we could sequence a hundred; and now we can sequence a thousand.

“It’s one thing to say we’ve sequenced a single reference genome at the beginning of the century,” McCauley says, “It’s another thing to have a million genomes in a database. With this scale of improvement that becomes very reachable. And in fact, in aggregate, I think over the next couple years we are going to see a million genomes sequenced.”

But where all that data goes is an open question. A significant chunk may be tied up in proprietary, private pharmaceutical drug testing databases instead of being made publicly available by publicly-funded research groups. For the sake of faster progress, according to McCauley, the more of the latter we have, the better.

So, if practical results prove Illumina has truly claimed the $1,000 genome—what happens next? McCauley thinks next-generation sequencing is ripe to be supplanted by next-next generation sequencing. And today’s fast pace will largely continue.

“Anybody who enters into this, they’re living in dog years. They’ve got to figure out how to not only make the technology work but keep improving it at this pace of probably 4x or 5x a year—just to compete.”

And perhaps, increasingly, we’ll see a more diversified approach. Some work, for example, will focus more on speed or miniaturization.

Certain requirements, say sequencing an individual cancer genome, may prove more urgent and less concerned with ultra-low cost. Eventually, McCauley says, we’ll see handheld DNA scanners for environmental identification and security. James Bond stuff.

The current trajectory hints at such sci-fi devices, but not immediately.

Closer in, we need to get a handle on the impending flood of data. It doesn’t make sense to have a team of geneticists pouring over every line. On the path to truly clinical genomics, expect software engineers and programmers to lay the next paving stones.

“Interpretation is king from now on,” McCauley says.

["From now on, interpretation is king" - says in 2014 McCauley". Interpretation has been a Princess at least since 2008, when in a Google Tech Talk YouTube (Is IT Ready for the Dreaded DNA Data Deluge?) this genomist predicted a massive "glut" of DNA sequences, threatening an unsustainable growth of the industry of sequencing - unless "Interpretation" ramps up the demand to match the supply. Not many listened - and the result was painfully experienced when at least half a $Bn valuation of sequencing companies were lost as a result. In the last 12 months, both Complete Genomics had to be sold (deep below its real worth) for a mere $117M to CHINA (and likewise, Pacific Biosciences also had to be sold, to Life Technologies). Now it is evident that Illumina will not be able to do "analytics" alone - has just closed a deal to team-up with SONY (of Japan). SAMSUNG (of Korea) has been providing an "analytics service" for about 30 months, and SIEMENS (of Germany) is also looking carefully at the emerging market. In theUSA, the newly announced Calico, Inc. (jointly by GOOGLE and APPLE) will, by necessity, arrive at the same conclusion - that a "Genome Analytics Appliance" must be constructed, enabled by proprietary IP for analytics (such as FractoGene, US patent 8,280,641, in force till 2026 late March). As for technology, a key question is for any/all such plans is if the required HPC will deploy GPU and/or FPGA parallel processors. As for the US hospital (cancer) market, a key is the deployment and clinical trial system, see here. For further info, contact Dr. Pellionisz, HolGenTech_at_gmail_dot_com.]

LincRNA, once believed useless, plays role in genome

Medical Press
January 23, 2014

By B.D. Colen

[John Rinn in the middle - AJP]

Ever since the Human Genome Project decoded the genome, the prevailing scientific view has been that only the 2 percent that makes proteins—the building blocks of cells—was important. The rest was deemed not functional, or "junk." But from his days in graduate school, through his postdoctoral fellowship, and now as a Harvard Stem Cell scientist, John Rinn has been digging through the genome, challenging that prevailing belief.

Now, Rinn and his Harvard Stem Cell Institute colleagues, including neurobiologist Paola Arlotta, have carried out an elegant and important experiment in which they have demonstrated that much of what had been dismissed in fact plays as vital a role as protein-coding genes.

Rinn and his colleagues have generated 18 strains of mutant mice, removing from each a different piece of "junk" genome, or so-called long intergenic noncoding RNAs (lincRNAs). If the lincRNA truly had been "junk," nothing should have happened.

What the researchers found was the opposite. Obvious defects were observed in seven of the 18 mutant strains. Three died shortly after birth, and there is reason to believe many others also are defective. The authors reported these and more findings in the new online journal eLife, initiated by the Howard Hughes Medical Institute, the Wellcome Trust, and the Max Planck Institute.

Martin Sauvageau, Loyal Goff, and Simona Lodato, the lead authors on the study, say it will take years to study all the mice, but an initial global characterization determined that seven had obvious defects, including early death, inadequate size, and lung and brain defects. Others had problems that were more subtle.

"There has been a lot of skepticism whether these long noncoding RNAs are important for living organisms," said Rinn, "but you can't say this is junk without testing it. The question will always be what percentage is junk, and what's functional. But what we need to do is look at lincRNAs with the same careful focus we've applied to protein-coding genes, using genetics to characterize them, and see what role they play on a molecular and organismal scale."

Rinn and Arlotta see their collaboration as unusual and yet indicative of how the Department of Stem Cell and Regenerative Biology, in which they are both faculty members, brings together scientists of disparate backgrounds and interests.

"How do a neuroscientist and an RNA biologist come together?" Rinn asked rhetorically. "That's the story of our department: two scientists coming together to do something neither would have done on their own. And our labs have become seamless. That's something the department aims for.

"I'm a geneticist who had never worked with mice. Paola is a neuroscientist who had experience with mice, but for whom this kind of genetic experiment was new. But she has a history of being a classic neurobiologist who takes risky, successful technological leaps. This set of experiments constituted a huge risk for both of us, and for the postdocs who did the work," Rinn said.

"We got into this because we thought these [lincRNA] molecules could be another layer of explanation of how a tissue as complex and mysterious as the brain is made," said Arlotta. "And indeed we found that these are key molecules for brain development."

The lincRNAs control the stem cells that give rise to a "particular class of neurons … that are important in the expansion of the brain, in the part that controls intelligent behavior, cognition and perception, the part of the brain that makes us," Arlotta said.

"When we removed the specific lincRNA, we looked at the mouse brain and the progenitors were reduced. As a consequence probably, the population [of neurons] that sits on top of the cerebral cortex are reduced … It's likely that in the future we'll see a number of studies showing that other lincRNAs are involved in specific behaviors," Arlotta said. "The brain likes this junk RNA."

[Beyond the above journalistic coverage, the peer-reviewed science paper is found below - AJP]

Multiple knockout mouse models reveal lincRNAs are required for life and brain development

[Positive experimental evidence against the "Junk DNA" dead-end (see in full in Ohno 1972 seeding the wrong idea that most of the human DNA is there "for the importance of doing nothing"). The "Junk School of Genomics" was exactly what Mattick referred to over a decade ago as "the biggest mistake of the history of molecular biology" - AJP]

Martin Sauvageau, Loyal A Goff, Simona Lodato, Boyan Bonev, Abigail F Groff, Chiara Gerhardinger, Diana BSanchez-Gomez, Ezgi Hacisuleyman, Eric Li, Matthew Spence, Stephen C Liapis, WilliamMallard, Michael Morse, Mavis R Swerdel, Michael F D’Ecclessis, Jennifer C Moore, Venus Lai, Guochun Gong, George D Yancopoulos, David Frendewey, Manolis Kellis, Ronald P Hart, David M Valenzuela, Paola Arlotta, John L Rinn

Harvard University, United States; Broad Institute of MIT and Harvard, United States; Massachusetts Institute of Technology, United States; Rutgers, The State University of New Jersey, United States; Regeneron Pharmaceuticals Inc.,United States; Harvard Medical School, United States

DOI: Published December 31, 2013Cite as eLife 2013;2:e01749

Many studies are uncovering functional roles for long noncoding RNAs (lncRNAs), yet few have been tested for in vivo relevance through genetic ablation in animal models. To investigate the functional relevance of lncRNAs in various physiological conditions, we have developed a collection of 18 lncRNA knockout strains in which the locus is maintained transcriptionally active. Initial characterization revealed peri- and postnatal lethal phenotypes in three mutant strains (Fendrr, Peril, and Mdgt), the latter two exhibiting incomplete penetrance and growth defects in survivors. We also report growth defects for two additional mutant strains (linc–Brn1b and linc–Pint). Further analysis revealed defects in lung, gastrointestinal tract, and heart in Fendrr−/− neonates, whereas linc–Brn1b−/− mutants displayed distinct abnormalities in the generation of upper layer II–IV neurons in the neocortex. This study demonstrates that lncRNAs play critical roles in vivo and provides a framework and impetus for future larger-scale functional investigation into the roles of lncRNA molecules. - See more here.

[Half a Century after Nobel-laureate Jacobs and Monod, this spectacular experimental evidence will rapidly accelerate the advancement of the new mathematical theory of recursive genome regulation. As Mattick, a long-time pioneer of RNA interpretation expressed so emphatically, "most assumptions are wrong". An exceptional beauty of the experimental study is that it calls for a unification of neuroscience and genomics - AJP]

Sony forms genome analysis company [with Illumina] in move towards personalized medicine

The Verge,

Sam Byford on January 23, 2014 02:09 am

Sony is forming a new company to focus on genome research with a view towards realizing personalized medicine and healthcare. The venture, currently called P5 Inc, is a collaboration with M3, a medical company in which Sony is the majority stakeholder, and Illumina, a US-based manufacturer of genome-sequencing equipment. News of the tie-up between Sony and Illumina, which will be a minority investor, was first reported by Jiji Press last year.

Sony refers to the collaboration as a "genome information platform." It will provide genome analysis services for enterprises and research institutions in Japan at first, as well as aggregating genetic data with other medical data. Sony expects the business to eventually expand to individual patients by providing the same mix of genome data and medical information to allow for personalized healthcare. Genome research can be used to develop new methods of treatment and identify the origins and likelihood of diseases.

The medical sector is an increasingly important area for Sony. New CEO and president Kaz Hirai announced plans to make it a core pillar of the company's business before taking over in early 2012, and Sony has since made major investments in the field. One such example is the $644 million spent on forming a medical imaging venture with Olympus, which the company said could push forward the development of technology such as 4K or 3D endoscopes.

Pulse of J.P. Morgan 2014: Interviews with 17 biopharma execs

SAN FRANCISCO--Another J.P. Morgan Healthcare Conference is in the books, and biopharma's movers, shakers and up-and-comers have headed back to Boston, Basel and Bangalore. This year, in the shadow of the best market for biotech IPOs since 2000, there's fresh optimism that capital will continue to flow into drug developers' pockets, whether via more market debuts or through the many top-tier VCs putting together new funds.

3 biotech investment trends gleaned from JP Morgan conference

January 17, 2014 8:50 pm by Stephanie Baum

Pharma is warming up to innovation, personal medicine, particularly for oncology, is hot, and molecular diagnostics have moved from the bench to the bedside. As bullish as investors seem about biotech investments, how long is that likely to last? Those were some of the talking points at the JP Morgan Healthcare conference where metaphors likening the investment atmosphere to the weather abounded.

IPO window is still wide open but for how much longer? The strong appetite for biotech initial public offerings, in 2013, at least 34 as of the start of December, is helping to feed the bullishness for investments in continuing to roll out Atlas Venture Partner Bruce Booth points out a fun fact in one blog entry about the conference: 12 biotech companies started a roadshow this week — a record number of simultaneous biotech road shows. As he points out, ”If the companies have done solid crossover rounds already, or have really compelling assets, the offerings and their pricings should be fine. But if not, good luck to them as it’s likely to be tough.”

Crowdfunding in biotech is rising Crowdfunding has been moving beyond the familiar territory of consumer goods to healthcare. Even so, it has primarily focused on medtech and health IT tools for an audience of medical staff or consumers. But Poliwogg’s initiative with the Epilepsy Foundation and Alpha 1 Foundation indicate that 2014 could be the year it expands in biotech in a significant way, particularly the crowdfudning model. A couple of biotech companies are also using MedStartr’s platform such as Atlantic Bio Sci.

Corporate venture capital funds investing in innovation A PriceWaterhouse Cooper’s report on healthcare investment trends pointed out that biotech is in the top five for corporate venture capital investing. Edward Yu, a principal at PriceWaterhouseCoopers Health Industries practice said companies realize that if they don’t invest in innovation, they’ll pay for it longterm. Corporate venture capital is about connecting the dots of innovation. It’s in a company’s best interest to ensure the entrepreneurs they invest in have a high likelihood of success. Companies are attracted to the lore of the Silicon Valley and take the attitude, ‘Why can’t I replicate the Silicon Valley inside my company?’

Janssen Labs seems to fit that description. It’s helping Johnson & Johnson Development Corp by tapping companies with innovative technology and providing them with the resources they need to be successful. It’s a moderate gamble for a big pharma company but given the analysis of FDA drugs approved last year, big pharma’s future depends on reaching beyond their walls and cultivating entrepreneurs. Janssen Labs Head Melinda Richter said its three innovation centers have helped change the culture of Johnson & Johnson and has made the company bolder.

Eric Schmidt's 2014 predictions: big genomics and smartphones everywhere

[See video and transcript at the link of this entry]

What does 2014 hold? According to Eric Schmidt, Google's executive chairman, it means smartphones everywhere - and also the possibility of genetics data being used to develop new cures for cancer. [Here the journalist is a bit sloppy, for presently there is NO cure for cancer - AJP]

In an appearance on Bloomberg TV, Schmidt laid out his thoughts about general technological change, Google's biggest mistake, and how Google sees the economy going in 2014.

"The biggest change for consumers is going to be that everyone's going to have a smartphone," Schmidt says. "And the fact that so many people are connected to what is essentially a supercomputer means a whole new generation of applications around entertainment, education, social life, those kinds of things. The trend has been that mobile is winning; it's now won. There are more tablets and phones being sold than personal computers - people are moving to this new architecture very fast."

It's certainly true that tablets and smartphones are outselling PCs - in fact smartphones alone have been doing that since the end of 2010. This year, it's forecast that tablets will have passed "traditional" PCs (desktops, fixed-keyboard laptops) too.

Disrupting business

Next, Schmidt says there's a big change - a disruption - coming for business through the arrival of "big data": "The biggest disruptor that we're sure about is the arrival of big data and machine intelligence everywhere - so the ability [for businesses] to find people, to talk specifically to them, to judge them, to rank what they're doing, to decide what to do with your products, changes every business globally.

He also sees potential in the field of genomics - the parsing of all the data being collected from DNA and gene sequencing. That might not be surprising, given that Google is an investor in 23andme, a gene sequencing company which aims to collect the genomes of a million people so that it can do data-matching analysis on their DNA. (Unfortunately, that plan has hit a snag: 23andme has been told to cease operating by the US Food and Drug Administration because it has failed to respond to inquiries about its testing methods and publication of results.)

Here's what Schmidt has to say on genomics: "The biggest disruption that we don't really know what's going to happen is probably in the genetics area. The ability to have personal genetics records and the ability to start gathering all of the gene sequencing into places will yield discoveries in cancer treatment and diagnostics over the next year that that are unfathomably important." [Some synonyms of "unfathomable" are - according to web - "unmeasurable", limitless, or infinite - AJP]

It may be worth mentioning that "we'll find cures through genomics" has been the promise held up by scientists every year since the human genome was first sequenced. So far, it hasn't happened - as much as anything because human gene variation is remarkably big, and there's still a lot that isn't known about the interaction of what appears to be non-functional parts of our DNA (which doesn't seem to code to produce proteins) and the parts that do code for proteins. [Here the journalist is amazingly precise. The obsolete dovetailing failed axioms of "Junk DNA" and "Central Dogma" have been defeated ("Last Mohicans" in the marginalized wilderness of the disarmingly naive antiquated beliefs don't matter any more than members - if any - of "Flat Earth Society"). While all knowledgeable scientists agree now that any and all parts of the genome may relate to protein coding, only FractoGene is a coherent mathematical algorithm that the genome does this in a dual valence (parts - formerly, "genes" - directly "constructing" amino-acids, thus proteins, that is mathematically a contravariant valence, while other parts - formerly collectively misunderstood as "junk DNA" indirectly code for proteins, by means of "measuring" built proteins, that is mathematically a covariant valence. The intrinsic mathematics of the quest for hologenomic equilibrium (life) is nonlinear dynamics (fractals and chaos). Intellectual property is held as a powerful combination of US patent 8,280,641 in force till late March, 2026, intertwined with "trade secrets" representing "state of art" beyond the last CIP to said FractoGene patent (2007) - AJP; holgentech_at_gmail_dot_com]

Biggest mistake

As for Google's biggest past mistake, Schmidt says it's missing the rise of Facebook and Twitter: "At Google the biggest mistake that I made was not anticipating the rise of the social networking phenomenon - not a mistake we're going to make again. I guess in our defence were working on many other things, but we should have been in that area, and I take responsibility for that." The results of that effort to catch up can be seen in the way that Google+ is popping up everywhere - though it's wrong to think of Google+ as a social network, since it's more of a way that Google creates a substrate on the web to track individuals.

And what is Google doing in 2014? "Google is very much investing, we're hiring globally, we see strong growth all around the world with the arrival of the internet everywhere. It's all green in that sense from the standpoint of the year. Google benefits from transitions from traditional industries, and shockingly even when things are tough in a country, because we're "return-on-investment"-based advertising - it's smarter to move your advertising from others to Google, so we win no matter whether the industries are in good shape or not, because people need our services, we're very proud of that."

For Google, the sky's the limit: "the key limiter on our growth is our rate of innovation, how smart are we, how clever are we, how quickly can we get these new systems deployed - we want to do that as fast as we can." [A most important legacy of Steve Jobs may be that hiring smart and clever people, and developing systems fast practically failed him - in the competition with IBM and Microsoft since smart and clever people are a commodity, and new system development is a direct function of investment in labor. He made Apple the most valuable company in the World, ever, by deploying Intellectual Property acquisition and protection - AJP]

It's worth noting that Schmidt has a shaky track record on predictions. At Le Web in 2011 he famously forecast that developers would be shunning iOS to start developing on Android first, and that Google TV would be installed on 50% of all TVs on sale by summer 2012.

It didn't turn out that way: even now, many apps start on iOS, and Google TV fizzled out as companies such as Logitech found that it didn't work as well as Android to tempt buyers.

Since that, Schmidt has been a lot more cautious about predicting trends and changes - although he hasn't been above the occasional comment which seems calculated to get a rise from his audience, such as telling executives at a Gartner conference that Android was more secure than the iPhone - which they apparently found humourous.

["It is difficult to make predictions, especially about the future". Thus, learning from history and questioning options of the future may be more productive. Overlooking Social Media is a mistake that Eric Schmidt is taking reponsibility for - to the tune of $billions. Given that he properly assesses the implications of genome informatics & instrumentation "unfathomable" - who is the one who will take charge NOT to miss this colossal historic opportunity? Eric Schmidt is no longer the CEO of Google - Larry Page is. CEO of CALICO, established jointly by Apple and Google is led by former Genentech CEO and present Apple Chairman of the Board Apple, Art Levinson (former CEO of Genentech, now Chairman of the Board of Apple. In the USA, perhaps the above three towering key men might bear responsibility if the challenge is going to be met. -AJP]

We should be looking at a complete paradigm shift

[Have a lucky 2014 - maybe more hope for hundreds of millions of people suffering from genome-regulation diseases, most notably cancers - AJP]

On 5 December, agency director Francis Collins told an advisory committee that the NIH should consider supporting more individual researchers, as opposed to research proposals as it does now . The NIH currently spends less than 5% of its US$30-billion budget on grants for individual researchers.

The idea of funding individuals is not new. There are the HHMI awards, and since 2010, the UK Wellcome Trust, a charity based in London, has directed its funding to promising researchers, allowing them to pursue research directions without oversight.

“We’re in an era now where insights will come from people thinking through the implications of data,” - rather than simply producing data in order to secure grants. ... funding researchers for longer periods will free them from having to review and apply for so many grants, which can take up to 40% of their time

[One could argue if a "complete paradigm-shift" is even possible, albeit necessary (see video below at 21:30 "people do not like paradigm-shifts"). "Paradigm" from the Greek is like pillars upholding a construction. Removing them, without replacement, would generate the kind of collapse, the "horror vacui" that science abhors. Would one argue at all when concluding another 7-year epoch, one perhaps could footnote on science itself, rather than its perhaps rusty funding habits. This columnist pointed out in 2008 (peer-reviewed paper and Google Tech Talk YouTube) BY WHAT new new foundation (The Principle of Recursive Genome Function) should replace the obsolete twins of "the biggest mistake in the history of molecular biology"; Central Dogma and Junk DNA misnomers. The paradigm-shift is precise though as subtle as the "butterly effect" ("Can the flap of a butterfly in Brazil trigger a tornado in Texas?") - in mathematics. The "genes/junk theory" had been largely void not only of advanced, but even quite rudimentary mathematics. A very recent review of nonlinear dynamics in neuroscience and genomics, spanning from Dr. Losa's 4 Conferences on "Fractals in Biology and Medicine" to Dr. Pellionisz' FractoGene is here in full.

[Can totally determined DNA explain the unpredictable chaotic-fractal Life ? BBC video on the nonlinear dynamics of geometry of life. 7 years after the Human Genome Project 2000, ENCODE revealed that the DNA was "pervasively transcribed". It took another 7 years since 2007 for the mainstream genomics to arrive at the realization that the mathematics of hologenomics is nonlinear dynamics, "beyond the Newtonian dream of total determinisms". With 2014 we enter the era of a novel philosophy, based on the "Principle of Genomic Unpredictability" [AJP]

Russian Billionaire Announces $3M Mathematics Prize


WASHINGTON, December 14 (RIA Novosti) – Top mathematicians will be rewarded for thinking big under a new $3 million prize announced by Russian billionaire Yuri Milner and Facebook founder Mark Zuckerberg.

Milner, a self-described “failed physicist” who made his fortune in high-tech investments, told The Guardian that he wanted the new Breakthrough Prize in Mathematics to encourage people to think more deeply about life. The prize will be awarded for the first time next year.

“If you take the largest scales possible, there are a number of scientists, individuals, who operate at that scale, they think about the whole universe. I think that we focus too much on small scales as human beings, and not enough on larger scales. That’s really the problem we’re trying to address here,” he told the paper Thursday.

The new prize was unveiled at an awards ceremony in the United States for two other multi-million-dollar research prizes established by Milner. The Fundamental Physics Prize, which he founded last year, was shared between Michael Green of Cambridge University and John Schwarz of the California Institute of Technology.

Green succeeded Stephen Hawking as the Lucasian professor of mathematics at Cambridge in 2009. Hawking won the first Fundamental Physics Prize last year.

The Breakthrough Prize in Life Sciences has been awarded to six scientists for their work, and each won $3 million. Milner co-founded the prize a year ago in partnership with Silicon Valley entrepreneurs including Zuckerberg; Sergey Brin, the Russian-American co-founder of Google; and Jack Ma, a Chinese entrepreneur.

The glitzy event in California was presided over by Hollywood star Kevin Spacey. Not everyone was impressed by the largesse of Milner and his fellow billionaires, however.

One “prominent physicist” who asked not to be identified told The Guardian that the money could be put to better use, saying: “The great philanthropists of the 19th and 20th centuries, like the Rockefellers and the Carnegies [or Stanford, nearby to the event - AJP], did not create prizes – they created universities and research institutes that have enabled thousands of scientists to make great breakthroughs over the succeeding decades.

“By contrast, giving a prize has a negligible effect on the progress of science. A few already well-recognized people get enriched, but there is little value added in terms of the progress of science compared with the multiplier effect of creating new institutions for scientific research.”

"The Last Mohican" of "Junk DNA" Obsolete Axiom

It could have been just an empty exercise to try to "avoid losing face" by facts coming down on him as a mega-ton of bricks, but a post-retierement age yet still active professor (of Biochemistry, not Genomics, and of course not in the USA but tucked away in a sparsley populated outskirt) could still be found late 2013 (December 30) with the rather laughable obsolete claim "Knowledgeable scientists agree that most (~90%) of our DNA is junk ". Since endengared species could disappear without notice, readers are encouraged to report to Holgentech_at_gmail_dot_com if in the coming up 2014 we'll find any professor not retired at relatively reputable universities/departments where obsolete teaching might still consume precious resources, occasionally even public tax monies. [AJP]

[Breakthrough Towards Deciphering Genomic Code of Life is Likely to Come from Mathematics] Mark Zuckerberg and Yuri Milner announced new $3 million Breakthrough Prize in Mathematics

[Breaking the Genomic Code of Life is more Likely to Come from Mathematics (Physics, Biophysics and Information Theory) Compared to Old Axioms Limited to Biochemistry. Yes, this made some biochemist(s) mad as hell - but on the doorstep of 2014 due course of science appropriately defeated the crazy misconception of junk-genomics (using the phrase from Mattick) - AJP]

2014 Breakthrough Prizes Awarded in Fundamental Physics and Life Sciences for a Total of $21 Million

SAN FRANCISCO, Dec. 13, 2013 /PRNewswire/ -- The names of the 2014 Breakthrough Prize winners in Fundamental Physics and Life Sciences were unveiled at an exclusive ceremony at the NASA Ames Research Center, Mountain View, CA. At a total awarded amount of $21 million, sponsored by Sergey Brin & Anne Wojcicki, Jack Ma & Cathy Zhang, Yuri & Julia Milner andMark Zuckerberg & Priscilla Chan, the prizes aim to celebrate scientists and generate excitement about the pursuit of science as a career.

The Breakthrough Prize in Fundamental Physics recognizes transformative achievements in the field of fundamental physics, with a special focus on recent developments. The 2014 winners are:

Michael B. Green, University of Cambridge, and John H. Schwarz, California Institute of Technology,for opening new perspectives on quantum gravity and the unification of forces.

The Breakthrough Prize in Life Sciences recognizes excellence in research aimed at curing intractable diseases and extending human life. The 2014 recipients are:

James Allison, MD Anderson Cancer Center for the discovery of T cell checkpoint blockade as effective cancer therapy.

Mahlon DeLong, Emory University for defining the interlocking circuits in the brain that malfunction in Parkinson's disease. This scientific foundation underlies the circuit-based treatment of Parkinson's disease by deep brain stimulation.

Michael Hall, University of Basel for the discovery of Target of Rapamycin (TOR) and its role in cell growth control.

Robert Langer, David H. Koch Institute Professor at the Massachusetts Institute of Technology for discoveries leading to the development of controlled drug-release systems and new biomaterials.

Richard Lifton, Yale University; Howard Hughes Medical Institute for the discovery of genes and biochemical mechanisms that cause hypertension.

Alexander Varshavsky, California Institute of Technology for discovering critical molecular determinants and biological functions of intracellular protein degradation.

"Scientists should be celebrated as heroes, and we are honored to be part of today's celebration of the newest winners of the Breakthrough Prize in Life Sciences and the Fundamental Physics Prize," said Anne Wojcicki and Sergey Brin.

The prize ceremony was hosted by actor Kevin Spacey, and awards were presented by the Prize sponsors and by celebrities including Conan O'Brien, Glenn Close, Rob Lowe and Michael C. Hall. The event was organized in cooperation with Vanity Fair and produced and directed by Don Mischer, the producer and director of the Academy Awards, among other television and live events. Grammy-nominated singer Lana Del Ray performed live for the guests of the ceremony.

The event will be televised by the Science Channel, one of the Discovery networks; it will be broadcast at 9pm on January 27th.

At the end of the ceremony, Mark Zuckerberg and Yuri Milner announced the launch of a new $3 million Breakthrough Prize in Mathematics. The details of the new prize will be announced at a later date.

"The Breakthrough Prize is our effort to put the spotlight on these amazing heroes. Their work in physics and genetics, cosmology, neurology and mathematics will change lives for generations and we are excited to celebrate them," commentedMark Zuckerberg.

Yuri Milner said: "Einstein said, Pure mathematics is the poetry of logical ideas. It is in this spirit that Mark and myself are announcing a new Breakthrough Prize in Mathematics. The work that the Prize recognizes could be the foundation for genetic engineering, quantum computing or Artificial Intelligence; but above all, for human knowledge itself."

This commitment to the pursuit and dissemination of knowledge is not limited to the Prize ceremony. On December 13, there will be two Breakthrough Prize Symposiums: at Stanford, on the Future of Fundamental Science; and at the University of California, San Francisco, on the Future of the Biological Sciences. Winners of the Breakthrough Prize from 2012, 2013 and 2014 will give lectures and take part in panel discussions before an invited audience.

Art Levinson, the chairman of the Breakthrough Prize in Life Sciences Foundation, said: "We are honored to recognize such an outstanding group of scientists as this year's Breakthrough Prize Laureates. We are sure they will continue to push back the boundaries of knowledge in the years to come."

About the Breakthrough Prizes

The Breakthrough Prize in Fundamental Physics and Life Sciences are founded by Sergey Brin & Anne Wojcicki, Jack Ma &Cathy Zhang, Yuri & Julia Milner and Mark Zuckerberg & Priscilla Chan. The prizes aim to celebrate scientists and generate excitement about the pursuit of science as a career. Breakthrough Prizes are funded by a grant from Sergey Brin and Anne Wojcicki's foundation, The Brin Wojcicki Foundation; a grant from Mark Zuckerberg's fund at the Silicon Valley Community Foundation; a grant from Jack Ma Foundation; and a grant from Milner Foundation. Laureates of all prizes are chosen by Selection Committees, which are comprised of prior recipients of the prizes.

The Selection Committee for the 2014 Breakthrough Prize in Fundamental Physics included:

Nima Arkani-Hamed

Lyn Evans

Fabiola Gianotti

Alan Guth

Stephen Hawking

Joseph Incandela

Alexei Kitaev

Maxim Kontsevich

Andrei Linde

Juan Maldacena

Alexander Polyakov

Nathan Seiberg

Ashoke Sen

Edward Witten

The Selection Committee for the 2014 Breakthrough Prize in Life Sciences included:

Cornelia I. Bargmann

David Botstein

Lewis C. Cantley

Hans Clevers

Napoleone Ferrara

Titia de Lange

Eric S. Lander

Charles L. Sawyers

Bert Vogelstein

Robert A. Weinberg

Shinya Yamanaka

Additional information on the Breakthrough Prizes is available at:

Media Contacts

Brunswick Group:

Oliver Phillips

+1 415 671 7676

Prize Foundations:

Leonid Solovyev

+44 7590 976 33

23andMe to only provide ancestry, raw genetics data during FDA review

By MICHELLE CASTILLO CBS NEWS December 6, 2013, 3: 33 PM

Genetic testing company 23andMe said Thursday it will still allow consumers to access ancestry-related information and raw genetic data without interpretation while complying with a Food and Drug Administration regulatory review.

23andMe added in a statement that it will continue with the company's educational projects and research using genetic and phenotypic data in their database.

“We remain firmly committed to fulfilling our long-term mission to help people everywhere have access to their own genetic data and have the ability to use that information to improve their lives,” Anne Wojcicki, co-founder and CEO of 23andMe, said in the press release. “Our goal is to work cooperatively with the FDA to provide that opportunity in a way that clearly demonstrates the benefit to people and the validity of the science that underlies the test.”

23andMe sold $99 genetic testing kits that allowed consumers to send in saliva samples. Laboratories then tested the sample, and the company provided detailed information based on the DNA analysis. This included ancestral origins, what traits the person was likely to have and what diseases they were more prone to developing.

On Nov. 22, the FDA asked 23andMe to stop selling the Saliva Collection Kit and Personal Genome Service. The FDA has restricted the company from providing health-related genetics tests while they are being reviewed.

The company said in marketing materials that the kits could provide reports on 254 diseases and conditions, but the FDA noted that the product was not approved by the government for those purposes.

The FDA was especially concerned because the results could cause consumers to make difficult, life-changing decisions on high-risk health issues, even though there was a possibility for a false positive or negative test result. The FDA was also troubled by the medication sensitivity tests because customers may be more likely to self-medicate or change their dosage without consulting with a medical professional.

Customers who were provided with health-related results or those who purchased kits before Nov. 22, 2013 will still have access to or will be given health-related results. Those who purchased kids after this date will only get ancestry information and raw genetic data without any form of interpretation. It is possible that they will get health-related results at a later date, pending FDA approval. Customers who bought a kit on or after Nov. 22, 2013 can receive a refund, and will be notified by email about how to go about receiving their money back.

A class action lawsuit was filed in the U.S. district court of California on Dec. 4 claiming that the company falsely marketed their kits, and have not proven that they provide scientifically-accurate results.

In October, critics spoke out about a patent on a product that 23andMe filed,called the Family Traits Inheritor Calculator. The product would allow consumers to send in a saliva to see what genetic traits and diseases their potential offspring could have. The application said that the company was seeking to use the item in fertility clinics. It could mean parents would be able to pick their children based on genetic superiority, what critics called "designer babies."

The company later clarified that while at the time they filed the patent they were considering practical applications in the fertility clinic, they have since decided to go in a different direction.

An article in Scientific American has also raised concerns that people who submitted their samples to 23andMe sign away their rights to their personal genetic data, allowing the company to share information about consumers’ genomes to other companies. This could potentially lead to more targeted consumer medicine, especially from insurance and pharmaceutical companies that would know a person’s “weaknesses.”

23andMe said it would not sell information without explicit consent from the consumer.

[Anne Wojcicki, "who picked up the Genome Baby left on the doorstep of IT", see at 6:10 of Google Tech Talks YouTube 2008 , is not the type who'd ever abandon her baby. The video shown in the December 6th article (aired November 7th) showed among its goals to "Revolutionize Healthcare". This may have rubbed Conservatives the wrong way, even triggering some into chaos. With the Solomon wisdom of dropping health advisories (for a while) and going on with the rest, she clearly wins this round with the FDA.

Notes for the two key sentences of the write-up: "On Nov. 22, the FDA asked 23andMe to stop selling the Saliva Collection Kit and Personal Genome Service. The FDA has restricted the company from providing health-related genetics tests while they are being reviewed." Well, the first sentence is how it happened by a bureaucrat already on record of mis-step (he declared in his letter "the 510(k)s are considered withdrawn, see 21 C.F.R. 807.87(1)"). The second sentence may be attributed to Dr. Margaret Hamburg, M.D., the Commissioner for FDA a number of days later (Dec. 3), when she may have realized the enormity of global business- and geopolitical implications of what appears to be another mis-step, and thus affirmed in Wall Street Journal a pledge by her subordinate [FDA and 23andMe] "remain committed to continuing our ongoing dialogue with the company in order to bring a safe, effective and trusted product to the market".

Be that as it may, the pledged "panel" and/or "dialogue" seems extremely unlikely to conclude prior to the "deadline" of December 16 set by "Warning Letter". It is not only difficult but probably meaningless to guestimate bureaucratic damage to Holiday Business of 23andMe, Inc. For any amount appears incomparably small to the illegal drug traffic measured as US $321.6 billion in 2003 (a decade ago, by all means probably much more damaging as 2014 nears).

Two competing trends have been de facto set into motion. Anne Wojcicki is not only committed to her "Genome Baby", but her conduct is exemplary - in retrospect reaffirms having been declared by "Fast Company" as "The Most Daring CEO of 2013". On the other hand, chaotic regulation accelerates "Globalization of Genome Industry", in this case with "third party genome analytics" where the US can only minimize damage if it is balanced by "US mover & shakers who invest locally but operate globally".

Let's make it very clear. Globalization did not start with the ongoing "episode of mis-communication". Roche established its subsidiary in Bangalore in 1956. Merck bought in 2006 SiRNA for $1.1 Bn in San Francisco, but shut down the SF facility in July 2011 - and almost simultaneously, moreover nearly exactly two years ago this day (2011 December 12) forked over $1.5 Billion dollars to its "research facility" in Beijing.

The reasons are not just bureaucratic. Application of a not necessarily effective regimen of drugs generates much more profit than a single "bulls-eye" (genome-based) precision medicine. Thus, innovation may accelerate to flee to countries where the reverse is true, since health-care is provided as a service (that needs to be both effective and of minimal costs) rather than business, particularly if the country not only recognizes but acts upon the strategic vital importance of genomics.

Need to list? One does not think so.

We could narrow down the list, however, to specific countries with a particular heritage in fractals (Lithuania, Poland & France [Mandelbrot ], France [Perez], Russia [Grosberg], The Netherlands [Ruis], Germany [Heinz-Otto Peitgen], Switzerland [Losa], Australia [Barnsley, Jelinek], Japan [Hokusai art], Korea [Dragon Temple]. China, with its most centralized government, is a category in itself [with its "fractal dragons"], while arch-rival India [that abounds with fractal architecture] might be moved in a coherent fashion by well-proven Industrial Groups [with genome-based generics to be made most competitively cost-effective for service-based health care]. The USA [Grosberg, Lieberman, Pellionisz, Shaw, etc.) can use USA/Global leveraging skills].

What the future holds, is anybody's "weather prediction" entering a non-linear dynamics mode. The state of art of genomics is definitely fragmented (fractal) and genome regulation seems chaotic.- AJP]

Fractal Genome and its Chaotic Regulation?

The news of "Warning Letter" by FDA to 23andMe, causing their marketing & sales to "cease and desist", plus a more recent Class Action law-suit against them (separately, but connected in a convoluted fashion) altogether created a veritable explosion in the cyber-space.

While the visible and the underlying (deeply entangled) issues are singularly complex, up to and including global strategy and balance, this columnist focuses on the perhaps not so widely understood science (an outstanding legal analysis is here). After all, it is interesting when science and the people's thinking about it is challenged by laws without a totally convincing mandate.

Dr. Guiterrez, who signed the "Warning Letter" from FDA, received a bachelor's degree from Haverford College and master and doctorate degrees in chemistry from Princeton University. With eminent science degrees in chemistry, or others having earned a Ph.D. in physical chemistry at Yale, Dr. Guiterrez' word "chaotic" (below) must be taken very seriously when he says in his YouTube Panel at PMWC earlier this year: "what is the state of Personalized Medicine regulation?" and he answers "the best they can say is "chaotic". (0:39)

"Chaotic" regulation of fractal genome?

The fact that the genome is fractal is paradigm-shift with escalating acceptance, including the President's Science Adviser putting it on Science cover, and lately heralded by some as prize-worthy.

How can static laws (that must provide predictability at least in a "piece-wise linear" manner as they are changed only in leaps and bounds from time-to-time) regulate fractal genome in a chaotic fashion in what is supposed to be a legal "steady state"?

Without getting unduly mathematical here chaos and fractals are collectively called as the branch of "nonlinear dynamics". "Non-linearity" without question results in a lack of trivially transparent predictability. For instance, scientifically astute scientists with degree in chemistry are familiar with the Belousov-Zhabotinsky reaction, or BZ reaction, which serves as a classical example of non-equilibrium thermodynamics, resulting in the establishment of a nonlinear chemical oscillator [1959-1964].

People from all walks of life are intimately familiar with another, much easier to understand example than the BZ reaction. It is the grossly nonlinear dynamics - of the weather! We know and understand that the weather is not totally, certainly not trivially predictable. Moreover, it is rather unyielding to regulatory efforts by government(s) - and since those often act in rivalry, they can further aggravate complexity. Weather reports fall into the science of meteorology. Let us remember Mandelbrot's fractals again "clouds are not spheres and even lightning does not go along a straight line". Talking about him, most everybody even with a remote familiarity with fractals would "visually recognize" a "Mandelbrot Set". However, a bit like the epoch-making "Heisenberg Principle of Uncertainty", one can either go for the exact mathematical description of the ideal infinite set comprised by the rather simple equation of Z=Z^2+C. Alternatively, one may wish to deal with a particular instance of it, where the number of iterations in the real world are always finite, but show individual diversity in both the numbers of iterations and specific fractal defects of the instance. The number of particular iterations could be too few (like the weather "partly cloudy"), or fuller ("mostly cloudy"). Though the fractal equation holds for any set (that does not contain "fractal defects"), even the best experts might find it impossible to call exactly how many iterations (along with the much more difficult question "what fractal defects") any particular instance of the same set is made of.

The 21st Century science of genomics is nascent. Its industrial applications (in health care, agriculture, energy, bio-defense etc) are both pioneering as well as sometimes quite understandably not public, and thus a proper understanding of modern genomics is largely absent in the society at large. Even the new axioms of a novel philosophy ("the genome is not your destiny", "ask what you can do for your genome") are at the dawn at a new era. Not totally unlike the paradigm-shift of quantum mechanics of nuclear physics that once already changed history and the world.

Since no single person may be entitled to arbitrate perhaps the greatest paradigm-shift of science/technology, ever, this realization may be the reason that Dr. Guiterrez at 37:47 of another of his public appearances called for a "panel" in cases of dispute, if any:

[Transcription is somewhat chaotic, but the concluding pledge seems very clear] "I guess the only thing I want to say is that even the guidance that one would put on companion diagnostics has flexibility, I don't think that you know there are forwarded by drug companies that would clearly increase the risks for them I don't deny that and the other thing is that I am not sure that I have seen too many uses where there is data to back them up that would I don't know I am not aware of any that the FDA would not allow and where is a dispute we are happy to take it to a panel"]

It may be a tall order at best to convene an effective panel of experts (particularly in the nonlinear dynamics of genome function) in the remaining days that can be counted on a badly injured single hand of the 15 workdays of "cease and desist". A hastily assembled Congressional Hearing, similar to a past "non-scientific regulation of science" , appears even more unlikely in a holiday panic-mode that might not necessarily be constructive or even a cost-effective use of tax dollars.

Thus, essentially there remain two likely alternatives - resulting in a most likely third outcome. One is a hyper-escalating and self-contradicting chaotic oscillation of "regulation"-attempts. Second, "a mountain of labor may give birth to a mouse". Whenever (it takes time) the US voters will realize that aspirin (and other NSAID-s) not only do not need prescription, but their mortality according to FDA's own study exceeds, by orders of magnitude, anything ever seen with "genetic tests" (where even the name, instead of "genomic" shows insufficient understanding), all the taxpayer-dollars spent on "chaotic regulation of fractal genome by scientifically self-contradicting legalisms" might be replaced by a very inexpensive label* (already on aspirin, NSAID-s, saccharin, let alone myriads of additives and supplements): "*This statement has not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure or prevent any disease".

Short of the obvious, a likely scenario is that the industry of 23andMe, a jewel of Silicon Valley, "Innovation of the year (2008)" could go down the river how another Silicon Valley jewel, Complete Genomics, became a presently a wholly owned subsidiary of BGI (with Chinese government subsidy in the billion dollar range).

Presently, China owns 80% of the World's human DNA sequences (with the USA and the rest of the World sharing the 20%), and the USA is at the brink of falling second to China in R&D . Thus, it is not inconceivable that International Airports (already famed Hong-Kong and Moscow, followed by Mexico City, Hyderabad, Bangalore, Dubai, Singapore, Delhi, Seoul, Tokyo, Toronto, Vancouver, Amsterdam, Zurich, Frankfurt, Berlin, Vienna, etc., etc.) could easily become enriched by saliva and other DNA sampling booths. US-based movers & shakers who invest locally and operate globally still have a chance to turn this around - or outright foreign parties can simply buy US patents (and thus monopoly-rights to the lucrative US markets) and laugh all the way to their bank. (China decided to shop a couple of $Trillions worth of USA property, intellectual or not).

This commenter hates to make it sound worse (but listening to a 2008 Google Tech Talk YouTube could have saved billions of dollars of lost valuation). The US company, should it be acquired with a customer-base already on record to have actually paid for genome analytics, in itself is a treasure. However, along with their already substantial primary data-set it is already sufficient for use -or abuse- far beyond the intended noble purposes of 23andMe. An M/A may extend analytics to be based on full DNA sequencing (where the announcement of freshly FDA-approved Illumina full sequencer surrounded with deafening silence, except a very notable exception).

Since homo sapiens actually has 2x23 plus a mitochondrial DNA, an M/A entity might be newly named as 47andWorld.

China and Russia already openly declared the strategic importance of genomics. Unless the publicly pledged "panel" is pre-empted by swift administrative action to defuse a danger to the (literally) vital interests of the USA, strategic world-balance will never be the same again. [Comment by Pellionisz, HolGenTech]

Gates Foundation to Double Donation to Fight AIDS

Washington Wire

December 2nd, 2013

[The richest person in the World by software looks pleased in the government office of the most able clinical genomics mover & shaker, when US R&D is about to fall second to China - AJP]

BETHESDA, Md. — Billionaire philanthropist Bill Gates said he plans to nearly double his foundation’s contribution to the Geneva-based Global Fund to Fight AIDS, Tuberculosis and Malaria, to as much as $500 million. Coupled with matching grants from other donors, Mr. Gates and his foundation’s officials said this could mean a total $1.6 billion contribution to the Global Fund.

The new money follows management troubles and a leveling off in funding for the Global Fund amid difficulties in the economies of many nations that contribute to it. Mr. Gates, who also spoke of worldwide health milestones that have been achieved by various groups including the Global Fund and his own foundation, made his remarks in a round-table discussion with news reporters preceding a lecture he gave at the National Institutes of Health.

The co-founder of Microsoft Corp., now a trustee and co-chair of the Bill & Melinda Gates Foundation, Mr. Gates said the commitment of various groups to fight diseases has had a measurable positive impact on lowered infant mortality and disease deaths around the world. Yet he said one impediment in that fight is the U.S. mandated budget cuts, known as the sequester, or sequestration.

The sequestration will force another $600 million reduction in federal funding for the NIH in January. The will cut the total $29.1 billion budget from 2013, which itself was slashed by the sequestration from a rate of nearly $32 billion a year ago. The sequestration was a mechanism created by congressional and White House negotiators to force strict cuts across the federal government when the two sides were unable to reach a more nuanced, negotiated budget level.

For the NIH, it means more limitations on what it can donate to medical research, both in the U.S. and abroad. The NIH currently funds about 40% of worldwide medical research and development outside the U.S., while the Gates Foundation pays for another 17%, according to Mr. Gates and NIH Director Francis Collins.

“Sequestration is a serious problem for the NIH in research,” said Mr. Gates. “It’s really a crisis where universities will have to look at their own infrastructure” and begin cutting back on their own research. Dr. Collins, in the roundtable discussion, agreed that sequestration “was the stupidest form of fiscal management.”

Mr. Gates said he is “deeply disappointed” in mandatory cuts in the NIH budget, since so many efforts against worldwide disease and malnutrition “are all long-term ventures,” the fruits of which won’t be seen for a while. Even so, he said, the Gates Foundation and other health groups have brought down the rate of infant death in recent decades from about 20 million annually to about 6.5 million now.

He said his goal is to lower that figure to below three million within 15 years, through vaccinating children worldwide and through efforts to reduce malaria, AIDS and rotavirus-caused diarrheal disease, among many others.

FDA warns Google-backed 23andMe to halt sales of genetic tests


Mon Nov 25, 2013 5:11pm EST

(Reuters) - The U.S. Food and Drug Administration has warned 23andMe, a company backed by Google Inc, to halt sales of its genetic tests because they have not received regulatory clearance.

23andMe, which was founded in 2006 by Anne Wojcicki, sells a $99 DNA test that the company says can detect a range of genetic variants and provide information about a person's health risks. Wojcicki recently separated from her husband, Sergey Brin, a co-founder of Google.

In a warning letter dated November 22 and released on Monday, the FDA said products that are designed to diagnose, mitigate or prevent disease are medical devices that require regulatory clearance or approval, "as FDA has explained to you on numerous occasions."

The privately held company, which is based in Mountain View, California, acknowledged receipt of the letter and said in a statement that "we recognize that we have not met the FDA's expectations regarding timeline and communication regarding our submission."

The FDA said some of the intended uses of the company's Saliva Collection Kit and Personal Genome Service (PGS) are particularly concerning, including risk assessments for certain cancers.

The agency said false positive tests for certain breast or ovarian cancers could lead a patient to undergo preventative surgery including mastectomy, intensive screening or other potentially risky procedures. A false negative could result in a failure to recognize and act on an actual risk.

23andMe will not be able to sell its tests for medical purposes until it submits the necessary data.

The FDA has not cleared any genetic tests that are offered directly to consumers.

Kathy Hudson, deputy director for science, outreach, and policy at the National Institutes of Health, said the FDA action clarifies its expectations for direct-to-consumer genetic testing. "NIH believes genetic information has a great potential to improve human health, but there need to be reliable, validated tests," she said.

One concern is that the results of genetics research, especially that linking a DNA variant to the risk of a particular disease, might apply to some ethnic groups but not to others. As a result, a consumer might think she has an elevated risk of some illness when in fact she does not.

On its website "the company quotes numbers for risk from published scientific papers, but you'd have to be pretty sophisticated to know that if the study was done on western Europeans it might not be relevant to you if you're Chinese," said geneticist Dr Jeff Murray of the University of Iowa and president of the American Society of Human Genetics (ASHG).

The FDA said in its letter that 23andMe had submitted applications in July and September of 2012 for several uses of its saliva test but had failed to address issues raised by the agency or to provide additional information requested. As a result, the FDA said, the applications "are considered withdrawn."

The company said its relationship with the FDA is "extremely important to us and we are committed to fully engaging with them to address their concerns."


Dr. David Agus, a professor of medicine and engineering at the University of Southern California and founder of Navigenics, one of the first personal-DNA testing companies, said the FDA's letter to "is not a death knell to personal DNA testing" but should be a wake-up call. "We have to be transparent with consumers about what sequencing their genome can and cannot reveal," he added.

Navigenics was acquired last year by Life Technologies Corp.

The FDA said it had been "diligently working" to help 23andMe comply with the law, and spent significant time evaluating the intended uses of the DNA-testing product. It said it provided detailed feedback to the company through more than 14 face-to-face and teleconference meetings, hundreds of email exchanges, and dozens of written communications.

"However, even after these many interactions with 23andMe, we still do not have any assurance that the firm has analytically or clinically validated the PGS for its intended uses," the FDA said.

While 23andMe may not have been communicating with the FDA, Wojcicki has been talking at length to the media. Earlier this month she told the New York Times that her company had mapped the genotypes of 475,000 people over the last five years and expected to "hit a million" in the first quarter of 2014.

In a recent article in Fast Company, Wojcicki said her ultimate goal was to sign up 25 million people. "Once you get 25 million people, there's just a huge power of what types of discoveries you can make," she said.

The company name refers to the 23 pairs of chromosomes that make up each individual's genome.

After years of trying to obtain from 23andMe the information it needs to ensure the tests are accurate, the FDA appears to have finally lost patience.

"I think this will certainly grab the attention of a lot of other companies out there," said Joseph McInerney, executive vice president of the ASHG.


[Comment by AJP - FDA (Food and Drug Administration) is admittedly a "US Government Branch". Nobody ever claimed that (any) "government" need to excel in science. In general, they do not. Simply because their forte is not there. Whenever an important-enough issue arises in history, they hire top scientists (see e.g. Oppenheimer, Teller, von Neumann hired by US government, or the UK government hired Information Theory expert Shannon, to successfully break the war-code of the enemy). Occasionally, when free enterprise calls for science expertise, they do their own hiring (e.g. Bill Joy was hired by KPCB). This columnist did both types of advisorship. Hired as a National Research Council Senior Associate, was assigned to NASA Ames Research Center (a US Government-branch) to cope with the Artificial Intelligence-to-Neural Net science paradigm-shift. On other occasions, hired by New York University Medical Center, successfully fought the USPTO to accomplish issue of Patent on the utility of the Biological Neural Net of the Cerebellum (now expired). Recently, in the role of advising Patent Lawyer Office, guided 2002 FractoGene patent application to issued patent 8,280,641 (in force till late March, 2026). In all above cases, science won over objections of bureaucrats that could have been technically legitimate, but were not necessarily scientifically valid (recalling an incident some years ago, a government-branch launched an attack on scientists, but unguided made the mistake of branding their own attack "not scientific"). In the opinion of this columnist, the art is how to make science what it is, the decisive issue. Take, for instance "weather advisory". Any native can hold a wet finger or two in the wind and "predict the weather". Scientists would, however, brush such "advisory" aside - by pointing out the apparent lack of science-depth. "Meteorology" can be seen as "wet finger", "prediction", "advisory", etc, etc, but none really matters, since ultimately meteorology *is* a science. Anybody ever legally challenged some "weather report"? Not only it looks silly, but modern "weather advisories" rely on massive computing power based on mighty algorithms, based on statistics and probability theory. In any court of law, the ultimate decisive factor is the power of expertise of science advisers that the respective parties employ. Those (on either side) who demonstrably can not properly round a real (non-integer) number would probably not measure up very well e.g. in statistics and probability theory of nonlinear dynamics that e.g. "genomics" (not some obsolete "genetics") truly calls for. - Pellionisz]

Mandelbrot, the Genius of Fractals, Born 89, Passed Away 3 Years Ago

[Comment by AJP] - In the past six weeks the World celebrated the birth and the death past 85 of "The Father of Fractals", Benoit Mandelbrot. His last video-interview below was made just 19 days before his passing (on October 14, 2010, now over three years ago, of what had started as pancreatic cancer). Perhaps the most touching tribute to his genius came from his own words (at 1:06). "As if a curtain opened" he said when he saw what so many others looked at before him - but others did not understand what was "obvious" to him. A true genius.

[see IBM Memorial Tribute article with YouTube here]

Having known Benoit, one finds perhaps the most moving moment of his last interview lurking behind what he did not say. Due to his most celebrated book "The Fractal Geometry of Nature" Mandelbrot was keenly aware that his advances would leap over Euclidean or even Riemannian geometries. His quest was to unify metrical and non-metrical spaces (in the sense of fractal Weyl laws). Such mathematical underpinning is universal in "Nature". He clearly understood that with time, the fractal/chaotic approach will transform the mathematical infrastructure of all natural sciences. Thus, when he did say about his "Eureka moment" at 1:06 "as if a curtain was lifted", one can not help being hard-hit by the next moment of the video. His joy visibly turned into a choked deep sadness. Was it his feeling, for years, of realization that the time of his "final curtain falling" might be so near? Was it the sorrow that he would have to leave entire fields that he already sowed to reaped by next generations?

One would think so.

Geometrization of biology, ever since Descartes [Fig.1. link to Springer] had always been the unfinished dream. See more recently Schroedinger (What is Life?, 1943) and Von Neumann (The Computer and the Brain 1955). Janos von Neumann is particularly relevant for me when remembering Mandelbrot, since von Neumann's book, by pointing out the lack of intrinsic mathematics of brain function was my intellectual imprinting. I never could meet von Neumann - but as Janos invited Mandelbrot to Princeton as his last PostDoc, Benoit and I amply exchanged our mutual recollection how von Neumann cardinally influenced our respective scientific careers.

Some may wonder if Mandelbrot was involved in geometrization of biology in a "hands-on" manner. Fact is (mentioned in his Memoirs), Mandelbrot was offered an early chance (and money) to lead mathematization of biology. However, he declined as he deemed that "biology was not ready". I deeply believe should von Neumann lived another couple of decades (easily, as he passed away by cancer 54 years young), my first paradigm-shift from AI to biological neural nets would have happened up to half a Century earlier. Likewise, should Mandelbrot have been in the position to penetrate biology, "Genomics turned Informatics, Leroy Hood (2002" would now be decades ahead of the present time. Indeed, Mandelbrot reached his first tenured position at age 75 as "Sterling Professor of Mathematics at Yale" by the year 2000 (when Ohno, with his misnomer of Junk DNA was still alive), only about the time the Human Genome Project readied Genomics to to Informatics.

Was Mandelbrot aware at all of my FractoGene approach (filed in 2002)? Certainly! See photos below taken at Stanford in the summer of 2004, where I handed over to Benoit a copy of my 1989 paper (on fractal Purkinje neuron, not one but two citations of Mandelbrot and personally dedicated to him). I also gave him a CD with some essentials (after the USPTO submission in 2002), with my "Eureka Figure" (original figure of my 2002, 2003, 2007 USPTO application) on the cover.

His question was not about science (particularly, since Francis Crick, with his misnomer of "Central Dogma" was still alive). We both knew that in fact he seeded it, as I properly cited Mandelbrot in my 1989 paper dedicated to him. On page 162 of his book "The Fractal Geometry of Nature" Mandelbrot mused: "NEURON BRANCHING. The Purkinje cells in mammalian cerebellum are practically flat, and their dendrites form a plane-filling maze... the notion that neurons are fractals remains conjectural". So went the two short paragraphs (with my side-note that the cerebellum was not a "mammalian" invention of Nature, as it appeared about 400 million years ago for the "vertebrate" fish of sharks). Mandelbrot's musing resulted in my 1989 paper "Neural Geometry: Towards a Fractal Model of Neurons"

During the 2004 Stanford conference we could see Mandelbrot study the 1989 paper and my FractoGene Hallmark:

Mandelbrot quickly sized up the utility of genomic and organismal fractals put into the light of "cause and effect" view. Thus, his dominant (telling) question was "who supports you?". From his Memoirs we learn that von Neumann supported him directly at Princeton Institute of Advanced Studies for a year, but Neumann also assigned top "movers & shakers" for later times to look after Mandelbrot. Since revolutions have an appetite to eat their children, Mandelbrot's "perilous" revolution was rescued by Princeton, IBM and finally by Yale.

Mandelbrot, like in most of his lectures, told the audience of his uncanny ability "just to look at most any rough picture, and tell its fractal dimension-number with a high degree of precision". Thus, I publicly asked in his plenary lecture only one question. "Prof. Mandelbrot, given your uncanny ability, what do you think the fractal dimension-number of the genome is?"

His answer was extremely telling, in both what he did not say, and what he did say.

He could have answered with a question "what are you talking about, who says the genome is fractal?" He did NOT say anything like that, since snippets of genomes had long been turned even into "fractal music" (Ohno, the originator of the misnomer "Junk DNA" [1972] and his wife pursued "fractal DNA music" as their ardent hobby). Fractal dimension-numbers had long been known to be distinctly different for the music of Mozart, Beethoven (etc), with Bartok's "absolute music" compositions being the closest to "fractal DNA sounds".

Mandelbrot's answer, however, was brutally honest: "I don't know".

He could have known and cited some numbers, and he was clearly and extremely interested in fractals in biology.

Mandelbrot just did not have the time & expertise, nor the support to pursue fractals of biology (especially genomics) as he knew the topic called for and deserved. In addition, (as the Eulogy in New York Times observed "For most of his career, Dr. Mandelbrot had a reputation as an outsider to the mathematical establishment") his life was already so full of "going against the grain as a maverick" that the last thing he needed was personal attacks by caricatures like a lonely moron (believe it or not, as of 2013, still clings to both of "flat Earth" misunderstandings of "Junk DNA" and "Central Dogma" contrary to overwhelming scientific evidence for going beyond the disarmingly naive nascence of genome informatics).

Dear Benoit, Farewell and R.I.P. "The curtain did not fall". It has just been opened for the "Prelude". We do not even know how many Acts and Scenes your Opera of Genomics will be composed of. [end of comment by AJP]

A Video Tribute to Benoît Mandelbrot

18 October 2010

On Thursday, mathematician Benoît Mandelbrot died of pancreatic cancer at age 85. Mandelbrot is most famous for coining the term "fractal," which he applied to fields as diverse as physics and finance. In 2007, an undergraduate at Cornell University named Pisut Wisessingcreated this video about the Mandelbrot set, a series of complex numbers that, when plotted, form an intricate fractal. The video is based on a song by Jonathan Coulton, who has penned other science-based music. (Warning: There is some explicit language.)

Watch Errol Morris’ New Documentary, About the Father of Fractals

Equation by brief Cartoon Rap

By Forrest Wickman

Errol Morris begins his new short documentary on Benoît Mandelbrot by asking a wonderfully straightforward question: “The fractal stuff, what was the origins of that?”

Mandelbrot, true to form, approaches this potentially complex question with an answer that is characteristically simple: When he looked at things that seemed extremely complicated to others, they seemed almost transparent to him.

Morris’ new documentary on Mandelbrot takes a similar approach, attempting to distill his work and story into something understandable even for those who don’t know his widely influential fractal geometry.

The short is presented as part of IBM’s “Big Brains, Small Films” series (Mandelbrot worked with IBM for 35 years), but it doesn’t feel like a commercial. It feels like a true Errol Morris film—complete with snazzy reenactments, a minimalist score, and cinematography that uses Morris’ signature Interrotron.

Mandelbrot died just 19 days after sitting down with Morris; IBM says this was his final interview. I’m glad that he got to explain his complex work, in simple terms, one last time.

Forrest Wickman is a Slate staff writer. Email him at


[Readers may wish to refresh their understanding of the utterly simple Z=Z^2+C explanation of mind-boggling "complexity" of The Mandelbrot Set. A lighter, entertainment-version in two and a half minutes is above on YouTube. An almost full hour NOVA Special of "fractals in their full glory" is below - AJP].

Equation by a 1-Hour NOVA Special of Fractals in Full Glory

Would he do it again?

Yes, and those who really know Dr. Pellionisz understand why he would.

Today is exactly the 11th anniversary (November 21, 2013) when a journalist Hal Plotkin wrote a very lucid essay to the electronic version (SF-Gate) of San Francisco Chronicle (see link for full text, with excerpts below)


"In a provisional patent application filed July 31 [2002], Pellionisz claims to have unlocked a key to the hidden role junk DNA plays in growth -- and in life itself.

Rather than being useless evolutionary debris, he says, the mysteriously repetitive but not identical strands of genetic material are in reality building instructions organized in a special type of pattern known as a fractal. It's this pattern of fractal instructions, he says, that tells genes what they must do in order to form living tissue, everything from the wings of a fly to the entire body of a full-grown human. [A large group led by Karolinska Institutet of Sweden revealed just days ago, that "pseudogenes" constituting 40-50% of "Junk" of human DNA are NOT "evolutionary debris" but actually many were found by sophisticated algorithms/computation to also "code for proteins", see entry earlier this week, November 17, 2013]

Another way to describe the idea: The genes we know about today, Pellionisz says, can be thought of as something similar to machines that make bricks (proteins, in the case of genes), with certain junk-DNA sections providing a blueprint for the different ways those proteins are assembled...

Hunt adds that most biologists simply don't know enough about fractals or the advanced math behind them to understand how they might apply to the field of genetic medicine.

"We need someone to tap us on the shoulder and explain it to us," he says. "But if it clicks as a tool, we would be more than happy to use it."

"Overall, we know very little about what is referred to as 'junk DNA,'" he adds. "But every year that goes by, there are more insights into the possible role they might play."

...Pellionisz has been working on understanding the possible linkages between math and physiology since his earliest days as a college student in Hungary, when he first decided to devote his life to understanding how the brain works. It's that pursuit that has helped lead him to his latest ideas, he says...

Experts generally agree that a breakthrough in figuring out the role junk DNA plays, if any, would represent a spectacular advance in our understanding about how DNA in general turns inanimate matter into living organisms. If that happens, humanity would take a giant leap toward gaining control of the machinery of life itself, which would open up a wild new frontier in medicine and science that could lead to everything from growing new organs designed for specific patients to preventing and curing any health- or age-related problems that have a genetic origin or component.

Pellionisz says his main goal is to set the stage for the next and even more promising generation of research into genetics. Given the fact that he may be the first person to assert a patent on intron fractal counting and analysis, it's also conceivable that Pellionisz could wind up with related commercial rights worth billions of dollars. If he's wrong, of course, any patent he might receive will be worthless. And even if he's right, he could have to contend with other inventors who may also have recently filed similar patent claims that, like his, have not yet been fully disclosed.

It could be years, even decades, before the dust settles and Pellionisz learns whether his patent application has any real merit, as well as whether someone else beat him to the punch with an earlier enforceable patent claim.


One has to admit at the outset, that the decade to win the issued patent was not exactly easy.

In accordance with Prof. Hunt's original comment that "most biologists simply don't know enough about fractals or the advanced math behind them to understand how they might apply to the field of genetic medicine". Fortunately, advised by patent lawyers that FractoGene patent submission would be examined by biologists, the sole inventor had the choice of either put in extremely narrow, "easy to understand" claims (that would severely limit its potentially enormous scope) - or follow a much more sophisticated patent strategy towards the broadest claims, for which a finessed teaching was necessary. Here is Claim 1 (of 21) and some non-obvious comments on the finesse.

CLAIM 1 (of 21, the broadest claim is abbreviated below by omitting "one or more" strings and emphasis added):

"A method to analyze and interpret information inherent in hereditary material of organisms in terms of fractal sets, in relation with resulting fractal structures and fractal functions of said organisms, such that said fractal sets are defined as a superposition over at least two iterations of a fractal template"

How could Dr. Pellionisz successfully obtain the legal right of monopoly controlled by such an enormously broad claim (even with a decade of waiting and absorbing a couple of $ Millions in costs & lost revenue "out of pocket")?

First, look at the (overlooked) expression in the Claim "in relation with". Fractal properties of either organisms (trees, lungs, etc) or those of the DNA (even in the form of "fractal DNA music") have been looked at in the prior art. Many-many scientists looked at the apparent fractality in various organisms, in various genomes - but they missed to see the cause-and-effect relationship - resulting in colossal utility. "In relation with" was brought into the teaching by invoking not only the mathematical arsenal of fractals, but also of statistics and probability theory. All in a way that is digestible for a patent examiner who is likely to be a biologist!

Fortunately, the legal mechanism of Paragraph 2163.07(b) could be invoked "Incorporation by Reference". According to this piece of law, see "Instead of repeating some information contained in another document, an application may attempt to incorporate the content of another document or part thereof by reference to the document in the text of the specification. The information incorporated is as much a part of the application as filed as if the text was repeated in the application, and should be treated as part of the text of the application as filed."

Utilization of this legal venue led to a highly mathematical teaching (with attachments "incorporated by reference" amounting to some 750 pages of advanced mathematics). It is possible that for a full decade the examiner never had a chance to read it in full, as in the last legal round USPTO required submission of all "methods" (with some of the papers/books not easily found and certainly could not be just "clicked").

In the same week when ENCODE 2012 avalanched biologists, Notification of Issue of FractoGene patent arrived. The "fractal approach" is now in the "prize-worthy box" instead of the bin for formerly "lucid heresy" items.

Intellectual Property experts know, that the Inventor of "Best Methods" described in the Application (with last CiP of 2007) had by now 6 additional years of "Improving Best Methods". These improvements are not disclosed in the now public patent - but as is customary, held as "Trade Secrets". Thus, while the patent is in force till late March of 2026, "Trade Secrets never expire".

Given the scope of Industrialization of Genomics, enforcement of the patent will be greatly assisted by those global IT/Health companies that are already committed to this "next big thing" (SAMSUNG for over 2 years eyes the market of US hospitals and SIEMENS, PHILIPS, SONY etc are not very far behind). The lists of already committed or "getting ready" USA-based global IT/Chip/Health companies need not (and now legally can not) be belabored. The market is segmented to "fierce competitors" to exclusively auction-out selective arch-rivals. Segments are compute-platforms, geographical regions, targeted diseases (for diagnostic and therapeutic purposes), hospital systems, and other rivals.

With Thanksgiving coming up, time is for R&R&R, with "Reflecting" perhaps the most unusual. The inventor and sole patent holder (with the next generation already spruced) already enjoyed a few nice days of contemplation.

Yes, even against all odds experienced (an unusual decade, admittedly peppered with some rather astonishing features), he would do it again. "It is in the genome" one might say. Though, as we learnt the other day, facial etc. features that are individual to all are NOT in the genes. Creativity, too, seems to lurk in the (formerly) intergenic regions...

Junk Genes Of Protein Codes Might Be Helpful To Understand Cancer

Nov 18th, 2013

Researchers have revealed that approximately one hundred human gene regions, also called as pseudo genes, which code the proteins might have a relationship with cancer.

Generally, only 1.5% of DNA or human genome has gene with protein codes. Among the other DNAs, few sequences are used to regulate the ability of the genes to produce proteins. Rest of the DNA are used to maintain the production of genes and regulate the proteins but the bulk DNA is found to have no purpose and is termed often as the junk DNA.

These junk DNA possesses pseudo genes that were regarded as genes with no functional purpose. Such genes are believed to be the remains of genes, which have lost their ability to function during the process of evolution.

Researchers have exhibited now that the novel method of proteogenomics makes it possible to hunt the protein code genes out of the 98.5%, which is remaining. This is something that has been an impossible task until now as it is not possible to proceed with. The research also indicates that some pseudo genes have the ability to produce proteins, which would mean that they have a perfect function.

Janne Lehtio, Asst. professor, lead author of the study, added that there is enough evidence for the presence for over 100 regions with new protein codes present in the human genome. Similar study results were also derived from the body cells found in mice. The next objective on the agenda of the researcher is to find out whether these junkyard genes in human genome play a vital role in finding cancer or other such medical conditions.

Dr. Lethio added that their challenges in the study regarding the old theory, which stated that there was no code for pseudo genes with respect to proteins, asserted that their latest method paves way to annotation of genome that are protein based in organisms that have complex genomes. This might lead to the discovery of novel protein codes from genes not only among the human beings but also among all species that have a DNA sequence.

[In the "Old School", there was no such thing as "Junk Gene". Parts of DNA were thought to be either "Genes" - the rest was labeled "Junk" by Ohno (1972, see facsimile of the original here , pseudogenes specifically junked "for the importance of doing nothing"). The Old School's Junk (DNA) Is The New School's Treasure. Karolinska-led paper literally blows both "Junk" & "Gene" categories into pieces (elsewhere a new word of "mosaic" is on its way - towards FractoGene). Though the Nature Methods paper mentions "cancer" by reference (once, to Kalyana-Sundaram, 2012), one finds among the sponsors both the Swedish Cancer Society and Stockholm's Cancer Society. Cancer will not be diagnosed, treated nor cured by any "gene/whatever re-definition". "Cancer is a digital disease and will receive a digital cure" - said one of the most mathematics-savvy genomist (Dave Haussler). When the axiom was brutally violated that "the atom was the smallest particle of any element, that could not split", for a while scientists went on auto-pilot with mesmerized diligence of "old school chemistry" - when the atom did split. Physicists, on the other hand, started to build quantum-theory to (literally) arm mankind for the new challenge of the inevitably upcoming "nuclear age". Fractal mathematics is already mentioned in journalism as prize-worthy in the quest against cancer . Funds are important to deploy software-enabling theory going - as disarmingly naive old-school theories finally need to be junked (Mattick). Assuming, or course, that we decide (along with IBM, Dell, Amazon, Google, Apple, Samsung, etc) to change the steady course of zillions suffering misearble deaths, including "Steve Jobs" potentially empowered to bring in the big guns of IT industries in time - AJP]

HolGenTech Board of Advisers News - in a Perspective

The “Internet Boom” (1984-2000) repeats itself in “Genome IT Boom” (in R&D stage 2000-2012 and now in industrial stage 2013-2026). A few orders of magnitude bigger and bolder than anything we have seen.

With the present consolidation of the Industrialization of Genomics the era of fireworks of conflicts of interest dawned on us. Triggered by the Calico, Google employee Zoltan Egyed was forced to resign by November 7, 2013 from Board of HolGenTech to negotiate FractoGene IP “at arms length” with major IT that are already committed to clinical genome analytics (see "Board" on HolGenTech website).

On one hand, firms already engaged in Clinical Genome Informatics like Google/Apple and IBM/Intel/Microsoft/Amazon/Dell/Xilinx/NVIDIA etc. attempt to prevail in a “sustained mode” inching through the most turbulent paradigm-shift in history, perhaps ever. Sector-selective exclusive IP-licence of FractoGene can be a safety-net for a protected tightrope-walking. On the other hand, ex-Google, ex-Facebook etc. entrepreneurs/investors are likely to hyper-escalate in a “disruptive mode” (in the manner formerly seen and proven by Bill Gates, Steve Jobs - now similar to the unique opportunities that Yuri Milner grabbed).

Dr. Egyed (Googler) introduces Dr. Pellionisz' Google Tech Talk YouTube 2008 (Is IT ready for the Dreaded DNA Data Deluge?)

Dr. Pellionisz' Google Tech Talk YouTube 2008 projects that the genome analytics "bottleneck" is NOT IT (technology), but IT (theory; a suitable algorithmic approach that e.g. was the foundation of Google...)

An example how to steer clear of “conflict of interest” and “negotiate at arms length”, Zoltan Egyed was already a Google employee in 2008, when he introduced Google Tech Talk “Is IT Ready for the Dreaded DNA Data Deluge” a mere five years ago. One may wish to re-view the presentation, how it warned against a mega-billion dollar failure of sequencing unmatched with analytics, etc, etc. Later, Dr. Egyed became a Board of Adviser member to HolGenTech, Inc. founded by Dr. Pellionisz. In 2009 Churchill Club panel by Dr. Pellionisz, Dr. Nikolich quoted [at 1:04:00] “What if Microsoft would acquire a pharma company or Google will build or acquire an IT-led pharma?”. By now Google already stepped beyond their discontinued “Google Health” by starting Calico (with Apple and even Roche/Genentech built-in ties)! Microsoft made early exploration by Paul Allen a decade ago (Regulome) and the MS “Health Vault” still seems to be alive. For a healthy survival of challenged Microsoft, some fundamental decision is due for Genome Informatics.

Now with Calico of Google/Apple (in itself an interesting business and intellectual property structure, especially with Roche/Genentech), Dr. Egyed as still a Google employee resigned of his HolGenTech Board of Advisers membership to avoid any “inside-deal”.

Samsung, Sony, Tata, Siemens, Philips, BGI/Complete Genomics round up the global horse-race.

FractoGene US patent 8,280,641 for fractal diagnosis and therapy in genomics was filed in 2002 (see a most lucid early write-up by Hal Plotkin in San Francisco Chronicle's SF Gate) A rather profound Claim 1 (of 21 of FractoGene patent) is "A method to analyze and interpret information inherent in hereditary material of one or more organisms in terms of one or more fractal sets, in relation with one or more resulting fractal structures and one or more fractal functions of said one or more organisms, such that said one or more fractal sets are defined as a superposition over at least two iterations of a fractal template"

Patent is in force till late March, 2026

The Genome Is Fractal - Loops Of Minimal Distances Are Key To "Recursive Genome Function", Enabling "Distance Function"

[In a Science Cover article in 2009 the Hilbert-fractal was invoked to explain the ultra-tight, knot-free folding of the DNA-strand, referring to pioneering work by Alexander Grosberg decades earlier . Experimental evidence for "fractal folding" was provided in the 2009 Science paper by the Hi-C method , revealing that the fractal folding brings into minimal distance of each and every part of the DNA sequence, parts that would be "a great distance apart" if one would inch along the 2 yard long linear thread. While not much attention was given why such "minimal distance" is functionally advantageous, Pellionisz pointed out in this website that his 2008 "The Principle of Recursive Genome Function" called for minimal distance loops to make recursive (fractal iteration) function effective. Very recently a couple of landmark papers provided evidence that "distance function" plays an essential role in genome regulation , essentially providing new dimensions to the classical notion originating from Jacobs and Monod (1961, Nobel in 1965) that "repressors" and "promoters" are linearly adjacent to particular gene(s). It might take a while to sink in that DNA function has long been misunderstood, based on the (mistaken) impression that the (human) 3.1 Bn A,C,T,G-s, just because they are stored and duplicated as two intertwined linear strands of the double helix - "must" also function sequentially.

No longer true. Novel experimental evidence is mounting that the DNA functions as a massively parallel processor, where even "linearly distant" sequences are brought into functional proximity by the utterly clever "fractal folding". Core authors of the 2009 Science paper (with additional members to the team) came forward now in 2013 with a major publication also in Science (see a journalist's write-up below, with link to the Science paper), clinching that loops (the essential conduits of recursion) "are key to fractal globule". Pellionisz' "FractoGene", since 2002 secured the utility of "fractal DNA governs fractal growth". To get a sense of the algorithmic software-enabling approach, please keep in mind that even the simplest and best known fractal (Mandelbrot set) is no more but no less than a "recursion of parallel elements". In the Mandelbrot set, every new state generated by the previous one via the utterly simple Z=Z^2+C repeat. However, every "Z" is in itself a parallel entity; a complex number (a composite of two elements, one real and one imaginary). Quarternions, as their name dictates, are composites of not two, but of four elements (the recursion resulting in "Mandelbulb fractal"). FractoGene is now in clinical applications against cancer (since "fractal defects" were found by essentially the same Boston core-group, see their Proof of Concept result that the "fractal globule" is compromised). Dozens of more PoC experimental studies are cited in Hyderabad Proceedings, 2012. In the era of "Industrialization of Genomics", however, "best methods" (since the last CIP in 2007 of FractoGene) can not be freely disclosed. However, the IP can be licensed. - Dr. Pellionisz, reach by holgentech_at_gmail_dot_com]


Scientists find that loops of DNA are key to tightly packing [fractal] genetic material for cell division

CAMBRIDGE, Mass. - Scientists first discovered chromosomes in the late 1800s, after the light microscope was invented. Using these microscopes, biologist Walter Flemming observed many tightly wound, elongated structures in cell nuclei. Later, it was found that chromosomes are made from DNA, the cell’s genetic material.

Since then, scientists have proposed many possible ways that DNA molecules might fold into 3-D condensed chromosomes. Now, researchers at MIT and the University of Massachusetts Medical School have obtained novel data on the 3-D organization of condensed human chromosomes and built the first comprehensive model of such chromosomes.

In this model, DNA forms loops that emanate from a flexible scaffold; the loops are tightly compressed along the scaffold. “This is a very efficient way of packing DNA material,” says Leonid Mirny, an associate professor of health sciences and technology and physics at MIT and a senior author of a paper describing the findings in the Nov. 7 online edition of Science. [See their Science paper, elaborating on fractal properties that enable "distance action" through loops here - AJP]

This condensed state, seen only when cells are dividing, allows cells to neatly separate and distribute their chromosomes so that each daughter cell receives the full complement of genetic material. At all other times, the chromosomes are more loosely organized inside the cell nucleus.

Job Dekker, a professor of biochemistry and molecular pharmacology at UMass, is also a senior author of the paper. Lead authors are MIT graduate student Maxim Imakaev, Harvard University graduate student Geoffrey Fudenberg, and UMass postdoc Natalia Naumova. Other authors are UMass researcher Ye Zhan and UMass bioinformatician Bryan Lajoie.

Layers of structure

Chromosomes are complex molecules with several levels of organization, allowing cells to cram 2 meters of DNA into a nucleus that is only one hundredth of a millimeter in diameter. Long strands of DNA wind around proteins called histones, giving rise to a “beads on a string” structure. Several models have been proposed to explain how those strands of millions of beads are arranged inside tightly packed chromosomes.

“There is no shortage of models of how DNA is folded inside a chromosome,” says Mirny, who is a member of MIT’s Institute for Medical Engineering and Sciences. “Every high-school biology textbook has a drawing of chromosomes folding. If you look at these drawings you might get the impression that the problem has been solved, but if you look carefully you see that all these drawings all very different.”

To help determine which model is correct, the researchers used a technology developed in Dekker’s lab called Hi-C, which performs genomewide analysis of the proximity of genomic regions. This reveals the frequency of interaction for every pair of regions in the entire genome.

The challenge, however, lies in generating an overall chromosome structure based on Hi-C data. “Given a three-dimensional structure, it is straightforward to find all contacts; however, reconstructing three-dimensional structures from contact frequencies is much more difficult,” Imakaev says.

In 2009, researchers including Imakaev, Mirny, and Dekker used Hi-C to demonstrate that during most of a cell’s life, when it is not dividing, DNA is organized as a fractal globule, in which DNA is not tangled or knotted.

Hi-C also showed that regions with more active genes tend to cluster together in easily accessible compartments, and unused regions form more densely packed clusters. The organization of each chromosome varies among cell types, because every type of cell uses different sets of genes to carry out its function. This means that each chromosome acquires a specific 3-D organization depending on which genes a cell is using.

Chromosomes during cell division

In the new paper, the researchers found that as cells begin to divide, chromosomes are completely reorganized. First, all chromosome-specific and cell type-specific patterns of organization, which are necessary for gene regulation, disappear. Instead, all chromosomes are folded in a similar way as cells begin to undergo cell division, or mitosis. However, the chromosomes do not form the exact same structure every time they condense.

“Unlike proteins, which fold into very defined structures, the chromosomes form a completely different condensed object every time,” Fudenberg says. “It appears similar macroscopically but the individual regions of the genome can be folded in very different ways in different cells.

The Hi-C technique “provides a modern day molecular microscope, with the power to see inside of these bodies and elucidate their principles of organization,” wrote Nancy Kleckner, a professor of molecular and cellular biology at Harvard University, in a perspective article accompanying the Science paper. The researchers “combine chromosome conformation capture with polymer physics simulations to provide a new, yet satisfyingly familiar, view,” she wrote.

The researchers believe that two stages are required to achieve the loop-on-a-scaffold structure: First, the chromatin forms loops — each of which contains about 80,000 to 120,000 DNA base pairs - radiating out from a scaffold made of DNA and some proteins. Then, the chromosome compresses itself along its central axis, where the scaffold is located.

While molecular details of the second stage remain mysterious, scientists have a good guess for what might be responsible for the first stage of chromosome folding: A team at Northwestern University recently proposed that proteins called condensins drive chromosome condensation by latching on to the DNA and extruding loops. To test this hypothesis in greater detail, the MIT team is now collaborating with these researchers.

Beyond characterizing condensed chromosomes, this study also opens the door for future work to understand mechanisms of chromosome condensation, cell memory, and epigenetic cell reprogramming.

The research was funded by the National Cancer Institute, the National Human Genome Research Institute, the Human Frontier Science Program, and the W.M. Keck Foundation.

"Junk DNA" as "Doing Nothing" became a Laughing Matter - Fractal Recursive Iteration is the Prevailing Paradigm of Genome Regulation!

[Composite of the Guardian-coverage illustration at right (titles added), rendering "Junk DNA" (as "doing nothing") literally a "laughing matter". Junk DNA was defined by Ohno in 1972 as DNA "for the importance of doing nothing", see page 367 of facsimile reproduced in its entirety. The "about face" ideology-spinners, see YouTube "Encode 2013" and leftover bloggers now try to substitute "Junk" by "Unknown function". The higher is their "declared percentage of ignorance", the more culpable and legally vulnerable is their negligent "science teaching". Diagram on the left is the classic cover-page of a "fractal face" by Michael Barnsley (original edition in 1988). "FractoGene" (The utility of fractal DNA growing fractal organisms) priority-date is 2002, now issued US patent) is a software-enabling algorithmic approach to fractal recursive genome function, see peer-revieed publications, PubMed 2006, 2008). - Pellionisz, contact HolGenTech_at_gmail_dot_com]

On October 25, 2013 a Science paper appeared by 20 authors from Lawrence-Berkeley (USA), San Diego (USA), Edinburgh (UK) and Calgary (Canada), with lead authors Catia Attanasio and Axel Visel. The science-focus of experimental findings is " Fine Tuning of Craniofacial Morphology by Distant-Acting Enhancers".

Readers with strong science background will find that the key-word of their title is "DISTANT-acting enhancers". Promoters, suppressors etc. have long been found in non-coding DNA since Jacobs and Monod (1961, Nobel in 1965). However, "distant-action" in the fractal DNA (see FractoGene software enabling genome regulation theory since 2002) has been increasingly in the forefront since e.g. the Hilbert-fractal minimizes functional distances of linearly remote part of the DNA-strand (see Pellionisz, 2012, interpretation of "copy number alterations" clogging transparency and thus becoming "fractal defects", already linked to cancer, autism, auto-immune diseases, schizophrenia etc.).

The impact of the paper on general readership is substantial since the title refers to "craniofacial morphology". While the science was done in mice, it is known since 2002 that the mere 20,000 or so "genes" of both humans and mice are 98% homologs and genome regulation in both multicellular vertebrate mammals is likely to be based on shared functional principles.

In case of homo sapiens, "craniofacial morphology" is otherwise known as "your face".

The "in your face" results of genome regulation, therefore, made the infamous "Junk DNA" misnomer (specifically arguing "the importance of doing nothing") literally a laughing matter; see press coverage by Lawrence Berkeley (Lynn Yarris; "What is it about your face?") and in the Guardian (Alok Jha; "Faces are sculpted by 'junk DNA'"). The wave of publicity reached even Huffington Post [and some 38 other media since the newsbreak].

What is it about your face? [Press release by Lawrence Berkeley, Lynn Yarris]

The human face is as unique as a fingerprint, no one else looks exactly like you. But what is it that makes facial morphology so distinct? Certainly genetics play a major role as evident in the similarities between parents and their children, but what is it in our DNA that fine-tunes the genetics so that siblings – especially identical twins – resemble one another but look different from unrelated individuals? A new study by researchers at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) has now shown that gene enhancers – regulatory sequences of DNA that act to turn-on or amplify the expression of a specific gene – are major players in craniofacial development. Berkeley Lab researchers identified distant-acting transcriptional enhancers in the developing craniofacial complex and studied them in detail in transgenic mice.

Faces are sculpted by 'junk DNA' [Press coverage by Guardian, Alok Jha]

Scientists have identified thousands of regions in the genome that control the activity of genes for facial features 'Transcriptional enhancers' switch genes on or off in different parts of the face... Researchers have started to figure out how DNA fine-tunes faces. In experiments on mice, they have identified thousands of regions in the genome that act like dimmer switches for the many genes that code for facial features, such as the shape of the skull or size of the nose.

Specific mutations in genes are already known to cause conditions such as cleft lips or palates. But in the latest study, a team of researchers led by Axel Visel of the Lawrence Berkeley National Laboratory in Berkeley, California, wanted to find out how variations seen across the normal range of faces are controlled.

Though everybody's face is unique, the actual differences are relatively subtle. What distinguishes us is the exact size and position of things like the nose, forehead or lips. Scientists know that our DNA contains instructions on how to build our faces, but until now they have not known exactly how it accomplishes this.

Visel's team was particularly interested in the portion of the genome that does not encode for proteins – until recently nicknamed "junk" DNA – but which comprises around 98% of our genomes. In experiments using embryonic tissue from mice, where the structures that make up the face are in active development, Visel's team identified more than 4,300 regions of the genome that regulate the behaviour of the specific genes that code for facial features.

The results of the analysis are published on Thursday in Science.

These "transcriptional enhancers" tweak the function of hundreds of genes involved in building a face. Some of them switch genes on or off in different parts of the face, others work together to create, for example, the different proportions of a skull, the length of the nose or how much bone there is around the eyes.

"If you think about face development, a gene that is important for both development of the nose and the mouth might have two different enhancers and one of them activates the gene in the nose and the other just in the mouth," said Visel.

"Certainly, one evolutionary advantage that is associated with this is that you can now change the sequence of the nose or mouth enhancers and, independently, affect the activity of the gene in just one structure or the other. It may be a way a way that nature has evolved in which you can fine-tune the expression of genes in complex ways without having to mess with the gene itself. If you destroy the protein itself that usually has much more severe consequences."

In further experiments to test their findings, the scientists genetically engineered mice to lack three of the enhancers they had identified. They then used CT (computed tomography) scanning to build 3D images of the resulting mouse skulls at the age of eight weeks.

Compared with normal mice, the skulls of the modified mice had microscopic, but consistent, changes in the length and width of the faces, as expected. Importantly, all of the modified mice only showed subtle changes in their faces, and there were no serious harmful results such as cleft lips or palates.

Though the work was done in mice, Visel said that the lessons transfer across to humans very well. "When you look at the anatomy and development of the mouse versus the human, we find that the faces are actually very similar. Both are mammals and they have, essentially, all the same major bones and structures in their skulls, they just have a somewhat different shape in the mouse. The same genes that are important for mouse face development are important in humans."

Visel said that the primary use of this information, beyond basic genetic knowledge, would be as part of a diagnostic tool, for clinicians who might be able to advise parents if they are likely to pass on particular mutations to their children.

Peter Hammond, a professor of computational biology at University College London's Institute of Child Health, who researches genetic effects on facial development, said understanding how faces develop can be important for health.

"There are many genetic conditions where the face is a first clue to diagnosis, and even though the facial differences are not necessarily severe the condition may involve significant intellectual impairment or adverse behavioural traits, as well as many other effects," he said. "Diagnosis is important for parents as it reduces the stress of not knowing what is wrong, but also can be important for prognosis."

The technology to go beyond diagnosis and make precise corrections of the genome does not yet exist and, even if it did, it is not clear that changing genes or enhancers to create "designer" faces would be worthwhile. "I don't think it would be desirable to even attempt that. It's certainly not something that motivates me to work on this," said Visel. "And I don't think anyone working in this field would seriously view this as a possible motivation."

["The Face of Former Junk DNA" is important not only to bring the heretofore "faceless" issue of misnomer "Junk DNA" to immediate grasp of everyone. It is also cardinal as it focuses on "genome regulation" as a "distance-function", and the paper specifically mentions (though does not elaborate how) "Copy Number Variations". "CNV"-s ("repeats" with as many "definitions" as many genomists you ask) are the new and trendy candidates of physiologically connecting (or pathologically clogging e.g. as independent Proof of Concept experiments have proven in case of cancers) distant parts of the genome according to the Principle of Recursive Genome Function. The paper, therefore, "is not just another pretty face" but directs attention to causes that are likely to lurk behind e.g. cancers. "Junk DNA" became a laughing matter for survivors. However, hundreds of millions do not laugh any more. Countless zillions died of miserable deaths of e.g. cancers over the many decades while first a scientifically mistaken, later a conveniently ignorant attitude, and in its terminal phase an ideology-warfare (of "belief-systems") stood in the way of strict (mathematical) science-progress. As explained both in peer-reviewed paper (Pubmed, full material free) and widely disseminated in Google Tech Talk YouTube (both in 2008), "Junk DNA" and "Central Dogma" erroneous axioms, in a dove-tailing manner, blocked the take-off of "Principle of Recursive Genome Function"; towards fractal iteration of growth. Lately, while fractals are quite warmly welcome, obstinate detraction and its dishonest record is likely to linger - but perhaps not in taxpayer-supported mode. - AJP]

Improving genome understanding

The cost and accuracy of genome sequencing have improved dramatically. George Church asks why so few people are opting to inspect their genome.

Nature, 09 October 2013 (Corrected: 09 October 2013 [According to Nature Search, the original title was "Genomics is Mired in Misunderstanding"]

Readers of Nature, we can assume, are bright and insatiably curious. So why have so few obtained and interpreted their own genome sequence? We should avoid being judgemental of people who practise genomic modesty or who choose not to act on genome information, but we should also ask if we are providing adequate and equal access to education about the benefits and risks of genome information.

For 7 years I led one of the teams registered to compete for the US$10-million Archon Genomics X Prize, and I was naturally disappointed by the abrupt cancellation of the competition in August. However, the confusion surrounding the X Prize does provide an occasion to reflect on the problems and misunderstandings in genomics. The first is that genomics is seen as expensive. In fact, sequencing costs have plummeted — from $2.7 billion for the first human genome in 2003 down to $1,000 today. That’s not much more than the cost of a decent laptop, and much less than a car. However, people are reluctant to pay to have their genome sequenced — many feel that health care should be provided for free by insurance or the government and, indeed, this is our not-that-distant goal, as there are many in our community who would not benefit from genome information if it were not free. However, for those today who can afford a genome sequence, we would argue that, overall, the cost of sequencing is expected to be recovered over a lifetime through the avoidance of unnecessary diagnostics and therapeutics and time spent in waiting rooms and hospitals.

Perhaps too many think that genomics is inaccurate. When it announced the cancellation, the X Prize Foundation claimed that “no company is sequencing whole genomes to the accuracy the contest required”. Aside from the pre-judgemental weirdness, is this statement true? Haplotype phasing quality — a measure of accuracy — has improved from 350 kilobases in 2007 to 2,463 kilobases in 2013, and point errors have improved from 1 in 100,000 to 1 in 10 million — both well beyond the X Prize goals. Genetic analyses of tough tandem repeats are now common diagnostically.

Are the results uninterpretable? Even if we place the As, Cs, Gs and Ts in the right order, how does this help? Genome-wide association studies (GWAS) and studies of twins can give the impression that predicting traits from genomic sequence is a haphazard science. But since 1991 the number of highly predictive gene tests has risen from two to 3,000. Even ‘complex’ traits include components that can be identified and applied clinically to individuals who are not classed to be directly at risk. For example, height and diabetes GWAS have shown that a vast number of common variants have small effects, but the alternative of seeking rare variants reveals large effects by altering levels of growth hormone for height and insulin for diabetes. These hormones are effective therapies even for individuals who are not mutant in them. Too often the messy results of GWAS and twin studies are down to poor selection of subjects and neglect of confounding environmental factors.

Even if they are interpretable, are the results useful? Yes! Even if there is no cure for the genetic conditions identified, there are effective preconception and prenatal options that could have an impact on the family. For example, Ashkenazi communities already use genetic screening to make lists of suitable marital partners early in life to avoid their offspring developing painful Tay–Sachs disease and more than 20 similarly devastating diseases (which are not restricted to their community, by the way). Although we are tempted to restrict genomics to those with ethnic or family risks, the fact is that we are all at risk. Even the possibility of finding markers for one treatable disease (such as a cancer or cardiomyopathy) could, for some, be a sufficient reason to check one’s genome.

Perhaps most provocatively, some critics assert that genomics could be harmful. The US Genetic Information Nondiscrimination Act (GINA) prevents discrimination based on health insurance and employment; however, there is not a GINA in every country, and it doesn’t cover the military, life insurance or person-to-person discrimination. But the question is: do the overall benefits of genomics exceed the risks? Do the benefits of driving trump the one-and-a-quarter million traffic-related deaths per year? A growing number of bioethicists and researchers are worried that typical consenting practices do not inform patients of the likelihood of data escape and re-identification. Certainly, conventional consents served to protect the researchers, not the volunteers. However, the huge numbers of volunteers who are willing to share their genetic data make this a moot point. Why insist on recruiting those — and setting policy around those — who would be upset if their data escapes?

It is important for those of us at the sharp end of work on genomics to work equally hard at conversations with the public. We already share our (very revealing) faces, voices and opinions. And, as we share more of our genetics and as we develop genomic progress into precision medicine, researchers and the public alike need frank assessments of all of these tests and treatments. We need the Genomics X Prize more than ever.

Nature 502, 143 (10 October 2013) doi:10.1038/502143a

[Excerpts from Comments]

Andras Pellionisz

Prof. Church answers with the title of his lucid assessment what exactly is required to streamline genomics for clinical use. The pendulum of interpretation must swing first from "knowledge" to "understanding". Nobels have just been dished out in Physics and Chemistry for predictive and experimentally testable theories and computer modeling to cope with data-sets incomprehensible for the un-aided human brain. However, software-enabling algorithmic understanding of recursive genome function is still at a pioneering stage.

A handful of cynics can not let go their "old school", ex-cathedra condemning the majority of 6.2 Bn DNA-bases "for the purpose of doing nothing" [So conceited, full of themselves -mostly junk- that bypass even a friendly guesture for a graceful way out]. Perhaps people easily overlook such negligence today, but attitudes will change dramatically as genome interpretation will allow us to differentiate between successful treatment and persistent or aggravated illness. Old school mentality is in fact responsible for millions of unnecessary deaths. Computer-aided genome interpretation could have made a difference for Steve Jobs, the high-tech genius. Tragically, he died of cancer at the peak of his life surrounded by his Silicon Valley IT company. Jobs left behind the most valued company in the world (Apple), while running out of time to develop advanced genome interpretation via computers and information technology!

Ironically, most of us would not consider checking into a hotel where there is no Wi-Fi. If we can’t connect our iPhone, iPad, or "iEverything", we turn away from such antiquated businesses. Shouldn't we have the same attitude toward genome based healthcare? Shouldn't we demand treatments such as precision chemotherapy based on our individual genomes?

So when is the daybreak of genomics for the masses? When the tide of patients and health-conscious movers & shakers, before checking into any hospital, will demand an answer to the vital question "What Can You Do For MY Genome"? Once the trend is sparked, masses will follow and insist on cancer therapy which is based on genome sequencing and computer-aided interpretation!

All Bets Are Off: Silicon Valley Goes For IT Google-Style!

Can Google Calico Conquer Death?

Time Magazine Cover Issue

We all know that Google has created many a miracle — but, can it conquer death?

Today, the company announced Calico, a new health-and-wellness initiative that aims to put the company's ingenuity into its biggest challenge yet: conquering cancer and, ultimately, death. Google CEO Larry Page said in a statement: "Illness and aging affect all our families. With some longer term, moon-shot thinking around health care and biotechnology, I believe we can improve millions of lives. It’s impossible to imagine anyone better than Art — one of the leading scientists, entrepreneurs, and CEOs of our generation — to take this new venture forward.” Apple chairman Arthur D. Levinson, who will head up the organization, added that he's devoted a lot of energy toward advancements in tech and science designed to make life better (and longer), and is excited about Calico's prospects.

A corresponding TIME Calico cover story goes much deeper, with Google CEO Larry Page explaining why he thinks his latest "moon shoot" is not such a crazy idea, given Google's determined unconventionality and resources. Just don't expect immediate impact.

"In some industries, it takes 10 or 20 years to go from an idea to something being real. Health care is certainly one of those areas," Clark told TIME. "We should shoot for the things that are really, really important, so 10 or 20 years from now we have those things done."

Does that mean a cancer cure is in the works? It's obviously on Calico's collective mind, but it's not necessarily the first priority. "One of the things I thought was amazing is that if you solve cancer, you’d add about three years to people’s average life expectancy," Page says. "We think of solving cancer as this huge thing that’ll totally change the world. But when you really take a step back and look at it, yeah, there are many, many tragic cases of cancer, and it’s very, very sad, but in the aggregate, it’s not as big an advance as you might think." What Page really wants to focus on is researching how to eliminate a greater spectrum of aging problems and illnesses, and luckily, Google has a whole lot of funding ($54 billion, to be exact) to put toward that odyssey. [Funding of NIH dipped seriously below $30 billion - AJP]

"Immortality" is the buzzword on everyone's lips, as well as Calico's assumed long-term goal, though Page hasn't officially confirmed this. If that all sounds a bit Neuromancer to you, take heart and remember that Google engineer (and renowned futurist) Ray Kurzweil has already made it clear that transcending biology — via upgrading the human body like software — is in his, and now his company's, very real career aims. So, strap in, this will be a long, possibly infinite ride.


Google announces Calico, a new company focused on health and well-being

MOUNTAIN VIEW, CA – September 18, 2013 – Google today announced Calico, a new company that will focus on health and well-being, in particular the challenge of aging and associated diseases. Arthur D. Levinson, Chairman and former CEO of Genentech and Chairman of Apple, will be Chief Executive Officer and a founding investor.

Announcing this new investment, Larry Page, Google CEO said: “Illness and aging affect all our families. With some longer term, moonshot thinking around healthcare and biotechnology, I believe we can improve millions of lives. It’s impossible to imagine anyone better than Art—one of the leading scientists, entrepreneurs and CEOs of our generation—to take this new venture forward.” Art said: “I’ve devoted much of my life to science and technology, with the goal of improving human health. Larry’s focus on outsized improvements has inspired me, and I’m tremendously excited about what’s next.”

Art Levinson will remain Chairman of Genentech and a director of Hoffmann-La Roche, as well as Chairman of Apple. [Plus Chairman of the Board of "Breakthrough Prize" - AJP]

Commenting on Art’s new role, Franz Humer, Chairman of Hoffmann-La Roche, said: “Art’s track record at Genentech has been exemplary, and we see an interesting potential for our companies to work together going forward. We’re delighted he’ll stay on our board.”

Tim Cook, Chief Executive Officer of Apple, said: “For too many of our friends and family, life has been cut short or the quality of their life is too often lacking. Art is one of the crazy ones who thinks it doesn’t have to be this way. There is no one better suited to lead this mission and I am excited to see the results.” [Tim did not have to mention an ultimately examplary person by name for a key issue that some kind of death is inevitable for all of us - but some diseases, a prominent example is cancer, deprive not only longevity but even a decent quality of life in some cases for many-many years of terrible suffering. - AJP]

Contact Leslie Miller

Google Corporate Communications


WTF Is Calico, And Why Does Google Think Its Mysterious New Company Can Defy Aging?

Gregory Ferenstein


September 19, 2013

Thursday, September 19th, 2013

The sad truth is that, if everyone on the Forbes 400 list simultaneously (and tragically) got cancer, or Parkinsons (or any given disease for that matter), the world would probably be well on its way to finding a cure for these illnesses, thanks to the enormous wealth that would be incentivized to back those efforts.

Finding a cure for an intractable disease requires time, enormous amounts of human and financial capital, cooperation and research — and at least a few public-private partnerships. It’s costly, and it’s messy. This is why Calico, Google’s newest mad science project, is potentially so exciting.

In fact, Calico could represent the company’s largest health-care initiative since Google Healthsprinted its way into obscurity. Of course, Google is a different company today than it was in 2008 (when it launched Google Health) and so are we. Our habits have changed: Today, 20 percent of smartphone users have downloaded at least one health app, and 60 percent of adults now look for health information online.

Led by former Genentech CEO and current Apple Chairman, Arthur D. Levinson, Calico has big plans in health care — at least over the long term. From what we’ve heard thus far, the new project will leverage Google’s massive cloud and data centers to help facilitate research on disease and aging by mining its trove of data for insight into their origins.

Plus, thanks to its investment in 23andMe, Google already has access to a fast-growing genomic database, which could come in handy as it begins to focus on, in its words, “health and well-being — in particular the challenge of aging” and dive into the science, genetics and biochemistry behind longevity and disease.

In an interview with TIME Magazine, Google CEO Larry Page implied that dramatically extending human life is one of Calico’s main goals; not making people immortal per se, but, according to a source familiar with the project, increasing the lifespan of people born 20 years ago by as much as 100 years.

“Are people really focused on the right things?” Page muses in the interview. “One of the things I thought was amazing is that if you solve cancer, you’d add about three years to people’s average life expectancy. We think of solving cancer as this huge thing that’ll totally change the world, but when you really take a step back and look at it, yeah, there are many, many tragic cases of cancer, and it’s very, very sad, but in the aggregate, it’s not as big an advance as you might think.”

While his delivery is a bit confusing, Page’s thesis seems to be an optimistic one: While curing cancer has always seemed like an insurmountable obstacle, the goal is more within reach than many believe — if only someone would just put their mind to it, he seems to say. Yes, Larry Page is brilliant, but his message also seems to imply that diseases (and their cures) are reducible — that all of the world’s problems could be cured if we just had some snappier algorithms. [Sir Alexander (Fleming) did not (have to) use any "algorithm" for serendipitously coming up with penicillin, nor there is any algorithm to aspirin - AJP). The Genome is, however, a "digital code" of life (more precisely, of hologenome regulation, based on the principle of recursive genome function). The expression of "cracking the DNA code" has been (ab)used far too many times. In fact, it has only been revealed - "cracking" of e.g. encrypted messages is a procedure that nobody even remotely familiar with mathematics would think of in any other way but by algorithms programmed into high-performance computers. Larry Page, mastermind of "Page ranking", see their brillilantly lucid core-patent, is absolutely right on target (along with Dave Haussler of USC etc, etc) that "cancer is a digital disease that will have a digital cure". - AJP]

Really, it almost seems more of a reflection of how the enormous many-headed-beast that is Google has become, as well as a testament to its resources and the type of talent it’s able to attract — rather than pure, unbridled hubris. It’s as if they’re saying: “Hi, welcome to Google! Today, we’re going to turn your eyeglasses into a computer, tomorrow we’ll develop self-driving cars, the day after that, we’ll cure cancer and increase the average human lifespan by 100 years. Oh, and by the way, we’re still trying to organize all of the world’s information and make it easily searchable!!” N.B.D., everybody, N.B.D.

Interestingly, Calico doesn’t seem to be a Google company per se, more of an investment in a new company that will be affiliated with Google and become an extension of the company’s mad science lab, Google X. “Don’t be surprised if we invest in projects that seem strange or speculative compared with our existing Internet businesses,” Page warned readers on Google+, Google’s social network. [Yes, let's not forget that Google also has a social network. It's like Facebook except no one uses it!] “Please remember that new investments like this are very small by comparison to our core business.” Of course, with a market cap approaching $300 billion, Google could make a $1 billion investment in Calico and it would still be a very small investment “by comparison to its core business.”

Not satisfied with self-driving cars and Google Glass, Page says health is something the company needs to tackle, that he wants to “solve cancer” the same way Google X has tried to experiment and innovate in wearable computing and transportation. “It takes 10 or 20 years to go from an idea to something being real. Health care is certainly one of those areas,” he told TIME’s Harry McKracken. “We should shoot for the things that are really, really important, so 10 or 20 years from now we have those things done.”

Sources tell us that Calico is still very much in the exploratory phases and is seeking neither near-term profits nor has much of any idea about how to actually increase lifespans. So there’s that [...]


While Page says that curing cancer won’t be the key to extending the average human lifespan, at some point, Calico and others will have to face it head on. “If a human could live long enough, it is inevitable that at least one of his or her cells would eventually accumulate a set of mutations sufficient for cancer to develop,” explains a team of authors in Molecular Biology of the Cell.

Thus, cancer is an inevitable part of the decay of our cells and, unfortunately, an omnipresent risk as we continue to live longer and longer. One source close to the project says that Google is exploring solutions in the area of genetically personalized medicine. Tailoring drug treatment to the unique biomarkers of the individual, such as the field of Proteomics, is a new path for improving cancer treatment.[...]

["Silicon Valley is going for it" - all bets are off ! Comment by Dr. Pellionisz)

In earlier times, Intel, Apple, HP (etc) invested non-trivial monies into Genomics. From 2004 and on, Dr. Pellionisz was visited by the now late Dr. Malcolm Simons from Melbourne to learn if Junk DNA is "anything but" then how fractals beat the at that time fashionable "combinatorial hypothesis". Other than co-authoring a peer-reviewed paper (2006 [full paper with predictions proven) we agreed as early as in 2004 that the Information Technology and Genomics "tectonic plates" would produce a "Big One" - what is happening now (yes, we were running 9 years ahead). Meanwhile, it was Samsung (well outside of Silicon Valley...) that first offered full genome analytics (2011 - that was within 7 years).

Indeed, Silicon Valley (of California) appeared to fall behind; with KPCB and Google Ventures investing in Boston-based Foundation Medicine to fight cancer and NVIDIA teaming up with Houston-based M.D. Anderson & Baylor invoking both a "Moon shot" and a "Possible Nobel Prize for fractal approach".

Now, with Google on Time Magazine cover, all bets are off. Silicon Valley IT is Ready for the Dreaded DNA Data Deluge. A heads-up YouTube has been broadcast since 2008 - but few listened and glut-producing Complete Genomics, a jewel of Silicon Valley of California, had to be sold to China.

Hardly anything happens overnight - with a few exceptions. 7 FractoGene patent licensing was made in Southern California in the 7 days after USPTO finished examination. True, the process took an extraordinary period of over 10 years by USPTO after priority-date in 2002 (announced in peer-reviewed presentation in 2003, peer-reviewed science paper 2006, and published in peer-reviewed paper in 2008, widely disseminated in Google Tech Talk YouTube (2008)).

A more typical landmark is 1 year. Last September, the ENCODE 2012 study was published in dozens of top-papers by hundreds of top scientists, worldwide. Today, as Thomas Kuhn observed in his 1962 bestseller ("The structure of scientific revolutions" p. 159. "at last only a few elderly hold-outs remain" [of the disarmingly naive genes/junk/central dogma "genome theory" of an ancient Millennium] with the sad conclusion that "the man who continues to resist after his whole profession has been converted has ipso facto ceased to be a scientist"). Unfortunately, some can make it worse for the remaining couple of detractors. Those who actively teach health professionals to neglect to look for clues e.g. of cancer in the majority of genome, falsely teaching that it is "junk" (it is there "for the importance of doing nothing", see Ohno 1972) are liable to class action lawsuits for willfull negligence by hundreds of millions of existing or future cancer-patients.

Even more prominent landmarks are 5, 7, 37 years (37 is the smallest prime that is not also supersingular prime number). Genomics appeared in connection with Google 7 years ago (Anne Wojcicki and Linda Avey founded 23andMe in 2006, with the clear intentions both to expand the scope of genomics to all consumers, lately ex-Facebook billionaire Yuri Milner providing an $50 M boost). 5 years ago the Google Tech Talk "Is IT ready for the Dreaded DNA Data Deluge?" brought the software-enabling algorithmic value of the paradigm-shift of "Principle of Recursive Genome Function" full paper and very detailed presentation literally inside the doorsteps of Google.

In 1976 (that is, 37 years ago, let's call it a "generation"), in the same year both Apple, Inc. and Genentech, Inc. were founded. It is noteworthy that to head Calico, Inc. by Google CEO Larry Page, Art Levinson was named. Dr. Levinson is former CEO of Genentech, Inc. and Chairman of the Board of Directors of Apple, Inc., and is also the Chairman of the Board of "Breakthrough Prize". Noteworthy for the magnetism of Calico, Inc. ("California Life Science Company") are the 9 lives of cats, including calico-spotted felines, and the surprising detail that is owned by Oracle (Larry Ellison is known as a champion both of extending life as well as a strong believer and practicioner of quality of life).

On breakthrough is the fractal approach to genome regulation over the "genes/junk/central dogma" (see Pubmed references above by Simpson & Pellionisz 2006, Principle of Recursive Genome Function by Pellionisz 2008 and Springer textbook Chapter by Pellionisz et al. 2013, see bio, claim of recognition and full references at Professional Homepage). The now highly acclaimed fractal approach opened the class of algorithms, most prominently of fractals, how e.g. fractal defects of the genome are linked to cancer (independently established experimental proof of concept).

Silicon Valley of California has everything we need; HPC Hardware (GPU by NVIDIA, FPGA by Xilinx), Software (now Google-sized), the power of Algorithms to build large and scalable global companies (Google) amply documented. We even have Big Pharma (Genentech/Roche, Merck). Still, as mentioned at Dr. Pellionisz' Churchill Club YouTube (2009), "It could not happen to a nicer bunch of people than us in Silicon Valley - but we should not take it for granted that it will happen here" 1:12:37 . As for Big Pharma, see the comment quoted by pharma-guru Dr. Nikolich in the same panel at 1:05:09 “With time a Microsoft or Google type IT will acquire – or build – an IT-led pharma.”

There you have it! - AJP, holgentech_at_gmail_dot_com ]

Most Assumptions in Molecular Biology are Wrong - Mattick says

Twentieth century views of microbiology are primitive and need to be junked, according to the Garvan Institute’s Professor John Mattick who spoke at a recent science lecture at ANSTO.

“The 20th century was just a warm up for molecular biology. It was primitive. The real game is on now; it’s all to be discovered,” Professor Mattick said in a talk that went to the heart of traditional views of biology and evolution.

Listen to what he had to say below, or download a copy of his presentation.

- See more at:

“RNA is a computational engine that holds the key to cell development and cognition. It’s the main game in evolutionary terms and always was.

The talks are given at ANSTO’s Lucas Heights campus on the outskirts of Sydney. To see previous talks, visit our Distinguished Lecture page.

- See more at:

[It is now a year since ENCODE 2012 devastated the remainder of old school genomists who "hoped against hope" that ENCODE 2007, discarding "junk DNA" perhaps wasn't so devastating. Science, however, is not a vain pursuit of "negative evidence" (what the DNA is NOT, or how many percent of the DNA we do NOT know their function). Taxpayers of Canada are wasting their money while hundreds of millions die of genome [mis]regulation diseases like cancers, by supporting a post-retirement-age detractor who pontificates everything, insults everyone and publishes peer-reviewed nothing. Upon hearing the lecture Sandwalk writes, typically again in a negative fashion; "How not to do science? - Many reputable scientists are convinced that most of our genome is junk. However, there are still a few holdouts and one of the most prominent is John Mattick". While an increasingly Lonely Moron is neither a scientist lately, nor qualifies as "reputable", why do we not see absolutely anything from him "how the genome is regulated?" (hint: without mathematics and computers addressing genome misregulation is "incomprehensible to the human mind").

Dr. Mattick discredits here an "early working hypothesis" that genome function might be based on a "combinatorial foundation". Metaphors, e.g. that "the DNA is a zip-file", "like a computer OS" etc. may also fall a bit short of the sophisticated mathematical solution that some of us pursue for recursive genome function and hologenome regulation. The utility of "fractal genome governing fractal growth" has been established by FractoGene 8,280,641 and those who would like to see the RNA-s as "self-similar repetitions", below are just two diagrams [source] - AJP]

In addition, a late 2012 paper already seems to support a "fractal approach to RNA function" "Multi-scale RNA comparison based on RNA triple vector curve representation" by Ying Li, Ming Duan and Yanchun Liang: "it is very easy to identify the difference between 5S_rRNA(U05019.1/544-658) and tRNA (U48228.1/7-166). In order to further prove the difference of the two TV-Curves, the fractal dimensions of the TV-Curves of 5S_rRNA (U05019.1/544-658)and tRNA (U48228.1/7-166) is 0.6404 and 0.5958".

Pellionisz et al. put forward the quantitatively verifiable or refutable mathematical principle that "the RNA system serves as a genomic precursor to the kind of covariant-to-contravariant transformation what an evolutionary late-comer, the cerebellar neural networks perform". Since the cerebellar network model was experimentally supported by independent researchers, it seems realistic to expect independent experimental tests how "the RNA system of multicellular organisms led to the Cambrian explosion" - AJP, to be contacted at holgentech_at_gmail_dot_com ]

Genomic Dreams Coming True In China

FORBES ASIA | 8/28/2013

This story appears in the September 2, 2013 issue of Forbes Asia.

By Shu-Ching Jean Chen

Wang Jian is proud of scaling Mount Everest in 2010 at age 56, but the Shenzhen genomicist has been climbing new scientific heights with the firm that he set in motion with three fellow young castoffs from the Cultural Revolution more than 30 years ago.

Today what is known as BGI has the world’s biggest capacity for sequencing the human genome, bringing credit to China and hope of mass affordability for a process that can identify an individual’s DNA and thus make it possible to take steps toward a longer, healthier life.

Just as mountaineering can take long preparation, determined advances and occasional bold steps, so has BGI’s reach for preeminence under Wang–its president–and two remaining cofounders.

One big advance came this past March, when it acquired, for $118 million, Complete Genomics California. The combined entity is capable of sequencing up to 80% of the whole human genomes the world has processed, according to George Church, a genetics professor at Harvard University. That’s still a small total; if you include partial genomes done for ancestry and health DNA such as focusing on a faulty gene responsible for breast cancer at the publicized outfit 23andMe, you’d still reach only a few hundred thousand to date. But that’s why the scale of operation that Wang and his associates are reaching is so meaningful.

BGI is akin to a giant assembly line in gene sequencing, stretching its arms, octopuslike, to different parts of the fast-evolving genome business universe, from discovery research (its clients: big pharmas and research institutions) at the top end to gene-sequencing services in the middle (such as academic and commercial labs). And it is now positioning itself in what many scientists recognize as the most promising area of all: diagnostics clinics such as hospitals.

With Complete Genomics, BGI has acquired not just superior technology in sequencing human genomes but also the know-how for producing the boxes, or the machines that process the data, giving it an edge in a rapidly evolving landscape. “In other industries such as automotive and electronics, the first companies to get to the highest-quality manufacturing also tend to retain the highest market share. This should be a big wake-up call [for BGI’s competitors],” says Church.

BGI’s archrival, Illumina, the global leader in making gene-sequencing machines and which two years ago started building up a sequencing service business, lobbied fiercely against BGI’s acquisition of Complete Genomics after its rival bid failed. Even before the acquisition, BGI had become the world’s leader in gene-sequencing services, which cover not just the human genome but also that of animals and plants such as pandas and rice.

Ross J. Muken of New York investment research firm ISI Group, which specializes in life sciences, put BGI at having at least 25% of the world’s total in gene-sequencing services, followed by Illumina of San Diego and the Broad Institute of Harvard and MIT.

Wang and his crew in Shenzhen are readying an IPO of the institutional-client business, more than 60% of its revenues, while they plan to keep the retail side. Meantime, the company and its backers, including Sequoia Capital and Shenzhen Capital, which helped finance the Complete Genomics deal, would have it be an exit for their sizable minority stake. That placement valued all of BGI at a modest $820 million.

BGI has sequenced 57,000 human genomes to date, mostly following its 2010 purchase of 128 HiSeq 2000 gene-sequencing machines, still the world’s most powerful. That purchase, value not disclosed, was backed by a ten-year loan of $1.5 billion from China ­Development Bank.

The hardware helps BGI compose the “book of life,” the code of each individual’s genetic makeup. Large-scale sequencing the way BGI does it not only drives down costs of such discrete profiles but also deepens understanding of complex diseases.

“Sequencing human genomes is all about two things—discovering what these variations mean and, once we understand them, sequencing the genomes of individual patients to personalize their medical treatment,” explains Adam Felsenfeld of the U.S. government’s National Human Genome Research Institute. Each human being, barring close relatives, differs by 3 million base pairs of genes, out of 3 billion, he notes.

The quest is of such scale and has such promise that it’s hard to believe that as recently as 2007 BGI was on the brink of extinction, one of several points of travail as it has navigated China’s state-dominated eco-system.

Wang and three pals founded it in 1999 in an industrial zone near the Beijing airport. They set out to create a nonprofit research outfit, only to find no such private entity was countenanced in China. Only registering as a business venture was possible, so for eight years it had no board, shareholders or meaningful returns.

“We were a group of people trying to do fun things,” Wang says. Previously, he had returned to China from the U.S. to set up a company developing diagnostic kits. The outfit, GBI Biotech Beijing, grew to 100 staffers and later was made part of what today is BGI. But the fun Wang had in mind was to be part of the Human Genome Project.

The route to BGI’s role in that led through Seattle’s University of Washington. There Wang was doing a post-doc in genetic science, and a friend from China, Yu Jun, was involved in the genome project as a researcher under one of its founders, professor Maynard Olson. The project wanted more Chinese participation.

So Wang and Yu hatched the idea that led to BGI. They recruited Yang Huanming, now the company’s chairman, who was well connected to the Chinese science establishment. Also joining in 1999 was Liu Siqi, a protein scientist trained in Texas. Wang and Liu go back to the 1970s at a medical school in Hunan, and before that to competing in youth sports.

But as it happened, all four founders had failed to finish high school because the Cultural Revolution upended their lives like so many others’. They all had managed to scramble back to college afterward and then to pursue advanced research at U.S. universities in the late 1980s. Wang was the glue binding them together.

Selling Chinese participation in the genome project was not easy at home, however. Most domestic scientists were skeptical about such a costly endeavor. But 50 million yuan, not quite $10 million, in initial funding was raised, and a staff of 400 in Beijing was quickly exhausting that sum.

When former U.S. President Bill Clinton touted the landmark mapping of the first genome in 2003, and Chinese President Jiang Zemin heard him, on CNN, mention China’s participation, it opened a new door. Jiang ordered up further funding and help from the scientific hierarchy.

Then known as the Beijing Genomic Institute, Wang’s operation took on an adjunct from the Chinese Academy of Social Sciences. The two worked in parallel, but the institute’s original enterprise kept advancing and was increasingly at odds with the government apparatus. By 2007 the research was being starved of funding and other state support, and a divorce loomed. Shenzhen’s administration stepped in with an offer of a former shoe factory as offices, but Wang & Co. would have to produce results that brought in revenue.

They took the gamble and relocated to the southern China growth town, rebranding the institute as BGI Shenzhen. By then it had shrunk to fewer than 20 staffers, all going without pay. Only six months later, when BGI mapped out the world’s first gene sequence of an Asian individual, would Shenzhen award a total of 90 million yuan spread over the next four years. At least the lights would stay on.

The move caused a split among the founders. Yu exited by selling his stake for a token sum. The remaining trio has kept a majority stake in BGI.

At headquarters in Shenzhen, now an eight-floor nondescript white building, President Wang often climbs up flights of stairs to his top-floor office—a desk, actually, by the windows in the middle of a labyrinth of numerous identical blue cells. “I am good at high-speed skiing. I am good at sports,” he declares. “You need to stay on balance.”

Cubicles on each floor are taken up by half of BGI’s 2,000-plus employees, with an equal number of staff scattered at a dozen labs around the world, in what Science magazine described as “the only genome enterprise with a global footprint.” Chairman Yang presides over this fast-expanding research and education network, which he describes as focusing on “applications in health care, agriculture and environment.”

Early in April Bill Gates visited BGI’s Hong Kong office for four hours, discussing cooperation possibilities. The Gates Foundation sought out BGI, and last September it agreed to join in global health and agricultural development, a partnership that may have helped grease approval of BGI’s acquisition of Complete Genomics.

Wang spends most of his time overseeing BGI’s for-profit businesses. The company broke even in 2011, with $192 million in revenue, roughly ten times what Complete Genomics brought in that year.

About 90% of its business is done with private clients, split equally between overseas and domestic. Among the most lucrative are long-term contracts, lasting two to three years, with more than 17 of the world’s top 20 pharmaceutical companies.

But the founders still do not look at theirs as a conventional business. The partial IPO can satisfy the outside investors, but, says Wang, “we will reinvest our earnings. We do commercial projects, but in some cases, it’d be no fun if we just think about making money.” Climbing genomic mountains is more like it.

[China recognizes the vital role of genomics. We are all safe, are we not? Google these: "God help us if we get a Worldwide Pandemic". Or, "Personalized bioweapons are a subtler and less catastrophic threat than accidental plagues of WMDs. They will likely be unleashed much more readily"]

Foundation Medicine seeks $86.3M IPO amid chase for reimbursement

July 29, 2013 | By Ryan McBride

Foundation Medicine has bought a ticket to ride the IPO train. The Cambridge, MA-based company, which provides genomic tests for cancer patients and drug researchers, has proposed an $86.3 million initial public offering. There have been nearly 30 maiden public offerings in biotech, and the company follows several cancer-focused startups that have completed successful deals. [Several factors listed in the bottom, however, make this filing for IPO a "game changer" - AJP]

Foundation operates on the cutting edge of personalized cancer treatment, but sometimes being way ahead of the curve comes with costs. As the company's filing on Monday states, the company has not yet begun to seek reimbursement for its clinical FoundationOne tests for cancer patients on Medicare. And the company indicated some uncertainties about gaining reimbursement for the test in the SEC filing for the public debut.

In fact, the venture-backed company has made most of its money from a growing list of drug developers that use its testing services to advance targeted treatments against tumors. There are 18 biopharma companies on Foundation's list of research partners, including industry giants such as Johnson & Johnson ($JNJ), Novartis ($NVS) and Sanofi ($SNY). In 2012 the company scored $8 million of its $10.6 million in revenue from biotech and pharma groups, compared with $2.6 million from FoundationOne sales.

The company, a 2012 Fierce 15 winner, is growing rapidly this year. It pulled in revenue of $5.2 million and a net loss of $7.3 million in the first quarter of 2013 compared with revenue of $612,000 and a $5.4 million net loss in the same three-month period a year earlier. The surge in revenue follows the June 2012 launch of FoundationOne, a next-generation sequencing test that assesses 236 cancer-related genes in cancer patients, helping to match them with appropriate treatments.

More than 1,500 doctors have ordered the test since its market debut, the company said. And Foundation boasts a lineup of big-named investors such as Microsoft ($MSFT) Chairman Bill Gates, Google Ventures, Kleiner Perkins Caufield & Byers and founding backer Third Rock Ventures.

Foundation, formed in 2009, could be the third company from Third Rock to pull off an IPO this year after the Boston-based venture firm's portfolio companies bluebird bio ($BLUE) and Agios Pharmaceuticals ($AGIO) both went public within the last several weeks. (Agios CEO David Schenkein is also on the board of Foundation, which lists Agios among its biopharma partners.)

If Foundation can overcome reimbursement hurdles, the company could become a major player in the global diagnostics market. Yet the SEC filing indicates that so far the company owes most of its commercial success to biopharma companies.

[Xconomy] Foundation Medicine Lays Groundwork For $86M IPOBen Fidler7/29/13

The appetite for biotech IPOs is as rabid as it has been in a decade. Will that good fortune seep into diagnostics? Now that Foundation Medicine has become the latest to step into the IPO queue, we’ll soon find out.

Cambridge, MA-based Foundation, a cancer diagnostics company backed by big names such as Bill Gates and Yuri Milner, and holding partnerships with 18 pharmaceutical companies, filed its IPO prospectus late Monday with the Securities and Exchange Commission. Foundation said it plans to raise as much as $86.25 million from public investors. It hopes to trade on the Nasdaq under the ticker symbol “FMI.”

Foundation has raised roughly $99 million in venture capital since it was founded in 2009. Its largest stockholders are Third Rock Ventures (30.9 percent stake), private equity firm Kleiner Perkins Caufield & Byers (16.6 percent), Google Ventures (11.5 percent), LabCorp (5.2 percent), Bill Gates’s Gates Ventures (5.2 percent), and Wellington Management (5.1 percent), according to the paperwork filed with the SEC.

Goldman Sachs, J.P. Morgan Securities, Leerink Swann, and Sanford C. Bernstein are underwriting the offering.

Even though Foundation has only been around for four years, it has attracted a ton of interest because of how it uses new high-speed/low-cost genomic sequencing technologies to create cancer diagnostics. Foundation takes a tumor sample from a patient, mines it for 236 of the most prevalent molecular abnormalities that could be causing that tumor to grow or spread, and sends a report to clinicians with information matching those alterations with targeted therapies and relevant clinical trials. This allows doctors to home in on specific abnormalities that appear to be driving an individual’s tumor, and then find targeted drugs or combinations that might have the best chance of working on that patient. This method is in stark contrast to today’s typical cancer diagnostics, which tend to look for a single genetic abnormality.

This approach has caught on with pharmaceutical companies who are looking to increase their success rates in R&D by picking the patients most likely to respond to their experimental drugs. Foundation said today it provides its services to 18 pharmaceutical and biotech companies, including Novartis, Sanofi, Celgene, Clovis Oncology, AstraZeneca, Agios Pharmaceuticals, and Johnson & Johnson.

Foundation formally began selling its diagnostic, FoundationOne, at the American Society of Clinical Oncology conference in June 2012. At first, it was designed to help with diagnoses in patients with solid tumors. By early next year, it expects to begin using the test to branch into diagnoses of blood-based cancers. The company said today that it believes the annual U.S. market opportunity for a diagnostic like the FoundationOne is $4.0 billion today, and will grow to $7.5 billion over the next several years as targeted cancer therapies become more and more integrated into treatment regimens.

Some 1,500 physicians in about 25 countries have ordered FoundationOne since it hit the market—including about 800 in the three months ending May 31.

This demand from physicians has put Foundation’s revenue on the upswing. It had $2.06 million in revenue in 2011 (mostly from pharma partners), $10.65 million in 2012 as it began marketing broadly to cancer physicians, and $5.2 million during the first three months of 2013. Despite the quick ramp-up of sales, Foundation suffered net loses of $17.33 million and $22.68 million in 2011 and 2012, respectively. The company said it expects those losses to continue in the near term as it expands and continues to invest in its business.

About 1,350 of its tests in 2012 were used by pharmaceutical companies, and 1,750 of them were done for physicians, the company said.

The average price per test in 2012 for its pharmaceutical customers was $3,700; for physicians it was $3,800, according to the S-1.

Foundation’s biggest challenge as a business will be tackling the reimbursement problem. Foundation’s test isn’t specifically covered under any plan—coverage and payment are determined by a third-party payer on a case-by-case basis. The company hasn’t yet submitted any claims to Medicare, the federal agency that covers many elderly cancer patients. Foundation will likely need to gather hard evidence from clinical trials—not just a collection of anecdotal patient success stories—to prove to private and government payers that patients are ultimately being helped by getting their test.

Foundation right now, for instance, is only collecting an average of $3,800 per patient on these tests despite a list price of $5,800 because of these ongoing payer negotiations.

Foundation said it plans to use the cash from the IPO to grow its sales force, fund the key clinical trials to support its reimbursement efforts, and help build out its infrastructure.

[Why a "Game Changer"? First, because it is the first IPO-filing of a major "genome interpretation" company. Second, because of the top-echelon of investors, IPO-underwriters, Big Pharma "initial adaptors". Suffice to mention that both KPCB and Google has long desired a formative involvement in "genome interpretation" - now a reality. Third, a Founding Adviser to Foundation Medicine is Eric Lander, who put the Hilbert-fractal (a model for fractal folding) on the cover of Science Magazine (Oct. 9, 2009), see Figure below (left insert).

The fourth reason, therefore, why IPO-filing of Foundation Medicine represents a "game changer" is, that it became both a major validation of Pellionisz' "FractoGene-approach". "Fractal defects of genome cause fractal pathology", e.g. cancerous growth. The paradigm-shift to fractal recursive iteration by Pellionisz (2002) was a "double heresy" (recursion was "blocked" both by Crick's mistake of the "Central Dogma" held to his death in 2004 and the artificial and false blockage was reinfored by Ohno's "Junk DNA" erroneous theory (1972), that ruled for the bulk of scientists till the end of first ENCODE project (2007). Thus, FractoGene had to be recorded as US patent (2002, with CIP 2007). Publication became possible after ENCODE (The Principle of Recursive Genome Function, submitted late 2007, peer-reviewed paper published in 2008), and the years of suppressed availability was remedied by the widest dissemination through Google Tech Talk YouTube "Is IT Ready for the Dreaded DNA Data Deluge?" in 2008. Fearful of the inevitable paradigm-shift towards informatics in genomics, a mathematically challenged petrified foreign blogger resorted to an attempt of defamation of Pellionisz ("Kook?", tried before against Barbara McClintock). However, a "proof of concept [POC] (2011)" ensued by a large group of top scientists, Dr. Lander participating, see review of dozens of POC papers). On top of it, by September 6, 2012 the 450+ top league of international science community destroyed remnants of the "negative evidence-based Junk DNA School" exactly as Thomas Kuhn said "until at last only a few elderly hold-outs remain ... will not find a point at which resistance becomes illogical or unscientific ... [the one who] continues to resist after his whole profession has been converted has ipso facto ceased to be a scientist (Kuhn, p. 159.). In the same week of ENCODE 2012 Notice of Allowance arrived that FractoGene patent was issued. Now Foundation Medicine becomes a platform to sort out the IP that called "Genome & Growth Fractal" a "Secret 2010", or as Dr. Lander's Ph.D. student Dr. Erez Lieberman-Aiden would have it is "Nobel-prize-worthy 201?"? - Pellionisz, for private contact mail HolGenTech_at_gmail_dot_com or call (408)-eight-nine-one, seven-one-eight-seven].

The Impact of Human Genome Program Nearing $1 Trillion - Battelle Report, 2013

The 2013 Battelle Report updates its previous figures, now the US government investments in the USA alone nearing $1 Trillion yield, according to the source. This columnist played an active role in the 1994 handover of the Internet (government defense project) to the private sector. Investment, and especially its yield, hyperescalated upon transfer. "Industrialization of Genomics" presently undergoes a similar, but incomporably more profound disruption, re-shaping global economics and strategic balance. Juan Enriquez envisioned this inevitable trend a dozen years ago ("As the future catches you", 2001), but at that time it was unclear how the strategic balance would change for specific powers. As of today, lessons are already measurable and can still be meaningfully addressed. Consult Dr. Pellionisz, holgentech_at_gmail_dot_com.

Interpreting the Human Genome [Pioneers on a Shoestring]

Tue, 05/21/2013 - 11:44am

by Silicon Mechanics

LISTED UNDER:Data Exchange Software|Process Integration Software

[Unique disruptions tipically call for creating the Algorithms & Architechture, Software, Hardware, Business Model - all at the same time, often by a single circuit of mastermind(s), occasionally even the basic wherewithal on a shoestring. Was rationing sugar for von Neuman's tea a good idea? - AJP]

When Knome needed a turnkey hardware platform for its knoSOFT genome interpretation application and kGAP informatics engine, it turned to Seattle-based solutions provider Silicon Mechanics. Knome had been using Amazon Web Services (AWS) for computationally intensive tasks, but needed to provide a locally-installed system with full control for clinically-oriented customers, who are sensitive about security, version control, and file transfer times.

Working closely with Silicon Mechanics, Knome developed the knoSYS100, which is a combination of Knome’s software and a hardware platform configured by Silicon Mechanics. The system is designed to provide labs with an end-to-end solution for the interpretation of human genome, exome, and targeted sequence data.

Seeking in-house solution

Cambridge, MA-based Knome provides human genome interpretation systems and services, working with pharmaceutical companies and medical researchers to understand the genetic basis of disease, tumor growth, and drug response. In its Interpretation Services division, the company has worked with researchers on a wide range of diseases, including Parkinson’s, Alzheimer’s, asthma, and cancer. Typically, the informatics for large interpretation projects, covering hundreds to thousands of genomes, would be processed in the cloud using AWS.

In 2012, as the market began to turn toward clinical applications, Knome recognized the need for labs to have internal interpretation capabilities. Instead of interpreting a large number of genomes in order to understand a specific disease, the requirement is to address the medical needs of one individual or family. In the clinic, processing and comparing large numbers of genomes is not as important as turnaround time, privacy, security, and version control.

To meet the demands of the newly emerging clinical market, Knome decided to develop an end-to-end system that would enable a lab to effectively handle the computational and interpretation requirements of next-generation sequencing-based tests within their own facility.

One of the most basic issues to be tackled is the transfer of files that are often over a terabyte in size. To transfer files this size to the cloud is typically too time consuming to be practical in a commercial environment. Even a relatively small file of 200 gigabytes can take two days to upload to the cloud. In addition, clinics have significant concerns regarding security and privacy; most early adopters want to keep their patients’ genomic data behind their firewall.

“Ultimately, privacy, security, and transfer speed drove us towards an in-house approach, so we began the process of deciding what hardware would be needed to perform all the computational tasks that AWS did for us in the cloud,” said Michael McManus, Senior Vice President of Knome.

Searching for the right hardware

Configuring the hardware required to optimize the intensive computational tasks required by whole genome-level informatics was no easy task. Knome’s knoSOFT and kGAP software packages are not single applications—rather, McManus likens them to an “ecosystem” of about 45 applications all running together.

To design, supply, and support the knoSYS100’s hardware platform, Knome turned to Silicon Mechanics, a provider of rackmount servers, storage, and high-performance computing solutions. Silicon Mechanics collaborated with Intel on product development activities to create the ideal solution. As a premier reseller of Intel products, Silicon Mechanics receives an advanced roadmap of Intel technology, as well as engineering samples of hardware to test for product compatibility, enabling it to base its product lines on Intel’s planned product launches and end-of-life plans.

Knome had already selected Intel processors, primarily because of their fast RAM throughput and the availability of hyperthreading, which improves parallel processing across compute cores within a processor. In addition, Intel worked closely with Knome to help them choose the right chipset for the appliance. The team reviewed the breadth of options in several of Intel’s chipsets and looked at the various performance bands with different characteristics.

According to Knome’s McManus, the evaluation began with the basics, like processor speed, the I/O capabilities of the hard disks in the compute nodes, and the database connections of the nodes.

“There were many discussions on bits and bytes and how to ensure we get the performance we need, as well as details like the best way to organize hard drives in a storage array to minimize failure rates and maximize performance,” stated McManus. “The Silicon Mechanics team was extremely helpful in openly working through the various issues we encountered.”

Silicon Mechanics began by developing a deep understanding of Knome’s requirements so it could narrow down all the available processor options in order to optimize price and performance. Power consumption, temperature, noise, and application performance were all evaluated.

“We went through a lot of discussion and used a process of elimination to narrow down all the available processor options to the optimal model for Knome’s users,” said Tim Groen, Silicon Mechanics’ Senior Enterprise Account Manager. “We started by asking about requirements in a pretty broad way and prepared a comparison of twenty possibilities in terms of power, price, lifecycle, and availability.”

For this type of custom-designed product, Silicon Mechanics is often called upon to bridge the gap between major vendors, component suppliers, and end users. Silicon Mechanics’ knowledge of Intel’s product lines was essential for educating Knome on the variables that were important for the application.

Hardware platform gives end users I/O support, computational power, and fast file transfer at an affordable price

The hardware ultimately selected for Knome’s new system, the knoSYS100, is a sophisticated high-performance grid computing system that integrates seven servers in a rack—all optimized to support 10 or more simultaneous users running Knome’s interpretation software and informatics engine. One of the key features of the appliance is that it uses industry-standard components, including the Intel Xeon Processor E5-2600 product family. This approach greatly reduces upfront capital and long-term support costs as compared to proprietary hardware solutions.

Within the Intel Xeon Processor E5-2600 product family were options with six- or eight-core processors, and Silicon Mechanics ultimately selected an option whose features offer the maximum RAM throughput: a high-performance computing cluster with four nodes, each with two 8-core/16-thread, 2.4 GHz, 64-bit Intel Xeon Processors E5-2665 with 20MB cache, capable of 500 GFLOPS per node. The Intel Xeon Processor E5-2600 product family offers performance gains up to 80 percent over a previous generation Intel Xeon processor-based server and provides the reduced I/O latency Knome required with Intel Integrated I/O.

Storage is provided by a Lustre array. According to Knome’s McManus, Lustre is being used because its I/O rate is matched to the systems’ intensive computational capacity. “We have all these applications running—some need memory, some need fast disk interaction, some just need a lot of CPU,” says McManus. “Each application has its own characteristics that must peacefully coexist with the others. Lustre gives us enough I/O support to manage a wide variety of usage scenarios.”

He is also pleased with the appliance’s hefty 512 gigabytes of RAM and the eight powerful Intel Xeon processors. “In this box format, we were able to create an architecture equivalent to eight of the large machines we use on AWS, giving us significant computational power at a much lower lifetime cost.”

“With this solution, we have something that is fast, reliable, easily supported— but not super expensive,” said McManus. “We have worked with a number of high-end custom hardware vendors, which may be a good solution for some customers, but the price is far higher. We decided we could get the best bang for the buck with a flexible, industry-standard solution like that offered by Silicon Mechanics.”

Silicon Mechanics integrates and tests each individual server; installs the operating system, cluster middleware, and the Lustre array; racks the servers; then integrates the power, network access, switching, and cables.

Knome is looking forward to the day when precision medicine will considered standard practice and the broad use of genomic information will be routine. Systems like the new knoSYS100 are poised to play an important part in this revolution.

[We have essentially lost half a Decade since 2008 when the question was asked publicly in Google Tech Talk "Is IT Ready for the Dreaded DNA Data Deluge?". Not many listened - and "Sequencing Industry" lost $Billions of valuation (Complete Genomics alone about half a Billion). Now the World is scrambling; with (some) components available in abundance; but "putting it all together" is still quite a challenge, requiring masterminds like George Church, whom I branded "the Edison of Genomics" - AJP]

Professor John Mattick, Executive Director of the Garvan Institute: "the dam is about to burst"

Hello, welcome to Sunday Profile, Richard Aedy here.

Today, a man who may just be overturning the way we think about our genes and ourselves.

John Mattick is the executive director of the Garvan Institute, one of Australia's finest medical research organisations. He's been in the job since January, after more than 20 years in Brisbane where he established the Institute for Molecular Bioscience and was a key player in Queensland's Smart State Strategy.

Professor Mattick developed a good relationship with the then Premier, Peter Beattie and was very effective at attracting bright scientific talent and, at least as importantly, lots of money for his institute.

But none of that will put him in the history books whereas what he's done in the lab just might.

Last month he received the Human Genome Organisation's Chen award for distinguished academic achievement and research.

It's hardly the first prize he's been awarded. But if his theory is right he might find himself on a plane to Stockholm in order to pick up a rather bigger one.

So what's all the fuss about? Well - junk. Junk DNA is the name first given to the 98 per cent of that molecule in you and me that doesn't code for a protein.

But John Mattick doesn't believe it's junk at all. He thinks it does something remarkable - coordinate human development. [See the mathematics how "the RNA system acts as a genomic ancestor of the cerebellum; whose sole role is coordination - AJP]

But I'm getting ahead of myself. Let's go back to first principles.

JOHN MATTICK: The definition of a gene arose in the 50s and 60s, 50 years ago, from the double helix and then studies on bacteria.

And the paradigm which was rather ironically called the central dogma emerged where DNA, a stretch of DNA gene, made a temporary copy called RNA which was then converted into a protein. And the proteins were and are the functional components of cells.

So everybody assumed that this is the way genes worked and that all genetic information was transacted by proteins. And protein one would carry oxygen, protein two would, you know, digest glucose or whatever it was.

It was a very deeply mechanical conception. You have to imagine the mindset of the 50s and 60s, that everything was mechanical. This was 20 or 30 years before the realisation of digital computing etc.

So when people discovered to their shock in the late 70s that much if not most of the human genome was composed of sequences that didn't code for protein, they automatically assumed that because it didn't fit their conventional [convenient - AJP] idea of a gene that it must be some sort of evolutionary debris or junk.

RICHARD AEDY: So that's where we get the word from, junk?

JOHN MATTICK: Yes. And the amazing thing about this Richard was, because I bumped into this as a post doc in Houston in the late 1970s.

And what was discovered - and this was and remains the biggest surprise in the history of this field - was that the genes of humans and other complex organisms are mosaics of protein coding and non-coding information, spread out over vast tracts of the DNA. ["Mosaic" is not mathematically defined - FractoGene is - AJP]

The whole lot is copied into RNA. And the in-between bits are spliced out.

RICHARD AEDY: Yeah they're sort of nipped out.

JOHN MATTICK: Nipped out, yes.

RICHARD AEDY: It's beautiful isn't it?

JOHN MATTICK: It is. And people said, oh thank God the central dogma still lives. Genes still make proteins even though they go through this bizarre process of making a much longer copy of the gene and cutting out all the offending intermediate bits.

Interestingly it was immediately and universally assumed - because everybody thought, knew, or thought they knew, that genes made proteins - this stuff that didn't make proteins, despite the fact that it was copied into RNA, must be junk.

And the thought popped into my head, hang on, there's another interpretation and that is that this RNA which has been copied off the gene but not going on to make a protein is sending some other sort of information into the system.

And I thought, well that's not only equally plausible; it's actually more plausible. And if that were true it means the system is so much more complex and sophisticated than we thought.

Now in those days, you know, this was very early days. You couldn't really test the idea. So it hung around my head as a kind of intellectual hobby.

And by the late 80s when gene cloning technology had been well established it was starting to be possible to really explore the idea. So I took myself off to England, had the luxury of having a sabbatical. I parked myself in Cambridge in the genetics department for six months.

And I read everything and talked to everybody. I said what about this idea? Most people thought it was mad. But the more I read about it the more information, funny observations seemed to fit with it. And more importantly there were no falsifying observations.

You know in science you can't prove anything.

RICHARD AEDY: You can only disprove it. And if you can't disprove it you accept that it's right.

JOHN MATTICK: Well it's looking better and better, yeah. I couldn't find anything that disproved the idea at all.

RICHARD AEDY: So let's just clarify John. You're arguing that the 98 per cent of the DNA that we have that doesn't seem to code for a gene actually is there to code for the bits that do all the conducting and organising.

JOHN MATTICK: Essentially, yes.

And let me just wind back a bit Richard, just put everybody in the picture. It turns out that there were three great shocks in molecular biology. The first was this mosaic structure of genes and all of this apparently useless RNA being transcribed.

The second was that our genomes are composed roughly half of viral sequences.

RICHARD AEDY: These are ancient invaders that are still there.

JOHN MATTICK: Yeah, yeah, that people called selfish DNA because they condemn them on the same basis. But there's more and more evidence that these are actually live parts of our genome, that the genome is far more complex than we thought.

And the most recent surprise which plays into both of these is that the numbers of conventional genes that you and I have is effectively no different than a millimetre long nematode worm that lives in the soil. They have the same number of conventional genes that you and I do.

RICHARD AEDY: So we must be doing something pretty cool with what we've got to develop so much of a more complex being than a nematode worm.

JOHN MATTICK: That's right. So basically the part set for animal development was invented a long time ago.

Now we have some differences from worms but most of the genes that are coding for proteins do the same things.

So what has clearly happened is that the regulatory architecture that puts these proteins in the right places and controls cell development and is essentially a difference between a worm of a thousand cells and a human with a hundred trillion cells is all of this RNA regulatory superstructure that really, as you said, orchestrates and conducts the patterns of gene growth, division and differentiation to put an increasingly sophisticated organism together, one that can walk and talk.

RICHARD AEDY: Now you first went public with this in '94, just after the, or at the end of your sabbatical more or less.

JOHN MATTICK: That's right, yes.

RICHARD AEDY: That's 18 years ago now. It's still contentious isn't it John?


RICHARD AEDY: There's the smile!

JOHN MATTICK: (Laughs) Yes, look it's less contentious.

RICHARD AEDY: But there are many people…

JOHN MATTICK: Or there are blogs out there who…

RICHARD AEDY: …who think you are talking through your bottom, basically.

JOHN MATTICK: Yes, and if people want to go on the web and look around at a few blogs they'll see some doozeys. But that's the nature of controversy.

Look I'm comfortable in my mind that all the evidence points in that direction. There are no falsifying observations. More and more evidence is accumulating daily. And maybe it would reassure people to know although I hesitate to say it that last, two weeks ago I got the Chen award from the Human Genome Organisation for this work. So the system is starting to acknowledge that I might be right and I'm sure I am.

But look, that's the nature of science. You've got to see where the mysteries are. You've got to see what the unusual observations are and chase them.

Look science is a journey. We tend to see it, all of us, as received wisdom. But we don't know what we don't know.

Somebody once said the best science was done at the point of greatest surprise. The surprise to me has been, as I get older, to see how truly conservative science is. You imagine within 10 years of the double helix, that was in 1953, by the early 60s the fledgling field of molecular biology had decided it knew the conceptual framework for how genes worked. Genes made proteins. That was it, done and dusted.

And then when they get slapped in the face by a wet fish of these vast tracts of non-coding sequences, these virally derived sequences in our genome, they don't reassess whether their founding conception was fully correct or not. They just assume that this is all junk and just sweep it under the intellectual carpet and get on with life.

It's amazing I mean how conservative science is.

RICHARD AEDY: And it's happened of course in other fields. At the end of the 1800s there was a widespread belief among physicists that they knew everything, that this had all been sorted.

JOHN MATTICK: (Laughs) That's right.

RICHARD AEDY: I think before even the discovery of the electron I think they were thinking that, let alone...

JOHN MATTICK: Lord Kelvin wrote an article predicting the end of physics, yeah. He said we have Boyle's Law, we have Ohm's Law, that's it.

And then along came Rutherford and Einstein and Shrödinger and that threw all the cats up in the air.

Look the same feeling was abroad in molecular biology at the end of the 20th century. The whole thesis of the Human Genome Project was, well, we need to know what all the genes, the conventional genes are, what they do and how they interact and then we can put Humpty Dumpty back together again. They thought that was all that was required.

In fact it was just the beginning. The real complexity, both in our developmental complexity and the platform for our cognition, is in all of these sequences that were dismissed as junk, that are orchestrating how to put these building blocks together.

RICHARD AEDY: Now John you were saying this first occurred to you when you were doing your post doc which you were doing in Texas at Baylor College. And at that time you were I understand at one point sharing an office with Frances Crick, a co elucidator of the structure of DNA. Or he was certainly around.

JOHN MATTICK: I didn't share an office with him, I wasn't that privileged. But what Baylor did which I thought was wonderful, when people like Francis Crick came through to give the occasional seminar, they introduced them to the students and post doctoral fellows first.

So I had the privilege of having Francis Crick in my office for half an hour. And to meet him in person was fabulous.

RICHARD AEDY: What was it like? Because he died quite a while ago now but he had this reputation of having about a hundred ideas a week and of which 95 would be certifiably rubbish and three would turn out to be ill advised and one impossible. And the other one, the one that was left, would be brilliant.

JOHN MATTICK: That was my impression. Look I was just a young post doc, you know, fresh out of Melbourne at the time. I did my PhD in Melbourne.

I found him to be very engaging and courteous, kind to me as a young post doc. He was a genuine intellectual and he was always pushing the boundaries of ideas and I think that's a wonderful thing.

And sure, you know, when you're having ideas many of them will be wrong. But you've got to have some to be right with some of them and he did. He was wonderful.

RICHARD AEDY: This is Sunday Profile on ABC Radio with me, Richard Aedy. And my guest today is the scientist and director of the Garvan Institute, John Mattick.

John, if you right about what we call, has been called junk DNA and is still called non-coding DNA and what it's for, the great organising of how we're put together, what are the implications?

JOHN MATTICK: In the sense of the straight knowledge which I think is always the first and fundamental thing, to truly understand how a suite of software which we call our DNA can orchestrate these 20,000 components and their variants, to put 100 trillion cells in the right places, and is self-programmed, if you like, this is a suite of software that assembles itself. I think that's going to be a tremendous breakthrough in just understanding the sophistication of human genetic programming.

The implications in terms of medicine and beyond are that this is where the real differences, not all of them, some of them are in the proteins, but most of the differences between you and me as individuals and between humans and other species, between limes and lemons, is in this super structure. Because the component set, the part set, like a Meccano set, is much the same for all animals.

So the idiosyncrasies that make you and I what we are as individuals and the idiosyncrasies that play into our susceptibilities to complex diseases are nearly all written in the variations in this structure.

RICHARD AEDY: Some we know it's definite genes and some we know there are several genes acting in concert. And there are, whether we're talking about an illness or a susceptibility or a trait like eye colour - we know, we kind of know how eye colour is inherited and it is, it's a gene. But most of it is going to be in this 98 per cent that doesn't code for what we have thought as a gene.

JOHN MATTICK: Yes look there's a history here because in traditional genetics people concentrated on what they called monogenic diseases - things like cystic fibrosis, Huntington's disease, thalassemia, etc.

RICHARD AEDY: This is where there's a problem in one place.

JOHN MATTICK: Where the protein in the gene does not work. It's a bit like having a light switch that doesn't work, you know. The implications are catastrophic. You're sitting in the dark. Or you can't carry oxygen in the case of thalassemia.

This is what I call catastrophic component damage. So if you have a genetic mutation in a protein coding gene, the conventional genes, the consequences are usually very severe, very nasty, if you survive at all.

But variations in the architecture of the system, just like variations in the architectural plans for this building, will result in a different looking building or a different looking organism.

So this hidden layer of regulatory RNA is the design, the orchestrator. So when you vary that by and large what you see is differences in the design rather than catastrophic component damage.

I was asked a few years ago by a very good geneticist, you know, if this is so important John how come we haven't seen it in conventional genetic screens? And the major reason is because conventional genetic screens were focused on catastrophic mutations. And subtle ones were either not of interest, hard to map or not even seen, particularly if you were dealing with fruit flies and mice.

So the interesting differences between us, assuming we have a functional part set, you know that we, to begin with, the differences that make us individuals are much more in this architectural layer than they are in the component layer.

RICHARD AEDY: So the way you wear your hat, the way you sing off key, all those things (laughs)…

JOHN MATTICK: It's amazing.

RICHARD AEDY: …that's in the 98 per cent?

JOHN MATTICK: Yeah, yeah. Almost certainly. What was dismissed as junk will hold the key to understanding human diversity and I think in the end human cognition.

Because what's occurred to me lately is that this regulatory RNA layer which is hardwired - you know it's hardwired because if you compare identical twins they look the same. So if you get the same version of the program then you come out the same physically. This RNA regulatory network which orchestrates these things has been then rendered plastic in the brain.

So all these enzyme systems, the new genes, conventional genes, have evolved to take this RNA information in the brain and change it in response to experience.

So we now think that this is the fundamental basis of the, the molecular basis of learning and memory. And that's what I'm doing now.

RICHARD AEDY: That's enormous. It also is going to have big implications isn't it for disease? The implications are that we can have much better medicine and much better health.

JOHN MATTICK: Yes and the era of personalised medicine is dawning as we speak. It's one of the reasons I'm in Sydney to join the Garvan Institute because I think this is the place in this country to do it.

But just to put it in context, the first human genome sequence which was published a decade ago cost $3,000 million to produce - $3 billion. We now do it in a few days for $3,000. And the cost of sequencing our whole human genome is dropping by a factor of two every six months or so.

So it's now becoming feasible and in fact it's happening that individual human genomes are being sequenced to great effect. So we can understand how the differences in our sequence between you and me play into our different characteristics and also how it underpins disease.

And this turns out to be extremely powerful in cancer.

RICHARD AEDY: Well yes. And it occurs to me, and I'll be very self interested, nakedly self interested here John. I'm 48 so in 20 years' time I'm 68, assuming I get there. In that time, with the rate of progress that's been shown, actually there's a very good chance there will be diagnostic tools and perhaps treatments that will mean that I don't get cancer when I might otherwise have expected to. It's fundamentally a disease of ageing.

JOHN MATTICK: Well I'm not sure about whether you won't get it. But I think that the chances that you'll recover well from it are very, very high. And I can give you a couple of examples just to make this more tangible.

Since it's become feasible to sequence individual human genomes at a reasonable cost people have been increasingly sequencing mutated DNA and cancers. And in fact the Garvan Institute together with my old institute IMB in Queensland are part of the International Cancer Genome Consortium where we're sequencing 500 cases of many different sorts of cancer, in our case mainly pancreatic cancer.

What's coming out of this is that it's somewhat uninformative and can even be misleading to type cancer as breast cancer or prostate cancer.

Rather it turns out that while the spectrum of mutations underpinning cancers in different tissues may differ somewhat that many of them are common, so that 5 per cent of cancers in tissue X may have the same fundamental driving mutation that's underpinning this rogue behaviour of the cells as 30 per cent of the cancers in tissue Y.

So you're much better off to talk about what the underlying mutation is.

And this was driven home a couple of years ago when a pioneering study in Toronto was done where an individual presented with a cancer, the cancer was sequenced and it turned out that the fundamental mutation in this unknown cancer was the same that had been well characterised in another type of cancer for which a drug was already available.

It was not indicated by the cellular pathology because it just looked like cells from this particular organ.

When they put this individual on the drug that was indicated by the sequencing he recovered. And there are many, many more examples of that now.

RICHARD AEDY: There's actually not just better health at stake here. I think whoever does this is probably odds on for a Nobel Prize in medicine and physiology. Whoever is able to show the DNA codes for the RNA which is definitely pulling all the strings…

JOHN MATTICK: On the non-coding side at least.


JOHN MATTICK: Well I don't know, possibly. I do think it's a transformative realisation if it's correct. And it does look like it's correct. But I don't think beyond what the implications are and what's the most interesting thing to do next.

I do think that within the next five to 10 years, give or take, everybody in this society will have their DNA sequenced. I think it's a new world.

RICHARD AEDY: You now head the Garvan Institute of Medical Research, which you've mentioned. And this follows a long - exile is probably the wrong, but a long time away from Sydney. Sydney is your home town. Why did you take up the role?

JOHN MATTICK: Why did I come back?


JOHN MATTICK: Almost for the same reasons I went to Queensland. I joked that I was in the wilderness but I wasn't. My 23 and a half years in Brisbane were just fabulous and I'm very grateful to the University of Queensland. We achieved a lot there.

What I saw in Queensland those days was an emerging city and an aspiration to do really good science. And there was a spirit abroad which I became part of.

I was quite happily doing my research there when I was giving a seminar here at the Garvan last year. And a good friend of mine here asked me if I might be interested in succeeding John Shine as the director. And to my surprise I said I might be interested.

And when I dug into my psyche as to why I might have said that, because I was very happy in Brisbane, it was because I do believe that the Garvan and the relationship of the Garvan Institute with St Vincent's Hospital is the best place in Australia to usher in this next generation of science in medicine that is genomically informed, genomically aware and drives towards personalised medicine.

Finally I think that molecular biology is going to make good on its promise to change things. So here I am back again.

RICHARD AEDY: I'm really interested in the move because you've just spent six years running your own lab. You'd sort of stepped away from running the Institute of Molecular Bioscience which you'd worked so hard to set up and you went back to what I imagine is your first love, the hands on running a lab with young people. Now you're back to the big office and all the extra demands of things.

JOHN MATTICK: Yes, it wasn't a decision taken lightly. I remember I guess it was seven or eight years ago talking to the then deputy vice chancellor of the University of Queensland saying that I had three jobs.

I had an institute of 500 people which was a big job and it's the representation as well as the management. I had research I wanted to prosecute because I thought I'd seen something nobody else had seen and I didn't want to die wondering. And I had a family.

And I said I think I can do any two of those three jobs well, but all three I'm compromising all three, so one's got to go. And I want to go in and chase, I want to you know look after the family better than I've been able to do for a while. And you know the kids are growing, all the normal things.

And I want to go and prosecute this idea that the junk ain't junk. You know I've just, I've got to do this. I became a scientist to be a scientist.

So that's gone extraordinarily well, aided by a gifted group of people that joined me from all over the world who are taken with the idea and came to me from the United States, from Canada, from Finland, from Russia, Brazil, Mexico. And these were gifted individuals. And so we made a great team. We were very happy.

RICHARD AEDY: So what's happening now with that, with the research end? Because running the Garvan is a full-on job.

JOHN MATTICK: It is. And look I'm still wrestling with myself over this because it's been particularly full-on because the first few months of a new job you've got many people to get to know and you've got to do a lot of listening. I feel confident that having had the experience of building and running a major institute which is of the size of the Garvan in Queensland, that I know how to do it.

With the wisdom of hindsight and that six years back in the lab, a kind of wisdom and experience has settled so that I have a clearer idea what's important to do, how to encourage the place, how to run it without having to learn on the job anymore.

The plan is to run the institute and develop it in the morning and do the exciting science in the afternoon.

And that will put pressure on me and the family again. But I also believe that not only is science the most wonderful endeavour of all, but the director of a major institute has to be research active.

So I think we proved that the RNA layer is important, even though the textbooks don't reflect it yet. But the dam is about to burst.

RICHARD AEDY: Thank you very much for joining us on Sunday Profile.

JOHN MATTICK: It's my absolute pleasure, thank you.

RICHARD AEDY: The molecular biologist and still newish director of the Garvan Institute in Sydney, John Mattick.

I'm Richard Aedy, thanks for joining me on Sunday Profile and thanks to producer Belinda Sommer.

[See 30 Nobel Prizes for Nuclear Physics - AJP]

Non-coding RNA .. is acutely regulated .. in schizophrenia..!

Genome Misunderstood for Fifty Years - Low levels of RNA linked to schizophrenia

The Sidney Morning Herald
April 30, 2013

[The science article by Mattick et al. (The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing) and its popular coverage below heralds a new era. Not only in Genomics, but also in a now rapidly merging Genomics & Neuroscience; "Our understanding of both the genome and the brain will remain partial and disjointed until we reach a unification of the intrinsic mathematics of structuro-functional geometry of both – as the first is without question a foundation of the second" [Pellionisz et al 2012].

Gone are the decades of empty “debates” over the “genes and junk governed by dogma”. All are surpassed by the paradigm of The Principle of Recursive Genome Function [2008], opening the floodgate to recursive algorithms "permitted" to make genome regulation software enabling). After half a Century, especially marked by ENCODE 2012, the question is no longer if the human genome is mostly not, or to whatever percentage it still may be, "Junk". Mattick won a "case of vintage champagne" by his bet with Birney - thus the number-game of "exact percentage" is one of those pseudo-scientific un-answerable questions, like exactly how many stars the Universe contains (by the time you could count them, some stars would die and others would be born - or ad absurdum "how many angels can dance on the tip of a needle").

Science moves beyond detractors to the real software-enabling question of the algorithms of "genome regulation" - by that whatever percent.

The article by Mattick et al. dashes false hopes that for specific diseases we can, by necessity, find "a gene as a culprit" (we should keep in mind that the "gene" itself is undefined since ENCODE 2007). Cancer is already admitted to be the ultimate "genome regulation disease" with too many genomic defects for the un-aided researcher/therapist. False hopes are abandoned to find any single "cancer gene", and thus the same might be true to so many other syndromes not yet addressed in the era of a new paradigm. The sober recognition remains that therapy up to a cure before all calls for an understanding "genome regulation" - for medicine to save costs measured in human life and dollars. Next to cancer, autism & schizophrenia as well as scores of auto-immune diseases have already been linked to massive "fractal defects" implicating vast arrays of "non-coding DNA". IP is already available by appointment for consultation leading to licensing of fractal utilities.

Mattick et al. provides now independent experimental evidence for "long non-coding RNA" linked to one of the most serious diseases (schizophrenia) falling into the domain of neuroscience, that is can no longer be reserved to exclusive search for any imaginary "schizo-gene". Instead, Mattick et al. challenge our understanding of genome regulation, with the long-neglected "RNA system" so wisely put into a laser-beam focus. This is in the larger context of the assessment after the first decade of the Human Genome Project; ''Spending lots of money to generate huge data sets without any real effort to getting to new knowledge or understanding has been a huge frustration,'' ... "'It's now easy with the new technology to generate a lot of different data, but there are very few groups or scientists generating knowledge out of this data. We're at a frighteningly unsophisticated level of genome interpretation.''. - comment by AJP]

[Public relation coverage of new results by Mattick et al. below - AJP]

Australian scientists have described how some neurons in the brain switch off certain genes as part of normal brain function, a process that appeared disturbed in people with schizophrenia.

While most people were familiar with the role DNA played instructing the body's cells to produce proteins, a far greater amount of genetic material, called non-coding RNA, was involved in regulating the expression of the genome in response to external cues, such as when neurons fire in the brain.

One of the research leaders, John Mattick, said in the brain, sections of these genes, known as long non-coding RNA, once activated, guided the behaviour of neurons.

"In the brain these processes are soft-wired [thus should be "softwared" ASAP - AJP] and they respond and adapt to external cues," said Professor Mattick, the executive director of the Garvan Institute of Medical Research.

Over the past two decades Professor Mattick and other others have shown the body's vast amounts of non-coding RNA are not junk as previously thought, but essential to regulating the function of other genes.

"People have misunderstood the structure of human genetic programming for the past 50 years," he said.

"The evidence is very strong that most of the human genome is active in producing RNA, most of which controls and regulates the genome in very precise ways during development."

In this study, Professor Mattick and Dr Guy Barry from the Institute for Molecular Bioscience at the University of QLD, found that when they activated specific neurons, the level of long non-coding RNA, known as Gomafu, inside the cell dropped dramatically, which signalled to other parts of the cell to perform specific functions.

After a few hours, the Gomafu levels return to normal, ready to be activated again.

But in the post-mortem brains of people with schizophrenia, the researchers found abnormally low levels of Gomafu.

While other experiments with colleagues from Johns Hopkins University showed these non-coding genes could form strong bonds with other proteins inside the neuron that have previously been implicated in schizophrenia.

"You can imagine that if the schizophrenic brain is firing differently – and Gomafu levels are consistently lower – it would cause havoc within the cell, with all sorts of genes and proteins free floating and available to act, where in a normal brain they would be tethered to Gomafu."

The team, whose findings were published in the journal Molecular Psychiatry, plan to study these process in more detail in human cells.


[Below, landmarks of vision by Mattick are highlighted over the past decade. Mattick, upon receiving a Prize, gave an Interview with excerpts below. He emphasized that both ENCODE 2007 and ENCODE 2012 handled "Central Dogma" as a "tabu subject", though precisely the reversal of the Dogma ("uncontestable truth" :-) "permitted" the class of algorithms, see The Principle of Recursive Genome Function by Pellionisz 2008- AJP]

HUGO Matters
Interview with John Mattick

MARCH 21, 2013

Q: The activity shown in the non-coding regions of the genome from last year’s ENCODE papers seemed to catch the mainstream media’s attention, but it must have been old news for you. How did you start looking into non-coding RNA and what did you think of the new data?

A: It’s been obvious for 35 years now that most of the genome is transcribed to RNA. That brings up two possibilities—the non-coding transcriptions are either junk, meaning that the genome is full of rubbish, or that another type of information is being put into the system. The second possibility struck me as much more interesting than the assumption that it’s all junk, and it became clear as crystal to me as more data came in over time that it’s much more likely to be functional than not.

The ENCODE project looked at things that have been on the table for years, but it’s nice to get some extra detail. Unfortunately, many still seem to cling to the notion that most genome biology in humans is driven by proteins. ENCODE is curiously silent about the implications of the massive transcription of RNA and the signatures of functional organization across these non-coding regions, preferring perhaps to duck the question of whether it is all relevant or largely “transcriptional” noise.

The intellectual and cultural problem is that if this non-coding RNA is functional—and all the emerging evidence points in this direction—the entire conception of gene regulation has to be reconstructed. The field has assumed for a long time that protein regulators, transcription factors of various sorts, drive the regulation of the system. But now we have to figure massive amounts of regulatory RNA into our understanding. Transcription factors are very powerful stage-specific effectors of gene expression, but my feeling is that much more information is required to supervise architectural organization—the shapes and positions of different muscles, bone and organs.

Q: Architecturally? You mean a larger regulatory framework?

A: Yes, people haven’t really considered whether additional information is needed for developmental architecture, and how the transcription factors might be integrated into this larger narrative.

The genome has an outpouring of RNA during development, with over 90 percent of the genome differentially transcribed in different cells at different stages. The major function of these transcripts appears to be to orchestrate the superstructure of the genome in a very precise way, by directing the site-specificity of the epigenetic complexes that modify the DNA and the proteins around which it is wrapped—an extraordinarily complex secondary code. Exploring that is a journey we’ll have to go on to understand development.


[Almost immediately after ENCODE 2012, Mattick wrote about "Rocking the Foundations"..]:

Rocking the foundations of molecular genetics

John S. Mattick
Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia

.. the finding of extraordinarily dynamic noncoding transcription in complex organisms suggests that the long held idea that gene expression is primarily controlled by combinatoric interactions between cis-acting transcription factors and their cognate binding sites is also incorrect, but rather that RNA may be the computational engine of the evolution and ontogeny of developmentally complex and cognitively advanced organisms


[Mattick laid down in his landmark 2004 Scientific American paper his thesis that the non-coding RNA as a genome regulatory system of differentiated multicellular organisms must be a quantum leap beyond genome regulation in prokaryotes]:

The Hidden Genetic Program of Complex Organisms

John Mattick
Scientific American, 2004

...Pioneering biologist Jacques Monod summarized the universality of the central dogma as “What was true for E. coli would be true for the elephant.”

Monod was only partly right. A growing library of results reveals that the central dogma is woefully incomplete for describing the molecular biology of eukaryotes. Proteins do play a role in the regulation of eukaryotic gene expression, yet a hidden, parallel regulatory system consisting of RNA that acts directly on DNA, RNAs and proteins is also at work. This overlooked RNA-signaling network may be what allows humans, for example, to achieve structural complexity far beyond anything seen in the unicellular world.

...Throughout evolution, therefore, the complexity of prokaryotes may have been limited by genetic regulatory overhead, rather than by environmental or biochemical factors as has been commonly assumed. This conclusion is also consistent with the fact that life on earth consisted solely of microorganisms for most of its history. Combinatorics of protein interactions could not, by themselves, lift that complexity ceiling.

Eukaryotes must have found a solution to this problem [The dual (covariant and contravariant) valences of RNA system, and the RNA system "acting as a genomic ancestor of cerebellar neural networks - Pellionisz et al, 2013 provides the mathematical apparatus to formulate the vision of the RNA system yielding coordinated regulation, along with Eigenstates of genome regulation (evident also by RNA interference) in a software-enabling manner - AJP]. Logic and the available evidence suggest that the rise of multicellular organisms over the past billion years was a consequence of the transition to a new control architecture based largely on endogenous digital RNA signals. It would certainly help explain the phenomenon of the Cambrian explosion about 525 million years ago, when invertebrate animals of jaw-dropping diversity evolved, seemingly abruptly, from much simpler life. Indeed, these results suggest a general [mathematical, within that, metrical and fractal geometrical - AJP] rule with relevance beyond biology: organized complexity is a function of regulatory information - and, in virtually all systems, as observed by Marie E. Csete, now at Emory University School of Medicine, and John C. Doyle of the California Institute of Technology, explosions in complexity occur as a result of advanced controls and embedded networking.

The implications of this rule are staggering.We may have totally misunderstood the nature of the genomic programming and the basis of variations in traits among individuals and species. The rule implies that the greater portion of the genomes in complex organisms is not junk at all - rather it is functional and subject to evolutionary selection.


[Mattick is an outstanding experimenter with an exceptional vision. He is a leader, not necessarily because he might have said it sooner than others that "Junk" was a misnomer. (The first appears to be Boyer, see facsimile, who in the next second after Ohno argued in 1972 that "Junk" was in the human genome "for the importance of doing nothing", immediately proclaimed Ohno's -mistaken- argument "suspect" - and the ignorant misnomer gained ground not for reasons of good science but for the simplistic convenience of - temporarily(?) - disregarding the "non-genic" 98.7% of human genome.)

The brilliance of Mattick is also evident in his determination - having won a "case of vintage champagne" over the percentage of non-coding that is demonstrably "functional". Now he considers, as everybody should sooner or later, the entire "numbers' game" good for an occasional betting, but irrelevant. Instead, towering over most, actually shows WHAT kind of "genome regulation" the "non-coding RNA" might be doing, opening the door to software-enabling unifying solutions, suitable for industrialization of genomics. After all, DNA transcription is very energy-consuming (in each and every cell of a differentiated organism), and not only "natural selection" would eliminate "junk" if it would be there "for the purpose of doing nothing" as Ohno erred, but the transcription of DNA into RNA, if it is not "coding" would be a waste of energy that organisms would could use more purposefully. - AJP]

Metaphores of Fractal Dynamics to Multi-dimensional Systems (Public domain hints)

This columnist (AJP) is on record since priority date of Aug. 1st, 2002 that the genome (not just its "genic" parts) is fractal and growth of fractal organisms is regulated by a multivariate fractal recursive iteration [the decade of fractogene]. FractoGene theory and thus utility have been built ever since based on mathematical rigor, "fractal genome governs growth of fractal organisms".

As glanced in the above "timeline", the Intellectual Property of FractoGene, flying into the face of the two dogmas (Junk and Genes plus Central Misunderstanding), was too early for publication at the emergence of concept and its utility (2002) thus was filed to USPTO. After slightly over a decade, the parent-patent is now available by appointment for consultations possibly leading to licensing of FractoGene (improvements on "best methods" of utility after submission of application are not revealed).

Now, after a decade of a tumultuous paradigm-shift, the author realizes even more acutely than at the time of "Eureka-moment" (2002), how frightening it could be to introduce the "double heresy of FractoGene". The author expresses anew that scientific progress over patently obsolete dogmas was not intended as an offense against anyone. It was intended as an effort to help those hundreds of millions of people suffering from genome regulation diseases (with cancer is the second and perhaps most dreadful killer, and schizophrenia, autism, auto-immune diseases and other genome (mis)regulation syndromes are enormously challenging). Also, it was to help develop a new generation of "antibiotics" and defense-agents by shutting down harmful extrinsic genomes, with a mathematical understanding of genome regulation permitting functioning and non-threatening (synthetic) genomes, among others to unleash innovative solution for energy, agriculture. With genome sequencing having become a commodity (with a growing glut that threatens to suffocate the ecosystem of unfolding industrialized genomics), software-enabling mathematical understanding of "genome regulation" is seen as an intellectual/entrepreneurial/social challenge calling for cohesive collective breakthrough unprecedented in history (perhaps with the exception of quantum physics leading to nuclear age).

For the author's "fair share" invested over the decade in human life and own resources, IP beyond the issued patent can not be freely disclosed. However, to provide ALREADY PUBLIC DOMAIN "hints" to metaphorically illustrate how fractals (not unlike the "Cambrian explosion") escalate in complexity when one proceeds from the "linear integers" (Fibonacci numbers) to "2D plane of real- and imaginary numbers" (Mandelbrot set), and to the "3D analogue of Mandelbrot set, Mandelbulb", see the following public domain YouTube/Wikipedia materials, and consult publications of the Geometrical Unification of Genomics and Neuroscience, and Industrialization of Genomics, with numerous independent "proof of concept" experimental results referenced, how "fractal defects" cause misregulation of genome function; making clinical applications e.g. in cancer therapy available.

Readers may wish to view a truly spectacular 54-minute NOVA special on fractals first. Not only to learn more about fractals, but perhaps to arrive at a similar impression of my "Eureka-moment" on FractoGene, 8,280,641 ("My God! Of course!") - though a key stipulation for any US patent is the "non-obviousness" (prior to the "how come I did not think of this before?" realization).

For a step-by-step approach, a first and simplest specific metaphorical illustration shows that a self-sustained recursive algorithm can "regulate" by a single number an easily defined stream of positive integers (called Fibonacci numbers). The algorithm F(n)=F(n-1)+F(n-2) is utterly simple. Starting from 0 and 1, let the next marked number be the sum of the previous two. Thus, after 0 and 1, the next number will be 1 (again), and likewise by the same recursive iteration we'll mark along the way 2, 3, 5, 8 and so on. The marked integers are known in Western cultures as the Fibonacci-series (India knew all this in ancient sanskrit prosody ages before, in ancient times). What is so "regulated" about the (marked) Fibonacci-series? It is most beautifully stable, since after rapid convergence of the iterative recursion you can even forget the very simple "rule" ("add the previous two numbers"). Suffice to know ANY Fibonacci-number, you can independently generate the next one - just multiply the given number by a constant (called Golden Ratio, PHI=1.6218...). The ratio is so stable that after the first dozen iterations it zooms to a 4 decimal digit precision.

[View Fibonacci YouTube here]

As the above montage from the public domain YouTube shows (the long presentation by Keith Devlin is introduced by Jim Simons, see lower left) that a single number ("Golden Ratio") can "regulate" not just a series of numbers, but also can "optimize" e.g. fractals; such that the branchlets optimally cover, without overlap, a surface. This can help illuminate the utility of FractoGene; since e.g. a "wrong number" for the governing ratio would result in pathology of e.g. a neural dendritic tree.

Let's go from the line of integers to the 2-dimensional plane, to arrive at the best known and most beloved fractal, the "Mandelbrot set". Again, the algorithm just could not be simpler; Z(n)=Z(n-1)^2 +C. (To generate a new number, the previous should be squared, adding a C constant, see a still picture from the (NOVA special) public domain YouTube. (where C is a constant, but the non-mathematically minded viewer may gloss over the subtlety that Z is a complex number, thus the zillions of subsequent points are on the 2D plane erected by the two axes of real numbers and imaginary numbers):

[View NOVA Special on fractals, also explaining the Mandelbrot set here].
We all have seen (or can view in the NOVA special YouTube) the mind-boggling "dynamics" of "self-similar repetitions" occurring at any resolution of "zoom". If one encounters such an "incredibly complex-looking dynamism" may really wonder "can we ever solve what makes it so miraculous?". ("Complexity is the mind of the bewildered" - the Mandelbrot set arises from a simple algorithm; "There is nothing simpler than a problem solved", said Faraday - AJP]

Now let us leap one step further. What could be the analogue of a 2D Mandelbrot set in THREE DIMENSIONS?? Is the unfolding 3D time-process even more mind-boggling?? YOU BET!

[View the "Animated Mandelbulb" vimeo in this blog].
Above is a still-frame from the Public Domain YouTube of the "Mandelbulb" , see a good description what it is, in this public domain explanation. Yes, looking at the "uncontrolled" burgeoning three-dimensional "structure" one can be outright frightened how "similar" it looks - to an "uncontrolled growth called cancer"!

For those who think we can win WWII (the second war against cancer, after Nixon's first hundred billions of dollars thrown at the menace) one tends to agree with David Haussler's 4-minute video (with transcript) : "It’s not comprehensible by an unaided human mind, but it would be with the power of a computer-aided analysis".

Computer power is plentiful, but computers do not understand "knowledge"; can only be programmed by algorithms. - Consult Pellionisz, by appointment; holgentech_at_gmail_dot_com or Four-Zero-Eight 891-7187.

Francois Jacob, Nobelist with Monod and Lwoff in 1965 for Operon gene regulation dies at 92

New York Times
Published: April 25, 2013

François Jacob, left, and Jacques Monod in 1971. They helped discover how genes are regulated.

Dr. François Jacob, a French war hero whose combat wounds forced him to change his career paths from surgeon to scientist, a pursuit that led to a Nobel Prize in 1965 for his role in discovering how genes are regulated, died on April 19 in Paris. He was 92.

The French government announced his death.

Dr. Jacob said he had been watching a dull movie with his wife, Lysiane, in 1958 when he began daydreaming and was struck with an idea of how genes might function. “I think I’ve just thought up something important,” he told her [See excerpts below from his Biography on his Nobel "Eureka Moment" - AJP].

Seven years later, Dr. Jacob shared the Nobel Prize in Physiology or Medicine with Dr. Jacques Monod and Dr. André Lwoff, his colleagues at the Pasteur Institute in Paris, for their discovery that cells can switch on and switch off certain genetic information. Their work, which focused on bacteria, increased understanding of how genes could be selectively deployed by an organism. “They’re all there in the egg. But how does the egg know when to turn from one type of cell type to another?” Richard Burian, a professor emeritus of philosophy and science studies at Virginia Tech, said of the question asked by Dr. Jacob and his colleagues. “There must be some kind of signal.”

Their discovery, considered central to the development of molecular biology, offered new insight into how people inherit traits, how they grow and develop, and how they contract and fight diseases.

“The discoveries have given a strong impetus to research in all domains of biology with far-reaching effects spreading out like ripples in the water,” Sven Gard, a member of the Nobel Committee for Physiology or Medicine, said when the three men were awarded the prize, according to the Nobel Web site. “Now that we know the nature of such mechanisms, we have the possibility of learning to master them.”

François Jacob was born on June 17, 1920, in Nancy, France. He had begun studying medicine when World War II began. France was occupied by Nazi Germany’s forces in 1940, and Dr. Jacob, whose grandfather had been a four-star general in the French Army, fled to England by boat in 1940 and joined the Free French Army led by Charles de Gaulle.

He worked as a medical officer and fought with Allied forces in North Africa and in France, where he was seriously wounded in a German air raid. He received numerous high military honors, including the Cross of War and the Cross of the Liberation.

Dr. Jacob returned to medical school after the war, completing his studies in 1947, but damage to his hands from his combat wounds prevented him from becoming a surgeon. At a loss for what career to pursue, he was encouraged to try research and, though he had little training in it, he found a place at the Pasteur Institute in 1950. (He earned a doctorate in science at the Sorbonne in 1954.)

Working with other scientists at Pasteur, he quickly distinguished himself by identifying how bacteria adapt to drugs and bacterial viruses. It was a time of great discoveries in genetics. In 1953, James D. Watson and Francis Crick published their groundbreaking work on the double helix structure of DNA. At the Pasteur Institute, Dr. Jacob began working with Dr. Monod, and they soon had a breakthrough of their own. By means of a series of innovative experiments, they established that the transfer of genetic information could be controlled through two different types of genes, regulatory genes and structural genes, with the former controlling the expression of the latter.

“What mattered more than the answers were the questions and how they were formulated,” Dr. Jacob later wrote. “For in the best of cases, the answer led to more questions. It was a system for concocting expectation, a machine for making the future. For me, this world of questions and the provisional, this chase after an answer that was always put off to the next day, all that was euphoric. I lived in the future.”

Dr. Jacob became laboratory director at the Pasteur Institute in 1956 and four years later was appointed head of its new department of cell genetics. In 1964, he joined the Collège de France, where a chair of cell genetics was created for him.

Dr. Jacob married Lysiane Bloch, known as Lise, a pianist, in 1947. They had four children. After her death, he married Geneviève Barrier in 1999. Information about survivors was unavailable.

Dr. Jacob’s inquiries included matters moral and philosophical as well as cellular. He once wrote that he wanted to discover “the core of life.”

“What intrigues me in my life is: How did I come to be what I am?” he wrote in his 1988 autobiography, “The Statue Within.” “How did this person develop, this I whom I rediscover each morning and to whom I must accommodate myself to the end?"


[In his biography "The Statue Within", Francois Jacob recalls his immediate perception of Crick's "Central Dogma" pp. 287-288 - AJP]:

"...the star at this London colloquium [p.286; "Society for Experimental Biology London in September 1957 - AJP] was the talk by Francis Crick. We had come across the name of Francis Crick in the notes in Nature on the structure of DNA. At the time no one in the attic had ever heard of him. Everyone, on the other hand, knew Jim Watson and his uncommon personality. So Crick had seemed like some sort of residual appendage to Watson. Some months later, however, when Crick made an appearance at the Pasteur Institute to give a seminar, it was immediately clear to all that Francis was not simply Jim's appendage; that a character as strong-minded, as mentally acute had no need of a coach. Tall, florid, with long sideburns, Crick looked like the Englishman seen in illustrations to nineteenth-century books about Phileas Fogg or the English opium eater. He talked incessantly, with evident pleasure and volubly, as if he was afraid he would not have enough time to be sure it was understood. Breaking up his sentences with loud laughter. Setting off again with renewed vigor at a speed I often had trouble keeping up with. ... He had no taste for experimentation, for manipulation. But no one contributed more than he to the working out of the body of hypotheses that in the 1990s and 1660s guided experiments and made it possible to foresee the general outlines of what was to come. .. For example, the so-called sequence hypothesis, according to which the sequence of the bases in a segment of nucleic acid suffices to define the sequence of amino acids in the corresponding protein. And then, it took a sure footing, an acute sense of publicity, to baptize Central Dogma - that is to say, incontestable truth - a hypothesis that was unsupported by any serious argument, but that, restricting the limits of the possible, sharpened the field of research. According to the Central Dogma, the information defining the sequence could go from nucleic acids to protein, but never in the reverse direction. Once in the protein, it could never get back out: neither back to the nucleic acids nor to other proteins. If, then, it was necessary to find the details of the machine that enabled the nucleic sequence to translate into a protein sequence, it was pointless to look for another machine for a reverse translation. Such a machine did not exist. To go straight to the point, not to worry about details, at least to begin with; such struck me as the lesson to be drawn from Francis's talk."

[Dr. Jacob also recalls in his Biography his "Nobel Eureka-moment", p. 297 -AJP]

"Late July 1958. A Sunday in Paris. The children have gone off on vacation. Lise and I have stayed at home. She is at the piano in the next room, practicing a sonata. For my part, I am trying to get started on a lecture that I must give in New York... With no desire to write this lecture, I go round in my study, chewing over vague hypotheses, possible experiments. At the end of the afternoon, fed up, weary, we decide to go to the movies. A film of no interest. Slumped in my seat, I dimly perceive in myself associations that continue to form, ideas for proceeding. .. I am invaded by a sudden excitement mingled with a vague pleasure. It isolates me from the theater, from my neighbors whose eyes are riveted to the screen. An suddenly a flash. The astonishment of the obvious. How could I not have thought it sooner? Both experiments - that of conjugation done with Elie on the phage, erotic induction; and that done with Pardee and Monod on the lactose system, the PA JA MA - are the same! Same situation. Same result. Same conclusion. In both cases, a gene governs the formation of a cytoplasmic product, of a repressor blocking the expression of other genes and so preventing either the synthesis of the galactosidase or the multiplication of the virus. In both cases, one induces by inactivating the repressor, either by lactose or by ultraviolet rays. The very mechanism that must be the bases of the regulation."

Celebrate the Unknowns

Comment by Philip Ball
Nature, 25 APRIL 2013
VOL 496 | NATURE | 419

On the 60th anniversary of the double helix, we should admit that we don’t fully understand how evolution works at the molecular level, suggests Philip Ball.

This week’s diamond jubilee of the discovery of DNA’s molecular structure rightly celebrates how Francis Crick, James Watson and their collaborators launched the ‘genomic age’ by revealing how hereditary information is encoded in the double helix. Yet the conventional narrative - in which their 1953 Nature paper led inexorably to the Human Genome Project and the dawn of personalized medicine - is as misleading as the popular narrative of gene function itself, in which the DNA sequence is translated into proteins and ultimately into an organism’s observable characteristics, or phenotype.

Sixty years on, the very definition of ‘gene’ is hotly debated. We do not know what most of our DNA does, nor how, or to what extent it governs traits. In other words, we do not fully understand how evolution works at the molecular level.

That sounds to me like an extraordinarily exciting state of affairs, comparable perhaps to the disruptive discovery in cosmology in 1998 that the expansion of the Universe is accelerating rather than decelerating, as astronomers had believed since the late 1920s. Yet, while specialists debate what the latest findings mean, the rhetoric of popular discussions of DNA, genomics and evolution remains largely unchanged, and the public continues to be fed assurances that DNA is as solipsistic a blueprint as ever. [Not totally - Google Tech Talk 2008 was rather forthright, with 15,571 views to date, The Principle of Recursive Genome Function 2008 peer-reviewed science paper was downloaded by tens of thousands, with "nolo contendere" - AJP)]

The more complex picture now emerging raises difficult questions that this outsider knows he can barely discern. But I can tell that the usual tidy tale of how ‘DNA makes RNA makes protein’ is sanitized to the point of distortion. Instead of occasional, muted confessions from genomics boosters and popularizers of evolution that the story has turned out to be a little more complex, there should be a bolder admission - indeed a celebration - of the known unknowns.


A student referring to textbook discussions of genetics and evolution could be forgiven for thinking that the ‘central dogma’ devised by Crick and others in the 1960s - in which information flows in a linear, traceable fashion from DNA sequence to messenger RNA to protein, to manifest finally as phenotype - remains the solid foundation of the genomic revolution. In fact, it is beginning to look more like a casualty of it.

Although it remains beyond serious doubt that Darwinian natural selection drives much, perhaps most, evolutionary change, it is often unclear at which phenotypic level selection operates, and particularly how it plays out at the molecular level.

Take the Encyclopedia of DNA Elements (ENCODE) project, a public research consortium launched by the US National Human Genome Research Institute in Bethesda, Maryland. Starting in 2003, ENCODE researchers set out to map which parts of human chromosomes are transcribed, how transcription is regulated and how the process is affected by the way the DNA is packaged in the cell nucleus. Last year, the group revealed1 that there is much more to genome function than is encompassed in the roughly 1% of our DNA that contains some 20,000 protein-coding genes - challenging the old idea that much of the genome is junk. At least 80% of the genome is transcribed into RNA.

Some geneticists and evolutionary biologists say that all this extra transcription may simply be noise, irrelevant to function and evolution2. But, drawing on the fact that regulatory roles have been pinned to some of the non-coding RNA transcripts discovered in pilot projects, the ENCODE team argues that at least some of this transcription could provide a reservoir of molecules with regulatory functions - in other words, a pool of potentially ‘useful’ variation. ENCODE researchers even propose, to the consternation of some, that the transcript should be considered the basic unit of inheritance, with ‘gene’ denoting not a piece of DNA but a higher-order concept pertaining to all the transcripts that contribute to a given phenotypic trait3.

According to evolutionary biologist Patrick Phillips at the University of Oregon in Eugene, projects such as ENCODE are showing scientists that they don’t really understand how genotypes map to phenotypes, or how exactly evolutionary forces shape any given genome.


The ENCODE findings join several other discoveries in unsettling old assumptions. For example, epigenetic molecular alterations to DNA, such as the addition of a methyl group, can affect the activity of genes without altering their nucleotide sequences. Many of these regulatory chemical markers are inherited, including some that govern susceptibility to diabetes and cardiovascular disease4. Genes can also be regulated by the spatial organization of the chromosomes, in turn affected by epigenetic markers. Although such effects have long been known, their prevalence may be much greater than previously thought .

Another source of ambiguity in the genotype-phenotype relationship comes from the way in which many genes operate in complex networks. For example, many differently structured gene networks might result in the same trait or phenotype6. Also, new phenotypes that are viable and potentially superior may be more likely to emerge through tweaks to regulatory networks than through more risky alterations to protein-coding sequences7. In a sense this is still natural selection pulling out the best from a bunch of random mutations, but not at the level of the DNA sequence itself.

One consequence of this complex genotype-phenotype relationship is that it may impose constraints on natural selection. If the same phenotypes can result from many similarly structured gene networks, it might take a long time for a ‘fitter’ phenotype to arise. Alternatively, mutations may accumulate, free from selective‘weeding’,thanks to the robustness of networks in maintaining a particular phenotype. Such hidden variation might be unmasked by some new environmental stress, enabling fresh adaptations to emerge. These sorts of constraints and opportunities are poorly understood; evolutionary theory does not help biologists to predict what kinds of genetic network they should expect to see in any one context.

Researchers are also still not agreed on whether natural selection is the dominant driver of genetic change at the molecular level. Evolutionary geneticist Michael Lynch of Indiana University Bloomington has shown through modelling that random genetic drift can play a major part in the evolution of genomic features, for example the scattering of non-coding sections, called introns, through protein-coding sequences. He has also shown that rather than enhancing fitness, natural selection can generate a redundant accumulation of molecular ‘defences’, such as systems that detect folding problems in proteins10. At best, this is burdensome. At worst, it can be catastrophic.

In short, the current picture of how and where evolution operates, and how this shapes genomes, is something of a mess. That should not be a criticism, but rather a vote of confidence in the healthy, dynamic state of molecular and evolutionary biology.


Barely a whisper of this vibrant debate reaches the public [just click on Google Tech Talk YouTube - AJP]. Take evolutionary biologist Richard Dawkins’ description in Prospect magazine last year of the gene as a replicator with “its own unique status as a unit of Darwinian selection”. It conjures up the decades-old picture of a little, autonomous stretch of DNA intent on getting itself copied, with no hint that selection operates at all levels of the biological hierarchy, including at the supraorganismal level2, or that the very idea of ‘gene’ has become problematic.

Why this apparent reluctance to acknowledge the complexity? One roadblock may be sentimentality. Biology is so complicated that it may be deeply painful for some to relinquish the promise of an elegant core mechanism. In cosmology, a single, shattering fact (the Universe’s accelerating expansion) cleanly rewrote the narrative. But in molecular evolution, old arguments, for instance about the importance of natural selection and random drift in driving genetic change, are now colliding with questions about non-coding RNA, epigenetics and genomic network theory. It is not yet clear which new story to tell. [For Informatics experts, some of it is extremely clear. "Exons" of human DNA amount to information to specify a stamp-size jpg; plainly and painfully clear that more genomic information is needed to specify a human being. Also, all IT-savvy experts agree that "Complex System Theory" is called for. However, few identified that the mathematics of the complex system at hand is FRACTALS - AJP]

Then there is the discomfort of all this uncertainty following the rhetoric surrounding the Human Genome Project, which seemed to promise, among other things, ‘the instructions to make a human’. It is one thing to revise our ideas about the cosmos, another to admit that we are not as close to understanding ourselves as we thought.

There may also be anxiety that admitting any uncertainty about the mechanisms of evolution will be exploited by those who seek to undermine it. Certainly, popular accounts of epigenetics and the ENCODE results have been much more coy about the evolutionary implications than the developmental ones. But we are grown-up enough to be told about the doubts, debates and discussions that are leaving the putative ‘age of the genome’ with more questions than answers. Tidying up the story bowdlerizes the science and creates straw men for its detractors. Simplistic portrayals of evolution encourage equally simplistic demolitions.

When the structure of DNA was first deduced, it seemed to supply the final part of a beautiful puzzle, the solution for which began with Charles Darwin and Gregor Mendel. The simplicity of that picture has proved too alluring. For the jubilee, we should do DNA a favour and lift some of the awesome responsibility for life’s complexity from its shoulders.■

Philip Ball is a freelance science writer based in London. e-mail: p.ball_at_btinternet_dot_com

HUGO 2013, Part 1: What does it all mean?

Illumina Blog [on HUGO 2013 in Singapore]
Posted by Kahlil Lawless on Thu, Apr 18, 2013

After several days of fascinating and varied talks by a multitude of talented researchers at the Human Genome Meeting/International Congress of Genetics, my head is swimming - and I doubt that I’m the only one. Midway through the conference, we celebrated ten years since the Human Genome Project was officially completed. At the time, this milestone was heralded as the dawn of the genomic era where researchers and clinicians would be able to leverage this new level of understanding to produce incredible discoveries, and deliver significant benefits to the world. Ten years on and the discoveries have been incredible, but once again we appear to have underestimated the phenomenal complexity of biological systems and our ability to understand and manipulate them. Our fancy new tools and databases have unleashed upon us a tsunami of new information, and the question on everyone’s lips is - what does it all mean?

Sample Size of One

The first setback was coming to the realisation of how limited a resource our Human Genome reference sequence actually is, and the emphasis here is on the singular - it is one genome, compiled from several different individuals. The diversity of Earth’s 7 billion humans is not represented in this database, and the more distantly related a person is from this reference, the less useful it becomes. This problem has spawned duplicate genome projects the world over. In our region, the Pan-Asian Population Genomics Initiative (PAPGI) has tackled this issue with gusto, with collaborators from the middle east to south east Asia and everywhere in between have been generating vast datasets and public resources that will become critical reference and research tools1.

Dotting i’s and Crossing t’s

A second potential source of concern is that the human genome reference, even after 19 consecutive revisions, has proved a moving target. Each time it gets better, but still errors remain. Stephan Schuster’s presentation on the RP11 genome assembly showed more than 80 new regions not found in the reference, some containing whole genes.

We Are Not Alone...

One of the hottest emerging fields is metagenomics, as evidenced by a standing room only crowd at the HUGO session to hear Martin Hibberd proclaim that the “future is biomes”. He demonstrated a strong link between diseases such as Age-Related Macular Degeneration and eye flora, while others such as Kyu Young Song from Korea set themselves on a course to understanding the role of microbial genomes in complex diseases such as Inflammatory Bowel Syndrome (which I don’t need to see any more photos of - thank you very much).

DNA is History

Literally. The history of an organism, or even of a single cell, is indelibly inked on its DNA. Julian Parkhill from the Sanger Institute presented his sequencing results on cholera strains for the last 100 years. He was able to show that rather than independent environmental events leading to regional epidemics, virtually all strains could be traced back to strains emerging from south Asia. This analysis showed conclusively that the cholera outbreak in Haiti was not the result of earthquake-damaged sanitation systems, but rather the arrival of Nepalese peacekeepers stationed upstream of Haiti’s main river. He also demonstrated this on a smaller scale tracing transmissions of methicillin-resistant Staph aureus (MRSA) in a hospital outbreak in the UK2. On a smaller scale, the mutational variants that make such analysis possible can also be tracked within an individual over time.

Patrick Tan used comprehensive understanding of the rates and types of somatic mutation to plot the accumulation of variation within a single lifespan, and to pinpoint sudden mutational events that are significant contributors to cancer. Through studying mutation types and frequencies, they were even able to elucidate which mutagens individuals had been exposed to, and determine if these exposures were the causative agent in particular cancers. Needless to say, from here I’m now going to studiously avoid Chinese herbal remedies that may contain wild ginger, as aristolochic acid appears to confer a cancer risk equivalent of smoking ten packs a day...

One Man’s Junk is Another’s Treasure

Geneticists have been eating their words ever since the day when 99% of the genome was proclaimed to be ‘junk’ DNA. This should have become apparent the moment we found out the human genome only had 20,000 genes, far less than anyone expected. Since then, researchers have identified GWAS loci where there were no genes at all, alternative splicing, antisense, small and long non-coding RNA, DNA methylation, a multitude of chromatin regulation mechanisms, DNA-DNA interactions….the list goes on. With the benefit of hindsight, we now say “it’s not the number of genes, it’s what you do with them”, and the study of gene regulation has risen to the fore.

As John Mattick said in his talk on long ncRNA and their role in disease, “the human genome is a zip-file extraordinaire”. Decoding this is proving much more challenging than sequencing the DNA itself. Regulation is dynamic, responsive, and often unpredictable. Due to perennial changing state of organisms, and the myriad of regulatory mechanisms in play, applying a reductionist scientific approach to regulation has proved a significant challenge.

Understanding these systems requires cross-disciplinary approaches, and at HUGO this year it wasn’t uncommon to see a talk employ everything from DNA-Seq, RNA-Seq, ChIP-Seq, proteomics, microscopy, genetic engineering and everything in between to gain an understanding of a single mechanism. Joseph Takahashi’s 20-year journey to understand mammalian cellular circadian rhythms illlustrates the intense cross-disciplinary paths that lead to success.

So, Why do We Care?

At some stage, we all hope this understanding can be applied in some useful manner (at least that’s what the funding bodies are hoping, otherwise I’m sure none of the presented work would ever have been done). That was the other half of HUGO this year, and comprised many success stories from the world of applied genomics, and how the tsunami of data can be ridden successfully into clinic beach while avoiding the submerged rocks of misdiagnosis and treatment. Stay tuned for my post on HUGO Part 2 – What is it all for?

Ranganathan S, Tongsima S, Chan J, Tan TW, and C Schönbach (2012) Advances in translational bioinformatics and population genomics in the Asia-Pacific BMC Genomics 13 (Suppl 7)S1.

Harris SR, Cartwright E, Tӧrӧk ME, Holden M, Brown N, et al. (2013) Whole-genome sequencing for analysis of an outbreak of methicillin-resistant Staphylococcus aureus: a descriptive study. Lancet Infectious Dis. 13(2) 130–136.

Image courtesy of US Department of Energy Genome Program’s Biological and Environmental Research Information System


"Geneticists have been eating their words ever since the day when 99% of the genome was proclaimed to be ‘junk’ DNA". Actually, at the minute Ohno finished his "scientific conclusion" (1972) the very first question seriously doubted the validity of his "argument" that non-genic DNA can not be of any use. (See facsimile at Likewise, when Crick laud mouthed his "Central Dogma", Jacques Monod (see his autobiography) immediately discredited (laughed) his "Dogma" (his Operon, Nobel in 1965 was not followed-up for many decades). The problem is, that some of us put genomics on mathematically sound new foundation - see e.g. The Principle of Recursive Genome Function (2008), submitted almost immediately after the 2007 ENCODE admission. However, though nobody could say a word against it, there are precious few, who actually WANT to follow-through with disruptive events. (For 7 years, nobody cited "The Double Helix" - and though genome function is without the slightest doubt is recursive, perhaps a dozen workers cited over the last five years the principle itself. Now, there are over 30 independent experimental papers to show that cancers, autism, schizophrenia, etc. massively rearrange the genome that has been proven fractal, billions of dollars on "cancer therapy" are reluctant to acknowledge the breakthrough in the fear of what the paradigm-shift may harbor for some. Meanwhile, billions are wasted, and hundreds of millions die of miserable deaths. Something is not fair. - Pellionisz

Posted @ Thursday, April 18, 2013 12:12 PM by Andras J. Pellionisz

Can Cancer Cells Solve the Puzzle of Junk DNA?

Matt Ridley

The Wall Street Journal
April 14, 2013

The usually placid world of molecular biology has been riven with two fierce disputes recently. Although apparently separate, the two conflagrations are converging.

The first row concerns the phrase "junk DNA." Coined in 1972 by the geneticist Susumu Ohno, it is an attempt to explain why vast stretches of animal genomes, far more in some species than in others, seem to serve no purpose. Genes of all kinds and their control sequences make up maybe 9% of the human genome at the very most. The rest may be nonfunctional "junk," mainly there because it is good at getting itself duplicated. Yet the phrase has always caused a surprising amount of offense. Reports of the discrediting of junk-DNA theory have been frequent [This is the easy part - see this column since 2004 - AJP].

Why does it matter? [This is eminently doable, as well - requires a twist, however - AJP]. Partly because scientists want to know if they are right to focus on part of the genome, ignoring the rest, but mainly because the issue tests an evolutionary theory about how DNA sequences can proliferate even if they do not benefit the body.

Late last year, a huge team of scientists running a consortium called Encode published an analysis of the human genome that they said showed some kind of activity in 80% of the genome. They later conceded that perhaps 20% is actually functional, yet insisted the phrase "junk DNA" could now be "totally expunged from the lexicon."

According to Dan Graur of the University of Houston and his colleagues, even this is a wild overestimate—not least because it uses a "causal role" definition of function that is all wrong, as if you were to describe among the heart's functions adding 10.5 ounces to the weight of the body, along with pumping blood. After a few exchanges, the Encode team leader Ewan Birney conceded that in hindsight, the team overstated its conclusions. But he added that whatever the interpretation, the Encode data are sound.

Are they? Here's where the junk-DNA row meets the other conflagration in molecular biology. All the Encode data were derived from cancer-cell lines. [See comment below! - AJP]. To describe human cancer cells as having the human genome looks increasingly unwise. Most cancer cells have extra chromosomes, fragmented and rearranged DNA and unusual patterns of gene activity.

As if to illustrate the point, last month a consortium of scientists based in Heidelberg, Germany, analyzed and sequenced the genome of one type of HeLa cell, an immortal laboratory cell line widely used since 1952. They described a genome that looks like a bomb has gone off in it. There are three copies of most chromosomes, yet only one copy of many genes. Hefty chunks have been reshuffled to other chromosomes, and some chromosomes have suffered from "chromothripsis," which one of the scientists describes as being "blown apart and stuck back together in a random order." A person with this genome could never be born.

Yet—and here's the source of the controversy—the HeLa cell line was derived from the tumor that killed a poor, black tobacco farmer named Henrietta Lacks in Baltimore in 1951. As Rebecca Skloot has documented in a remarkable best seller ("The Immortal Life of Henrietta Lacks"), the medical community never got her consent and treated her family with tactless disrespect for years—until Ms. Skloot's book began to make a difference.

Not enough of a difference, apparently. The German team did not seek the consent of the Lacks family before publishing the HeLa sequence, claiming it revealed nothing specific about Ms. Lacks's own genome. "Your claim is so wrong that I don't know where to start," replied one geneticist. The sequence has since been unpublished.

So here's the paradox: A cancer genome like HeLa may not be sufficiently representative of human genomes to resolve the junk DNA question, but may still give away private information about the human being from whom it derived.

[The towering genome publicist Matt Ridley could not be reached to creatively resolve what he believes as a paradox of ENCODE. Their 2012 report stated "We integrate results from diverse experiments within cell types, related experiments involving 147 different cell types" (see list online for ENCODE CELL TYPES ) . Many, but certainly not "all" genomes investigated by ENCODE were cancerous. Therefore, since after the 2007 and now 2012 ENCODE conclusions many workers focus on the best continuation, this columnist submits that MATHEMATICAL (see article below...) comparison of the "Junk" of control versus "Junk" of cancerous cells is rather revealing. A couple of dozen such efforts are referenced in this recent review; moreover how The Principle of Recursive Genome Function might be violated by "fractal defects" is explained. Thus, perhaps a better title would have been "How 'Junk DNA' Solves the Puzzle of Cancer" - Pellionisz]

Grappling with Cancer

Editorial by Edison T. Liu
Science 29 March 2013:
Vol. 339 no. 6127 p. 1493
DOI: 10.1126/science.1237835

One of the greatest challenges in the study of cancer has been confronting the mindset that the disease is too complex to address effectively: too many tissue types, too many etiologies, too much genetic chaos. [While the ordinary meaning of "chaos" is "disorder", in the mathematical sense of nonlinear dynamics "chaos" and "fractal" can be a strictly deterministic or probabilistic, albeit not trivial ORDER - AJP]. In the 1970s, the oncogene concept provided temporary relief from this angst, because it was thought that a limited number of genes (proto-oncogenes), when activated through mutations, might turn a normal cell into a cancerous one. But what briefly seemed tidy quickly became messy again with the discovery of other classes of genes that normally protect against cancer. Most recently, advanced genome sequencing technologies have revealed a surprising fact: Every tumor contains hundreds to thousands of mutations, most of which affect only a small percentage of the cancers in any tumor type (see the Review by B. Vogelstein et al., p. 1546). In addition, the high degree of cancer cell heterogeneity in each tumor suggests that we are studying a moving target that can readily dodge treatments through continual mutation. And the genetic uniqueness of every cancer raises the question of whether standardized cancer treatment protocols can ever achieve broad efficacy.

The good news is that we are now armed with dramatically more information and substantially more powerful tools to grapple with cancer's complicated nature. By necessity, past research focused on one gene at a time, and so our mindsets were necessarily restricted. Now that we can access the complete, precise genomic information about any cancer, future advances will depend on exploiting the natural genetic complexity of this disease. This will require much more than annotating lists of mutations. What is needed is the ability to detect all of the relevant components of a system and describe the complexity observed in a mathematical manner so that models can be computed. We then need to reconstruct this complexity in experimental systems and perturb those systems to test their characteristics. Ultimately, this could reveal higher-order rules that explain the possible actions of each particular cancer in terms of its gene networks.

Going forward, a transition to a systems dynamics view requires a different empiricism. A major change will be viewing each type of cancer as an experimental system by itself. Rather than analyzing many thousands of tumors somewhat superficially, we may need very deep analyses of a few well-characterized tumors, using multiple approaches for which diverse data sets can be integrated (complete DNA and RNA sequences, whole-genome epigenetic information, etc.). The tumors to be analyzed can be selected on the basis of their exceptional differences in behavior, such as sensitivity versus resistance to chemotherapy, and aggressiveness versus latency. The analyses required to validate the behavior of that cancer could be aided by using genetically engineered mouse models and patient-derived xenografts. The goal would be to generate a “whole-system” understanding of each cancer and provide a more nuanced approach to developing therapies.

But perhaps this view of each type of cancer as a unified but static unit is too simplistic. Instead, each cancer could be considered an evolutionary experiment involving a genetically plastic population of cells undergoing selection within a tumor. The genomic composition of single cells in an individual cancer before and after treatment may best uncover the genetic fluxes that lead to therapeutic resistance. Thus, a small group of individuals entering a “proof-of-concept” study could have their tumors genomically analyzed, the tumors' therapeutic sensitivity tested in patient-derived xenografts, and the in vivo tumor clonal response to a tailored anticancer treatment monitored by detailed analyses of circulating tumor DNA.

Which experimental approach will be the best for advancing understanding of cancer biology and improving clinical outcomes is, of course, debatable. But we are very fortunate to be in a position today to test each of the many possibilities.

GPU Advances Genomic Science - A Possible Nobel Prize?

3/25/2013 by: Gil Russell

Lieberman Aiden’s research utilizes a branch of mathematics first described by David Hilbert in 1891 – Hilbert space-filling curve is a continuous fractal space-filling curve (now called Hilbert’s curve). Lieberman Aidan has added the third dimension and applied a function, which computes the most likely fold combination on the genome of a given chromosomal ordering...

...Another discovery occurred when the results of assembling the genomes by computation revealed that they naturally formed into compartmentalized departments known as “fractal globules” versus “equilibrium globules”, which was formerly the accepted theory. Lieberman Aidan’s theory advances this idea further with the discovery of the “fractal globule” which unfolds without knotting, remains organized on unfolding and follows a -1 power rule...

What we discovered is two really interesting facts:

One, is that as genomes specialize in function they’re actually folding. As cells specialize, the genomes inside them are actually folding into new configurations that enable that cell to be in one state versus another.

And, (two) we also got a sense of how folds like the fractal globule can enable the genome to keep this unbelievably long stretch of information fully accessible at all times whenever it is needed.

...learn a lot more about how genomes fold and unravel a lot more of this mystery of what is going on when a cell specializes and how does that go wrong in a disease like cancer.

...Simply put, it takes 6 to 7 years to develop and test a complex algorithm before deciding whether it is even marketable

...A complete understanding of cancer and its underlying causes now does not seem to be quite so far away as it did just a week ago. In fact, we are siding on the optimistic side that it could come a lot sooner..

[Some readers may wonder if GPU technology, or Hilbert (1891) might be nominated by this optimistic piece of journalism for a Nobel. Regrettably, neither is likely to pass the scrutiny of Stockholm, as there is no category for "technology" and scientists must be alive. Breakthroughs towards understanding genome (mis)regulation (e.g. in cancers), however, are highly likely to be peppered by Nobels all along (how many was received for developing quantum physics, when the splitting of the atom flew in the face of the central dogma that "atom" is the smallest unit that "can not split"?). Prize and/or Progress, another point readers may wonder about why all (coding or not :-) bits of the "long stretch of [DNA] information" should be "fully accessible at all times whenever it is needed"? A dedicated copy of the manuscript of The Principle of Recursive Genome Function" (2008, elaborating the FractoGene concept and utility of algorithm about 6 years after its priority date of 2002) was put in the hand of Dr. Lander in the fall of 2007 (UCSF lecture). With ENCODE 2007 just weeks ago concluded, the classic dogmas no longer held - recursive (fractal) algorithms were no longer a "lucid heresy". In the same week ENCODE 2012 concluded once more (with 350+ top scientists as co-authors in 30 leading articles), the FractoGene patent-utility was issued. Having tested the core algorithms for so many years, implementation in hospital setting in the WWII against cancers is an opportunity explored as we speak - Pellionisz, holgentech_at_gmail_dot_com]

Complete Genomics acquired by BGI of China on Sequoia Capital in Silicon Valley, USA

Dream Driven: Exclusive Interview with Dr. Jun Wang, Executive Director of BGI

ChinaBio Today
publication date: Mar 19, 2013

author/source: Richard Daverman, PhD|

ChinaBio® Today recently had the chance to interview Dr. Jun Wang, a co-founder of China’s sequencing giant, BGI-Shenzhen. Dr. Wang was named Executive Director of the company at the young age of 32. The company works with many of the big pharma and has established several major international partnerships. The driving force behind these relationships, according to Dr. Wang, is always the science.

“We are a dream-driven organization,” he says. The dream is the promise of genomic science to improve human life, and BGI seems willing to enter any partnership that will advance genomic science, even if it doesn’t necessarily represent a profit opportunity.

In 2012, Dr. Wang was named one of “Nature’s 10: Ten People Who Mattered this Year,” an international group of scientists selected by Nature who are making a major impact in life science.

BGI got its start in 1999, when it participated in the Human Genome Project, contributing 1% of the work. At the time, it was known as Beijing Genomics Institute. Since then it has moved its headquarters to Shenzhen and become known as BGI. It has also grown into the world’s largest sequencing company, with many “firsts” in its short 13-year history.

One of these is the acquisition of Complete Genomics, the first acquisition of a public US company by a Chinese firm to date, and an indication of the increasing globalization of the Chinese life science industry. The acquisition was finalized on March 18, 2013.

A special thanks to Dr. Samantha Du, Managing Director of Sequoia Capital China, for helping arrange the interview. Sequoia recently participated in BGI’s $222 million capital round in September, 2012, which helped fund BGI’s acquisition U.S. Complete Genomics.

ChinaBio: Dr. Wang, I read your biography and was very impressed by your background. You have accomplished a great deal at BGI in a very short period of time. How did you get started with BGI?

Dr. Jun Wang: I joined the team before BGI started. I was the one doing the computing work at the institute, taking care of data analysis, hardware and software and that sort of thing.

ChinaBio: You were heading up the bioinformatics side of things initially. Your role has expanded pretty significantly since then.

Dr. Jun Wang: At that time, BGI was basically in Beijing and it had a subsidiary in Hangzhou. I was head of the Hangzhou center for one year and then headed the Beijing office for another two or three years. I became the Executive Director of BGI in 2008.

ChinaBio: How would you say BGI has changed your life?

Dr. Jun Wang: In my bachelor’s work, I was working on artificial intelligence. That also is a multi-disciplinary field that is based on computing science, biology and mathematics. At the time, the human genome project was an interesting niche in my career. We didn’t know the future when we started. We formed BGI by ourselves and were going to try to do 1% of the project. After we finished the project, a lot of people asked us what would be next step.

We are the true believers, believing that genomics leads to a new future, a new world, that genomics will change a lot of things. We have to prove that. We have to prove that genomics will be useful. We want to do something that is good for society. We know genomics technology will change the world, but we have to prove it. We want ordinary people to have the services and products that come from genomics knowledge.

ChinaBio: You do whole genomes of individuals, but aren’t you focused on doing much deeper science?

Dr. Jun Wang: We are doing prenatal testing for Down’s syndrome and deafness, for example. So people can take advantage of BGI now. There is a big difference biotech and IT. They both want to change world. But biotech must know the world before it can change the world. It is important to bring the understanding of the human genome down to DNA level or molecular level. Based on that, you can apply the findings to ordinary life. We know the gene and phenotype relationship of Down’s syndrome. We can test maternal blood for that, test the genes and offer the value of genomic knowledge. This is just one example of what can be done. We know the biology and so we can make a difference in ordinary people’s lives.

ChinaBio: When I was looking back at BGI’s accomplishments over the past thirteen years, there is quite a list, starting with the 1% of the human genome, and now you have over 3,000 employees in China and the US.

Dr. Jun Wang: We have close to 5,000 employees now.

ChinaBio: And looking at your list of locations, you have many locations in China, including Beijing, Shanghai, Hangzhou, Wuhan, Shenzhen, plus Boston and other locations in the US.

Dr. Jun Wang: Our headquarters is in Shenzhen. Our international headquarters is in Hong Kong, but those two campuses [Shenzhen and Hong Kong] are just a half hour’s driving apart. We have lots of centers in China. We actually cover most major cities in China. We have two labs in the US: the east coast is Children’s Hospital of Philadelphia, and west coast is UC-Davis. We also have a lab in Copenhagen.

ChinaBio: How have you been able to grow so quickly? Is there a specific business model behind that that has allowed you to grow?

Dr. Jun Wang: First of all, we are not a profit-driven institution. We have efficient needs to set up a lab or office where we will do work. At these locations, people have research needs or healthcare needs – they need us to work with them and to develop something useful. In Copenhagen, we have several big projects with Danish researchers, so we set up a lab. In Philadelphia, the Children’s Hospital of Philadelphia wanted more clinical services for newborn babies in the future and it wanted to do research on children’s disorders, so we needed a lab there.

So basically, we are not profit-driven, but goal-driven or dream-driven. We have a dream together. We have projects together and we are going to work together, so we need a lab. In most cases, we send back samples to Hong Kong. Then they can perform the experiments. That is also a model. We don’t really care what kind of model we are using, but we care about getting the job done most efficiently.

ChinaBio: I like the expression dream-driven. It’s a great way of describing what you are doing. One of the reasons you’ve been able to accomplish all this in such a short time would seem to be because of your government support. The China government has given, or committed, billions to BGI, which makes it easier to do the work. Now you have raised $222 million from VCs, including Sequoia Capital China, and we know Sequoia well enough to know they are going to expect some return on their investment. Are you going to have to change how you operate in the future because of this? Will you have to be profit-driven as opposed to purely dream-driven?

Dr. Jun Wang: First of all, I have to clarify. We didn’t really receive billions of dollars from the government. We have received loans from commercial banks in China. They don’t give the money for free; we have to pay them back. We are not a government-funded institution, but a private one. We do also receive research grants from the central government. They are competitive grants. In the China system, people could get them, if they are competitive enough. And we are getting research grants from our research entities. But again, that doesn’t mean we are government-funded institute.

ChinaBio: You’re right. If you look at what’s been published, it seems like BGI is dependent on government support.

Dr. Jun Wang: We are one of the few institutions in China research that [is making a profit and thus] also pays tax. The after-tax profits are used to fund research. We are putting hundreds of millions of dollars into research. We could become rich. But we don’t think that way. We invest all the money back into research because we want to do good things for society. We have bigger dreams. So to clarify, in regards to the VCs like Sequoia, the reason we are doing this fund raising is we needed the money to acquire a US public company called Complete Genomics.

There are different parts to BGI. We have research parts like BGI Research, BGI Tech Service, BGI Healthcare, BGI Agriculture to do molecular breeding, and we recently started an Environmental Protection division to reduce carbon emissions, lower water waste and other environmental work.

ChinaBio: You mentioned Copenhagen University, Children’s Hospital of Philadelphia and UC-Davis. You have been very active with cross-border partnerships with other research institutes and hospitals, such as Johns Hopkins, University of Edinburgh, and Autism Speaks, among others. These are probably dream-driven projects, I guess, and these bring in scientific value, but do they also bring profits to BGI?

Dr. Jun Wang: Lots of them are pure scientific collaborations. Genomics is international. We can’t do it all. We need all kinds of expertise all over the world to do the job. Doing scientific research has no national borders; scientists can talk freely anywhere. So we talk to each other freely. If we have a common goal or dream, we can pool all our research together to do a great project together.

ChinaBio: With Children’s Hospital of Philadelphia, where you are working to develop a more effective therapy of sub-types of pediatric brain tumors. Will you be focusing more on rare disease and individual medicine? Is this a corporate strategy to move toward rare diseases?

Dr. Jun Wang: Very rare tumors are often inherited, and they’re often easier to detect compared to other tumors. BGI has different groups working on different projects, but we don’t want to emphasize one area over another.

ChinaBio: What about the data that comes out of all this research? You have amassed a tremendous amount of data over the years. Is that something you plan to leverage going forward and maybe develop new diagnostic tests or identifying maybe other applications for new drugs?

Dr. Jun Wang: Lots of the data have been published. All of the research is publicly available. Sometimes we work with private partners, whose data must be kept private. We do that on a case-by-case basis.

ChinaBio: So, in some cases, you are building a proprietary database from the data?

Dr. Jun Wang: We are project based. We are trying to organize all of the data that BGI is developing into a central database. BGI has just announced a journal called GigaScience. The journal is coupled with a freely available database so we are trying to organize all of BGI’s data into that database.

ChinaBio: And that will be available for no cost?

Dr. Jun Wang: Yes, it will be freely available. There is also a category for projects where companies don’t want to release the data. So we respect that.

ChinaBio: You have relationships with corporate entities like Merck and Novo Nordisk and others, where that would apply?

Dr. Jun Wang: Yes, it also happens in some academic relationships with professors who want to keep their research private. We also respect that. We are flexible. But for ourselves, we want to share as much data as possible because the whole genomics world needs to be shared. People have to work together on the data, mine it, and develop something good.

ChinaBio: Is this a correct to say that BGI generates data and makes it widely available to others, but does not necessarily mine it or extract the next level of value from the data?

Dr. Jun Wang: No. We absolutely will mine data. We absolutely seek to extract as much knowledge by ourselves as possible. But sometimes you can’t do it alone because your capacity or your ability is limited. We need help from others, and sometimes you want to put the data on the web to benefit society. But we will absolutely do the annotation and the mining by ourselves. Also, if you want to publish a paper, you need to mine the data. You can’t just publish the data, you need to tell the story of the data.

ChinaBio: From a business perspective, what is the value you are generating for BGI or your market, such as the maternal genetic tests you mentioned, from the data?

Dr. Jun Wang: So for a given cancer tumor, we get sequencing down to a single cell. We try to figure out the driving genes of the tumor and then discover drug targets for the tumor. In the future, we will be able to offer personalized cancer services based on that.

Another thing we are doing is associating dietary studies with different diseases, such as diabetes, so we are looking at nutritional patterns with these diseases to see how nutrition affects the metabolic process. There are a lot of scientific stories. All the data has stories behind it. And eventually those scientific stories will converge into medications in the market.

ChinaBio: Getting back to your corporate relationships with big pharmas like Merck and Novo Nordisk, is that what you are doing with them, identifying opportunities for new drug development?

Dr. Jun Wang: These are strategic partnerships. We are trying to develop something useful for the next generation of pharmaceutical solutions.

ChinaBio: Can you be more specific? Are these relationships focusing on personalized medicine, for example?

Dr. Jun Wang: It’s really all related to how to use new kinds of drug solutions based on the genomic data that has been discovered.

ChinaBio: With respect to the acquisition of Compete Genomics, the company was supposed to be a profitable company, but they didn’t make it. The two benefits of the acquisition would seem to be their presence in the US and CG’s technology. Is that right?

Dr. Jun Wang: We already have a presence in the US, so we didn’t need to buy CG for that. It was mostly the technology and their R&D [capabilities]. But, once again, it is because we share the same dream. They want to sequence one million human genomes. And we want to do that too. And we believe that with the technology and BGI’s downstream capability, we can work together for that.

ChinaBio: You have developed a very impressive array of data that spans agricultural, plants and microbes. In the future, will you focus on human genomic questions or what area do you see as future direction?

Dr. Jun Wang: We think the other areas are also important and we have subsidiaries for each, though we expect healthcare will be important and also agriculture.

ChinaBio: In your early years at BGI, how did you initiate the contact with the human genome project and how did you convince them that you were capable? After all, you were the only participant from a developing country.

Dr. Jun Wang: Maynard Olson at the University of Washington was one of the people behind the human genome project, and two co-founders of BGI graduated from there. That was an easy go for BGI to be part of the Human Genome Project. It was important for the project to be international. The idea was “We do it together, we share it together.” Everybody owns the human genome. Everybody shares the outcome of the human genome. Everybody sequenced the human genome together.

ChinaBio: The whole world of genomics is evolving very rapidly. Where do you see BGI in five or ten years?

Dr. Jun Wang: This is a long journey for BGI. We don’t have a very specific definition for what we should achieve in five or ten years. We want to develop something good for society. We want to use our genomics technology to do the job. We will continue to work in all genomics areas and develop as many products as possible.

But we do have some specific goals for healthcare, agriculture, BGI Research and BGI Tech in mind. We will continue on this very long journey. We are dream-driven and dreams are not that easy to make true.

ChinaBio: What about you personally – do you have goals for yourself in five or ten years?

Dr. Jun Wang: I don’t really separate my personal ego from BGI’s goals. I have to think of the two together.

ChinaBio: Dr. Du, let me direct the final question to you. Dr. Wang has a very long-term perspective and, as he says, is dream driven. But VCs have limited life for their funds. What is Sequoia expecting from BGI in terms of return?

Dr. Samantha Du: That’s a billion dollar question. We share their dream. We think the company has a lot of promise and a big future, and we will be very patient in working with them, not only for the dream but the return for the investors.

Disclosure: none.

[There is a complex set of issues, thus this columnist will not publicly comment on the interview. Andras Pellionisz, inventor & developer of the FractoGene Patent & Trade Secrets Portfolio can be consulted at HolGenTech_at_gmail_dot_com]

A Genetic Code for Genius? In China, a research project aims to find the roots of intelligence in our DNA; searching for the supersmart.

Wall Street Journal

February 15, 2013


At a former paper-printing factory in Hong Kong, a 20-year-old wunderkind named Zhao Bowen has embarked on a challenging and potentially controversial quest: uncovering the genetics of intelligence.

Mr. Zhao is a high-school dropout who has been described as China's Bill Gates. He oversees the cognitive genomics lab at BGI, a private company that is partly funded by the Chinese government.

At the Hong Kong facility, more than 100 powerful gene-sequencing machines are deciphering about 2,200 DNA samples, reading off their 3.2 billion chemical base pairs one letter at a time. These are no ordinary DNA samples. Most come from some of America's brightest people—extreme outliers in the intelligence sweepstakes.

The majority of the DNA samples come from people with IQs of 160 or higher. By comparison, average IQ in any population is set at 100. The average Nobel laureate registers at around 145. Only one in every 30,000 people is as smart as most of the participants in the Hong Kong project—and finding them was a quest of its own.

"People have chosen to ignore the genetics of intelligence for a long time," said Mr. Zhao, who hopes to publish his team's initial findings this summer. "People believe it's a controversial topic, especially in the West. That's not the case in China," where IQ studies are regarded more as a scientific challenge and therefore are easier to fund.

The roots of intelligence are a mystery. Studies show that at least half of the variation in intelligence quotient, or IQ, is inherited. But while scientists have identified some genes that can significantly lower IQ—in people afflicted with mental retardation, for example—truly important genes that affect normal IQ variation have yet to be pinned down.The Hong Kong researchers hope to crack the problem by comparing the genomes of super-high-IQ individuals with the genomes of people drawn from the general population. By studying the variation in the two groups, they hope to isolate some of the hereditary factors behind IQ.

Their conclusions could lay the groundwork for a genetic test to predict a person's inherited cognitive ability. Such a tool could be useful, but it also might be divisive.

"If you can identify kids who are going to have trouble learning, you can intervene" early on in their lives, through special schooling or other programs, says Robert Plomin, a professor of behavioral genetics at King's College, London, who is involved in the BGI project.

But critics worry that genetic data related to IQ could easily be misconstrued—or misused. Research into the science of intelligence has been used in the past "to target particular racial groups or individuals and delegitimize them," said Jeremy Gruber, president of the Council for Responsible Genetics, a watchdog group based in Cambridge, Mass. "I'd be very concerned that the reductionist and deterministic trends that still are very much present in the world of genetics would come to the fore in a project like this."

Mr. Zhao is a phenomenon in his own right. In addition to his genetics wizardry, he says his near-fluent English is self-taught. His career as a geneticist began quite humbly—with the cucumber. In 2007, he skipped afternoon classes at his school in Beijing and started an internship at the Chinese Academy of Agricultural Sciences.

He cleaned test tubes and did other simple jobs. In return, the graduate students let him borrow genetics textbooks and participate in experiments, including the sequencing of the cucumber genome. Mr. Zhao was 15 years old; when the study of the cucumber genome was published in Nature Genetics in 2009, he was listed as a co-author.

Tantalized by genomics, Mr. Zhao quit school and began to work full-time at BGI, one of the biggest genomics research centers in the world. It is based in the mainland city of Shenzhen, near Hong Kong. The following year, BGI founded a cognitive genomics unit and named Mr. Zhao as its director.

Mr. Zhao's first foray into the genetics of intelligence was a plan to collect DNA from high-achieving kids at local high schools. It didn't work.

"Parents were afraid [of giving consent] because their children's blood would be taken," says Mr. Zhao. Blood samples are the most efficient way to collect DNA samples.

In the spring of 2010, a theoretical physicist called Stephen Hsu from the University of Oregon visited BGI. Dr. Hsu was also interested in the genetics of cognitive ability, so the pair joined with other colleagues to launch the BGI intelligence project.

One part of the plan called for shifting to saliva-based DNA samples obtained from mathematically gifted people, including Chinese who had participated in mathematics or science Olympiad training camps.

Another involved the collection of DNA samples from high-IQ individuals from the U.S. and other countries, including those with extremely high SAT scores, and those with a doctorate in physics or math from an elite university. In addition, anyone could enroll via BGI's website if they met the criteria.

The Shenzhen government agreed to pay for half the project, and BGI said it would pitch in the other half, says Mr. Zhao.

Most of the samples so far have come from outside of China. The main source is Dr. Plomin of King's College, who for his own research had collected DNA samples from about 1,600 individuals whose IQs were off the charts. Those samples were obtained through a U.S. project known as the Study of Mathematically Precocious Youth, now in its fourth decade.

Dr. Plomin tracked down 1,600 adults who had enrolled as kids in the U.S. project, now based at Vanderbilt University. Their DNA contributions make up the bulk of the BGI samples.

Dr. Hsu embarked on his own marketing drive. When giving science talks at various institutions, including the California Institute of Technology, Taiwan's Academy of Science and Google, GOOG +0.62%he exhorted listeners to sign up for the study.

BGI's website has so far attracted about 500 qualifying volunteers.

The scientific challenge is significant. Consider the genetics of height, which, like intelligence, is a complex trait governed by many different genes, each one with a tiny influence.

Attempts to find height-related genes didn't yield any reliable hits until the number of DNA samples exceeded 10,000. By studying more and more samples, scientists have now identified about 1,000 genetic variations that partly explain why some people are taller than others. Those results are replicable—and they hold true whether a person is from Iceland or Japan.

By comparison, one of the biggest genomic investigations of IQ attempted so far involves only about 5,000 people drawn from the general population. Scientist say that tens of thousands of regular people would have to be studied just to find the first useful IQ gene.

That's where BGI's genomic deep dive comes in. The team will compare the genomes of 2,200 high-IQ individuals with the genomes of several thousand people drawn randomly from the general population. Because most of the supersmart participants being studied are the cognitive equivalent of people "who are 6-foot-9-inches tall," says Dr. Hsu, it should be much easier to identify many key IQ-related factors in their genomes. (Dr. Hsu is now vice president for research and graduate studies at Michigan State University.)

"The genetic basis of intelligence has been ignored for a very long time," says Mr. Zhao. "Our data will be ready in three months' time."

["This kind of research is impossible in the USA" - so would judge some from the forced resignation of Jim Watson as Director of Cold Spring Harbor Laboratories for a causal comment on the perceived IQ of some ethnic groups. Kind of not true. While the SNP-based study by California-based direct-to-customer genome testing company 23andMe can only be compared to the above Chinese full genome study as "apples to oranges", 23andMe runs a test relating to "the ability to learn from mistakes" (based on a single-point mutation Rs1800497). Though the at least partly Chinese government-run study uses the genome of - presently - mostly non-Chinese individuals, one can assume that an ulterior motif of China is to make their population (yes, they can even forcefully select) more intelligent. There seems to be nothing wrong with the goal - though the Western Civilization and law rejects any assumed means of "forceful selection" - in case of humans. (Enforced genomic selection e.g. for higher agricultural yield - see Monsanto - is already a huge business in the USA and Worldwide). The "controversy" reported here is a very strong reminder of the advantages of genomics in China - even if no "forceful selection" would ever take place even there. Let's assume that from the "initial mostly non-Chinese" sample is substituted by an entirely Chinese population-sample. In that case, nobody could even raise the "R-world", since the 9 leading tribes of China are essentially the same race. On the positive side, the homogeneity will certainly accelerate their probing into what they say "we are interested in the diseases of the Chinese people". At the same time, China (led by a monolithic government) is keenly aware of the genomic vulnerability of a homogeneous population - and not only from the viewpoint of an IQ. It does not call for a very high IQ to realize the consequences. - Pellionisz, at hologenomics_at_gmail_dot_com]

(Feb 21) Breakthrough Prize on YouTube (and everywhere... spilling to BRIC)

The Silicon Valley Industrialists, reigniting the culture of science, will have a global impact - see article by Antonio Regalado from Brazil

Breakthrough Prize in Life Sciences ($3 M each, for 5 scientists per year - list of first 11)

February 20, 2013 4:48 AM - General- Awards- Biotechnology- Medical/ Pharmaceuticals

Art Levinson, Sergey Brin and Anne Wojcicki, Mark Zuckerberg and Priscilla Chan, and Yuri Milner Announce the Breakthrough Prize in Life Sciences. 11 Inaugural winners receive US$3 million each for Groundbreaking Achievements in Life Science Research

SAN FRANCISCO, Feb. 20, 2013 /CNW/ - Art Levinson, Sergey Brin, Anne Wojcicki, Mark Zuckerberg, Priscilla Chan and Yuri Milner announced today the launch of the Breakthrough Prize in Life Sciences ("Breakthrough Prize"), recognizing excellence in research aimed at curing intractable diseases and extending human life. The prize will be administered by the Breakthrough Prize in Life Sciences Foundation, a not-for-profit corporation ("Foundation") dedicated to advancing breakthrough research, celebrating scientists and generating excitement about the pursuit of science as a career.

The first 11 recipients of the Breakthrough Prize are:

•Cornelia I. Bargmann

•David Botstein

•Lewis C. Cantley

•Hans Clevers

•Napoleone Ferrara

•Titia de Lange

•Eric S. Lander

•Charles L. Sawyers

•Bert Vogelstein

•Robert A. Weinberg

•Shinya Yamanaka

All prize winners have agreed to serve on the Selection Committee of the Foundation to choose recipients of future prizes.

Founding sponsors of the Breakthrough Prize include Sergey Brin and Anne Wojcicki, Mark Zuckerberg and Priscilla Chan, and Yuri Milner, who collectively have agreed to establish 5 annual prizes, US$3 million each, going forward.

Art Levinson, Chairman of the Board of Apple and Chairman and former CEO of Genentech, will serve as the Chairman of the Board of the Foundation, while additional directors will include Anne Wojcicki, Mark Zuckerberg and Yuri Milner.

"I am delighted to announce the launch of the Breakthrough Prize in Life Sciences and welcome its first recipients," said Art Levinson. "I believe this new prize will shine a light on the extraordinary achievements of the outstanding minds in the field of life sciences, enhance medical innovation, and ultimately become a platform for recognizing future discoveries. I also want to thank our founding sponsors, Sergey Brin, Anne Wojcicki, Mark Zuckerberg, Priscilla Chan and Yuri Milner. Without their contribution, this prize would not have been possible."

"We are thrilled to support scientists who think big, take risks and have made a significant impact on our lives. These scientists should be household names and heros in society," said Anne Wojcicki.

"Curing a disease should be worth more than a touchdown," said Sergey Brin.

"Priscilla and I are honored to be part of this," said Mark Zuckerberg. "We believe the Breakthrough Prize in Life Sciences has the potential to provide a platform for other models of philanthropy, so people everywhere have an opportunity at a better future."

"Solving the enormous complexity of human diseases calls for a much bigger effort compared to fundamental physics and therefore requires multiple sponsors to reward outstanding achievements," said Yuri Milner.

Going forward, each year's prize winners will join the Selection Committee for future awardees. One of the distinguishing characteristics of the Breakthrough Prize will be a transparent selection process, in which anyone will be able to nominate a candidate online for consideration. Also, the prize can be shared between any number of deserving scientists and can be received more than once. In addition, there are no age restrictions for nominees.

All Breakthrough Prize recipients will be invited to present public talks targeting a general audience. These lectures, together with supporting materials, will be made available to the public, allowing everyone to keep abreast of the latest developments in life sciences, guided by contemporary masters of the field.

About the Breakthrough Prize Foundation:

The Breakthrough Prize in Life Sciences Foundation is a not-for-profit corporation dedicated to advancing breakthrough research in life sciences, celebrating scientists and generating excitement about the pursuit of science as a career. Additional information about the Foundation and the 2013 recipients of the prizes can be found at

About the prize winners:

Cornelia I. Bargmann

Torsten N. Wiesel Professor and Head of the Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior at the Rockefeller University. Howard Hughes Medical Institute Investigator.

For the genetics of neural circuits and behavior, and synaptic guidepost molecules.

David Botstein

Director of the Lewis-Sigler Institute for Integrative Genomics and the Anthony B. Evnin Professor of Genomics at Princeton University.

For linkage mapping of Mendelian disease in humans using DNA polymorphisms.

Lewis C. Cantley

Margaret and Herman Sokol Professor and Director of the Cancer Center at Weill Cornell Medical College and New York-Presbyterian Hospital.

For the discovery of PI 3-Kinase and its role in cancer metabolism.

Hans Clevers

Professor of Molecular Genetics at Hubrecht Institute.

For describing the role of Wnt signaling in tissue stem cells and cancer.

Titia de Lange

Leon Hess Professor, Head of the Laboratory of Cell Biology and Genetics, and Director of the Anderson Center for Cancer Research at the Rockefeller University.

For research on telomeres, illuminating how they protect chromosome ends and their role in genome instability in cancer.

Napoleone Ferrara

Distinguished Professor of Pathology and Senior Deputy Director for Basic Sciences at Moores Cancer Center at the University of California, San Diego.

For discoveries in the mechanisms of angiogenesis that led to therapies for cancer and eye diseases.

Eric S. Lander

President and Founding Director of the Eli and Edythe L. Broad Institute of Harvard and MIT. Professor of Biology at MIT. Professor of Systems Biology at Harvard Medical School.

For the discovery of general principles for identifying human disease genes, and enabling their application to medicine through the creation and analysis of genetic, physical and sequence maps of the human genome

Charles L. Sawyers

Chair, Human Oncology and Pathogenesis Program at Memorial Sloan-Kettering Cancer Center. Howard Hughes Medical Institute Investigator.

For cancer genes and targeted therapy.

Bert Vogelstein

Director of the Ludwig Center and Clayton Professor of Oncology and Pathology at the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center. Howard Hughes Medical Institute Investigator.

For cancer genomics and tumor suppressor genes.

Robert A. Weinberg

Daniel K. Ludwig Professor for Cancer Research at MIT and Director of the MIT/Ludwig Center for Molecular Oncology. Member, Whitehead Institute for Biomedical Research.

For characterization of human cancer genes.

Shinya Yamanaka

Director of Center for iPS Cell Research and Application, Kyoto University

Senior Investigator, Gladstone Institutes, San Francisco

For induced pluripotent stem cells.

About the participants:

Art Levinson

Arthur D. Levinson is chairman of Genentech, Inc. and a member of the Roche Board of Directors. He has been chairman of Genentech since 1999, and he served as chief executive officer of Genentech from 1995 to 2009. Levinson joined Genentech in 1980 as a research scientist and became vice president, Research Technology in 1989; vice president, Research in 1990; senior vice president, Research in 1992; and senior vice president, Research and Development in 1993.

Art was appointed Chairman of the Board of Apple in November 2011. He had served as a co-lead director of Apple's board since 2005 and a director since 2000. He is Chairman of the Board of Amyris and a director of NGM Biopharmaceuticals, Inc. and the Broad Institute of MIT and Harvard. He was a director of Google, Inc. from 2004 to 2009. He currently serves on the Board of Scientific Consultants of the Memorial Sloan-Kettering Cancer Center, the Industrial Advisory Board of the California Institute for Quantitative Biomedical Research, the Advisory Council for the Princeton University Department of Molecular Biology and the Advisory Council for the Lewis-Sigler Institute for Integrative Genomics.

Art has authored or co-authored more than 80 scientific articles and has been a named inventor on 11 United States patents. Art received his Bachelor of Science degree from the University of Washington and earned a doctorate in Biochemical Sciences from Princeton University.

Mark Zuckerberg

Mark Zuckerberg is the founder chairman and CEO of Facebook, which he founded in 2004 in his college dorm room.

Mark is responsible for setting the overall direction and product strategy for Facebook. He leads the design of Facebook's service and the development of its core technology and infrastructure.

Mark studied computer science at Harvard University before moving the company to Palo Alto, California. In September 2010, Mark donated $100 million to the Newark Public School System to help renovate and revamp the system.

Sergey Brin

Sergey Brin, a native of Moscow, received a Bachelor of Science degree with honors in mathematics and computer science from the University of Maryland at College Park. He is currently on leave from the Ph.D. program in computer science at Stanford University, where he received his master's degree. Sergey is a recipient of a National Science Foundation Graduate Fellowship as well as an honorary MBA from Instituto de Empresa. At Stanford, he met Larry Page and worked on the project that became Google. Together they founded Google Inc. in 1998, and Sergey continues to share responsibility for day-to-day operations with Larry Page and Eric Schmidt.

Sergey's research interests include search engines, information extraction from unstructured sources, and data mining of large text collections and scientific data. He has published more than a dozen academic papers, including Dynamic Data Mining: A New Architecture for Data with High Dimensionality, which he published with Larry Page.

Sergey has been a featured speaker at several international academic, business and technology forums, including the World Economic Forum and the Technology, Entertainment and Design Conference.

Anne Wojcicki

Anne Wojcicki is Co-Founder of 23andMe, a privately held personal genetics company that helps individuals understand their own genetic information through DNA analysis technologies and Web-based interactive tools. By encouraging individuals to access and learn about their own genetic information, 23andMe aims to create a common, standardized resource that has the potential to accelerate drug discovery and bring personalized medicine to the public. Anne has an extensive background in health-care investing, focused primarily on biotechnology companies. She received a bachelor's degree in biology from Yale University.

Yuri Milner

Yuri founded Group in 1999. Under his leadership, Group became the leading European Internet company. Yuri took that business public in 2010, stepping down from his role of Chairman at the beginning of 2012 to focus his efforts on global Internet investments. DST Global, a family of funds investing in Internet companies, was established in 2009 and is one of the largest Internet investors in the world.

Yuri graduated from Moscow State University in 1985 with an advanced degree in theoretical physics and subsequently conducted research at the Institute of Physics at the Russian Academy of Sciences. In 2012 he launched the Fundamental Physics Prize Foundation, a not-for-profit corporation dedicated to advancing knowledge of the Universe at the deepest level by awarding annual prizes for scientific breakthroughs, as well as communicating the excitement of fundamental physics to the public.

SOURCE: Milner Foundation

For further information:

For additional inquiries, contact: / +1-(415)-671-7676

[A multiple breakthrough. First, the acknowledgement that genomics ("Life Sciences") needs "breakthroughs" - just as Thomas Khun predicted in his bestseller "The Structure of Scientific Revolutions" - closes a chapter (the Decade of Genomic Uncertainty, when The Human Genome Program opened the Pandorra box, and it was found by Encode 2007 and finally by Encode 2012 that the earlier axioms are obsolete). Second, this Prize is created by the families of spectacularly successful INDUSTRIALISTS, who fully understand that without software-enabling algorithms any progress is seriously hindered. Third, there may be an apparent realization that both Internet-search and Social Media, fueling hypergrowth of industries, may have peaked - with the Next Big Thing in genome informatics. Last, but not least, not one of the creators of this Prize relate to the classic culture of science that holds "Curing a disease should be worth more [for a properly appreciative society] than e.g. a touchdown". - Pellionisz, holgentech_at_gmail_dot_com]

Young Chinese Scientists will Map any Genome

Bloomberg Businessweek

By Lauren Hilgers on February 07, 2013

When the workday ends at BGI’s factory in Shenzhen, the headquarters of the largest genome mapping company in the world, it’s like a bell has gone off at math camp. The company’s scientists and technicians spill out of the doorways of the building, baby-faced and wearing jeans and sneakers. Some still have braces. Several young women link arms and skip toward a bus line. Others head next door to the dorm or over to the canteen where young couples are holding hands across plastic trays. “This work we do is tiring and requires focus,” says Liu Xin, a 26-year-old team leader in the bioinformatics division, as he sinks into a couch in one of BGI’s conference rooms. “So it’s good that they allow us to date.”

Liu is one of a small army of recent college graduates at BGI’s largest facility, a former shoe factory. Two gray buildings, the factory and the dorm, are wedged between one of Shenzhen’s industrial zones—a grid of high-rises, apartment buildings, and several hospitals and medical equipment companies—and a lush, jungly hill that’s in the process of being bulldozed. Liu is stocky and serious, glad that he already has a steady girlfriend so he can focus on his career. He arrived at BGI three years ago, a biology major from Peking University with little experience in the study of the genome, the term for the entirety of an organism’s genetic information. Now he’s one of the senior people in his department. He works 12-hour days and oversees the sequencing of multiple genomes at a time. He specializes in plants—his team is currently sequencing a species of orchid. The bioinformatics teams around him are picking through the genomes of animals, microbial organisms, humans, and anything else that comes with a genetic code. “Everyone is just out of college,” he says. “I am now more sophisticated than most of the newcomers.”

Ten years after the mapping of the human genome, BGI has established itself as the world’s largest commercial genetic sequencer. The ranks of China’s college graduates are expanding faster than the country can employ them, and BGI is leveraging this cheap, educated labor pool. At the factory in Shenzhen, more than 3,000 employees (average age, 26) spend their days preparing DNA samples, monitoring sequencing machines, and piecing together endless strings of A’s, C’s, T’s, and G’s, the building blocks of genetic material.

“This is big data analysis,” says Wang Jun, BGI’s 36-year-old executive director. Wang, who regularly wears tennis shoes and untucked polo shirts, has published more than 35 articles in Science and Nature magazines and also teaches at the University of Copenhagen. Genomics, he says, is a new field and experts are being created from scratch. “We don’t need Ph.D.s to do this work,” Wang says. Instead, he believes genomics is best learned the old-fashioned way. “You just throw them in,” he says of BGI’s technicians. “The best way is hands-on experience.”

When the first draft of the human genome was released in 2000 as part of the international Human Genome Project, it seemed inevitable that scientists would soon crack the codes of disease, health, and human development. But the genome has proved more complicated. What scientists produced in 2000 was a long list of nucleotides, the combinations of markers in DNA that specify the makeup of an organism. It was just a list, and only a fraction of it is understood. Scientists were quick to identify fragments of the genome that translate into proteins, which control things like eye color, but these make up only 1.5 percent of the entire thing. As geneticists like to put it, they produced a map without a legend. This is where BGI comes in.

The company was founded in 1999 with state funding to lead China’s participation in the Human Genome Project. “We didn’t think about any business model; we basically didn’t plan further than the human genome,” says Wang, who was brought on in the early days of BGI to provide expertise in computers. China, he points out, was the only developing country working on the international project, and although the BGI team contributed only 1 percent of the finished project, it did it quickly and with little previous experience. “Even Bill Clinton thanked us for our participation,” he says. Wang joined the project when he was just 22 and worked under BGI’s two founders, the scientists Wang Jian, then 45, and Yang Huanming, then 47.

For its next challenge, BGI decided to tackle rice, whose genome is significantly shorter than that of humans but still large enough to impress. “We recruited a bunch of undergraduates, and lots of them had no working experience on any project,” Wang Jun says. The schedule was tight; Wang and his team barely slept. “We can do these kind of crazy things in BGI,” he says. “We can get 100 people together, very fresh, no experience at all, and get it done.”

In 2002, BGI published a paper on the rice project in Science and again attracted attention and money from the Chinese government, though it’s a private company. The company was rewarded with entry into the state-run Chinese Academy of Sciences, a distinction that secured additional funding. As part of CAS, however, BGI was limited to only 90 scientists. Its leaders had their eyes on expansion. “Our boss wanted to buy more sequencing machines,” says Deng Wenxi, a 24-year-old communications officer at the BGI factory. “But the Beijing government would not support us.” In 2007 the company found a solution by way of Shenzhen’s city government, which offered the factory 10 million yuan (about $1.6 million in today’s exchange rates) to cover startup fees and 20 million yuan in annual grants. The company changed its name from Beijing Genomics Institute to BGI Shenzhen and moved to the shoe factory. “Beijing is more strict,” says Deng. “Shenzhen wanted to welcome us.” The factory, she says, actually belongs to the Shenzhen government. When asked about the move, Wang Jun answers the question a little more vaguely, “Well,” he says, “the weather is definitely nicer here.”

Today, BGI organizes its operations into three categories—health care, agriculture, and the environment. When scientists look at the genome, they’re looking for variations from one individual to another, from species to species, or population to population. They’re looking to understand which variations link to specific traits or diseases.

As Wang Jun says, decoding any genome is a big data endeavor, and there’s no other research institution or for-profit sequencing company in the world that has the capacity of BGI. In health care, it offers straightforward sequencing services for universities and corporations globally, which ask BGI to sequence a genome and send it back for analysis. More often than not, BGI works in partnerships to map, analyze, and publish the findings.

When Deng meets me in the morning, the first place we visit is a kind of trophy room on the top floor of the factory where the walls are decorated with copies of Science and Nature magazines, each containing a paper from BGI. The subjects include the company’s part in the ICGC Cancer Genome Projects; its work with 2,000 families to map the genomes of children with autism; its mapping of the epigenetic differences (differences in gene expression not the result of a variation in the genetic code) between 5,000 twins; and a project to increase the number of identified Mendelian, or inherited, genetic disorders.

In addition to linking more disorders to variations in the genome, BGI’s research could change the way medical providers and governments understand and respond to outbreaks of disease. BGI’s partners include GE Healthcare (GE), Merck (MRK), and Novo Nordisk (NVO), and the work they’re doing will help pharmaceutical companies understand why some drugs are more effective in some populations and less so in others. In May 2011, BGI flexed its muscle during a deadly outbreak of E. coli in Germany. As soon as the outbreak began, BGI began to piece together the genome of the strain from samples provided by the University Medical Center Hamburg-Eppendorf. Within five days, the company released sequencing reads on the strain, leading to the crowd-sourced assembly and analysis of the genome. In the future, BGI’s expertise could be applied to viruses.

Wang Jun says BGI’s first goal is to “find ways that genomics can serve society.” The company, he emphasizes, is not state-owned, and the profits it makes are cycled back into research. The company has been steadily increasing its profits in the past few years. In 2011, BGI reported revenue of 1.2 billion yuan. Many projects the company takes on reflect this policy of for-profit science. In agriculture, BGI is mapping genome sequences it considers proprietary and using them to engineer superior strains of rice, millet, and even fish. Technicians do this by using genomic information to breed for certain traits. Hybrid millet, says Deng, could improve yields and help alleviate hunger in Africa. Balsa trees designed by BGI can withstand colder temperatures, which means they could be grown in China. Sharing the trophy room with the BGI published papers is a single large fish, mottled green and gray, swimming in a tank. “That is our hybrid grouper,” Deng says. It grows three times as fast as a regular grouper, she says, and according to a BGI brochure, it tastes better. When I ask Wang how BGI determines which plants and animals to sequence as part of its “1,000 Plants and Animals” project, he answers, “We start with anything tasty.”

The company is also taking part in the sequencing of the earth’s microbiome, meaning all microscopic organisms. This is an effort to identify the functional and evolutionary diversity of microbial organisms across the globe. (BGI has sequenced more than 1,000 such organisms in the human gut.) Many of the plant and animal genomes it has sequenced, such as the giant panda and Liu’s orchid, are beneficial mainly to scientists studying the traits and evolution of animals.

BGI has also made forays into cloning and has invented a simplified technique. Called “handmade cloning,” it cuts costs and makes large-scale cloning more realistic for use in animal and plant research. So far BGI has applied the technique to clone mice, sheep, and a mini pig that glows in the dark. In an office, a slightly desiccated stuffed piglet sits in a small display case. A better-looking piglet, Deng says apologetically, had been misplaced.

“It’s the Wild West,” says George Church, a professor of genetics at Harvard University and an adviser to BGI. “This is a field that has arisen overnight, and the number of discoveries is going up exponentially.” A single genome contains a massive amount of data (a human genome, for example, contains about 3 billion nucleotides, or data points), and a bioinformatics expert’s work requires sifting through, comparing, and testing the information in multiple genomes. While sequencing costs have dropped dramatically in the last 10 years, the process is far from automated. Companies that offer personalized genetic testing, such as 23andMe, typically test only for a sampling of 100 traits and diseases, or about 1/3,000th of the entire genome, Church says. For about $4,000, BGI does the whole thing.

BGI’s electronic sequencers—11 are in Shenzhen, 77 in Hong Kong, and more than 66 scattered throughout the rest of China and the world—are imposing-looking black-and-white boxes, slightly taller than the technicians that run them. They don’t churn out fully formed genomes; rather, they handle fragments, reading each nucleotide from signals emitted as the machine resynthesizes a template DNA strand. These out-of-order sections of the genome require piecing together. Once assembled, a genome sequence still has to be interpreted to find the source of whatever trait or disease a particular study aims to find. This process, even with a reference genome fully in place, is difficult to hand over to a computer program. “The software basically doesn’t exist yet,” Church says.

BGI’s Shenzhen factory is organized so that a genetic sample travels from floor to floor as it goes through the sequencing process. When a sample first arrives—it usually comes in a test tube—it’s taken to the fourth floor, where workers in different colored coats prepare and expand the genetic material (coat color signifies the kind of DNA being handled). Workers bend over tiny vials, mechanically separating genetic material with a syringe. They’re splitting DNA samples into single strands and will soon put them through a chemical process called polymerase chain reaction, or PCR. This will copy a single DNA fragment about 10 million times. Microscopic chains of beads holding the DNA fragments are then loaded onto a sheet with tiny cups and sent to the sequencers on the fifth floor. When the machines are finished, the information is delivered electronically to the second floor, where Liu, the bioinformatics team leader, works.

In a large, open room, more than 1,000 young scientists sit in cubicles, staring at strings of computer code, piecing together sections of whatever genome they’ve been assigned. Liu’s team is slightly apart from the rest. “You’re looking for variants or parts of the genome that are hard to map,” he says. Computer programs have difficulty identifying a new variation unless a spot on the genome has already been pinpointed and entered into the computer program. Recently, with the orchid, Liu’s team had problems interpreting a certain section. Liu was assembling his species of the plant according to an orchid reference genome, and certain sections of the code were just not lining up the way researchers (and the computer) had expected. Trying to tie these sections to certain orchid traits was proving difficult. Liu calls it a “weird region.”

“We had to figure out how to analyze this,” he says. “It required us to try different solutions, look through sets of data that could be important, and figure out why we were having trouble mapping that section.” Researchers tried different solutions and found that some of the orchid’s traits were heterozygous—there were two spots on the genome responsible for their development. Weird regions of a genome, Liu says, are the most exciting part of his job.

A decade ago young people arriving in Shenzhen would have hoped to land a job building iPods or sewing jeans, a wholly different career track from Liu’s colleagues. “This is the virtue of Shenzhen,” Liu says. “People are all coming from other places, they are here trying to make money or to find some opportunities. We all have the same kind of ambitions.” An opening salary at BGI runs around 3,000 yuan ($481) a month. “It’s not great, but it is competitive,” Deng, the communications officer, says.

Executive Director Wang could easily disappear in the crowd of recent graduates on BGI’s campus if it weren’t for his imposing height. He doesn’t like calling BGI a factory—he’s more interested in creating the feel of a college campus. In addition to encouraging dating, BGI promotes the creation of clubs and the enjoyment of free time. “On weekends we like to climb North Mountain,” Deng says, pointing to a hill in the distance. Wang likes to play basketball, and BGI has an annual tournament. According to Deng, Wang’s team always wins. He has a suspicious number of tall people on his team. “We think he might hire people just for the basketball team,” she says, giggling.

After six o’clock, when most of BGI’s staff is done with work, a basketball court outside the dorm quickly gets crowded. Some of Liu’s colleagues from the bioinformatics division stick around to watch the games. One of the dorm’s oldest residents, Tai Shuaishuai, says he’s just taking a break before heading back to work. “For those of us who always stay in the office, the dorm is more convenient,” he says, smiling through braces. Tai is 31, and his first name translates to “handsome handsome.” Like Liu, he’s been at BGI since 2009, an eternity at the Shenzhen factory, and he heads a team using sequencing to improve what he calls “molecular breeding,” the same process responsible for BGI’s grouper. Tai is also responsible for reviewing potential employees.

“China has a lot of universities, but we prefer candidates from the top universities,” he says. “To be a BGIer means you have to be creative as a scientific researcher, and you have to have team spirit. We take a lot of things into consideration—skills, knowledge, educational background, and working style.” According to Tai, an offer made to a potential employee is rarely turned down.

One reason may be that BGI offers employees the chance to study while working. If Liu hadn’t joined BGI, he says, he probably would have pursued graduate studies somewhere else. “I would not be getting this hands-on experience,” he says. “Working here is basically a Ph.D. program.” Nonetheless, he’s starting at the University of Hong Kong this year in a program that will only require that he leave work for a day or two each week.

Most of the employees on the basketball court seem to be participating in one of BGI’s work-study programs. One group of four says they’re still college students, living at BGI on a full-time internship. “It’s just as comfortable as the dorms in our universities,” one says. “And Shenzhen is a great place to be for young people.” On weeknights, he says, karaoke halls offer a discount.

Around 6:30 it begins to rain, and the BGI basketball court empties. Tai ducks into the entrance of the dorm, where a janitor is mopping under fluorescent lights and BGI employees queue up to buy snacks. A couple of people from the bioinformatics team gather around Tai and talk about their plans. “I would like to go abroad to the U.S.,” says a team leader named Gao Zhibo. “Not to get my Ph.D. but just to improve my language skills and my social skills.” Tai, for his part, is hard-pressed to imagine why anyone would ever leave. “Doing scientific study is my passion,” he says. “It’s my belief that science has no limits.”

[Comments are far too numerous and sensitive to fully list here. The remark is most noteworthy by Harvard genomics professor George Church (whom I dubbed "the Edison of genomics"), as an adviser to both BGI and my Silicon Valley HolGenTech, who says (about genome analytics) "the software basically does not exist yet". If anyone, George should know, since the Boston-based genome analytics company he founded (Knome) sells high-performance computer boxes with genome analytics software. (His statement should be quoted when it comes to any due diligence of investors of a list of over 100 "genome informatics companies" and a similar number of "genome service" companies already in existence). As the average age of workers at BGI is a tender 26 years, on average they were 7 years old when the "Internet boom" started (1994) - and most of them never lived in Silicon Valley, and even now do not hold even one Ph.D. degrees. Thus, a brief recollection might be useful by someone who shared pioneering THAT industrial paradigm-shift (at Academia, US Government and Private Industry). "Software" was the least crucial #5 component of "the Internet boom". While software development is expensive in California (compared to the monthly $481 at BGI - in Silicon Valley it is at least one order of a magnitude more expensive), other more important crucial components were 3) science, 4) algorithm, 5) business model (let's us not factor-in the most important #1 component that is explicitly declared for BGI to have been provided by governments; MONEY. Those who would interject that BGI is not "owned", only "funded" by government, an interesting parallel might be that e.g. the CIA is widely known to fund "independent" businesses for tasks that are strategically crucial for the global interests of the USA). Looking at #3-5 components of the Internet boom (compared to the present "Industrialization of Genomics") some major differences are extremely important. The most enormous difference is that "Science" of Internet was essentially a "no brainer", since the Internet-technology (packet-switching) was entirely man-made, thus 100% transparent, remarkably easy to understand and program for. Further, it was actually built to be utterly simple and robust to withstand a nuclear war. In contrast (and Prof. Church would probably enthusiastically second this statement, as well as some 15,000+ others), "scientific understanding of (recursive) genome function only exists at its basics perhaps since 2008" . Thus, very much like nuclear technology first required nuclear PHYSICS, which in turn called for the colossal challenge of development of quantum physics, massive investments into "industrialization of genomics" were too early before gaining basic insights into the intrinsic mathematics of the genome-epigenome regulation. Further to the comparision of Internet- and Genome Informatics, with simple e-mails (or a single gene) there is not much need for search- (or regulation)-algorithms, Internet worked fine without a "search-engine" or regulation of the output of a single gene with "Operon" (Nobel to Jacob and Monod, 1965). With the advent of the Internet-boom there were so many Internet-companies that huge billboards along highway 101 asked "What will all the industries do with the Internet?" - to be answered in a mile or so "What sill all the industries do without the Internet?". The boom gave birth to the brilliant (in retrospect, utterly simple...) Google search-algorithm-patent (and company) - that swept away nearly all others, except those that found at the outset "business models" (eBay, Amazon) that guaranteed their survival. At the beginning of the Internet-boom there were many companies without any "business model" at all. "The name of the game" used to be just the "number of eye-balls" attracted by any given firm. (There were some, who remembers their name, that actually paid for geeks simply to look at, and click at websites - with no utilization of the "captured eye-balls"). A bit similarly, "the big question" now appears to be "how many DNA sequences did you do, how many e.g. cancerous DNA sequences do you store?" With the Industrialization of Genomics, however, there are some obvious "business models", simple as they are, in "Genomically Modified Organisms". We all know (and the article reinforces that impression) that China (BGI) - and perhaps with some more "checks and balances" the USA as well - are very big at that, certainly sustaining a couple of thousand developers at $481 per month. (Science, that would be much more expensive in house, can be acquired). Thus, the secondary most obvious "business model" is a given. (For those wondering, the #1 is "biodefense"). Energy, health and pharma are #3-5 with significant glitches to overcome for global and scalable business models (public comments are not appropriate here) -c.f. Pellionisz; HolGenTech_at_gmail_dot_com.

Non-coding Mutations May Drive Cancer

The majority of human melanomas contain mutations in a gene promoter, suggesting mutations in regulatory regions may spur some cancers.

By Dan Cossins | January 24, 2013
The Scientist

Mutations in the regulatory, or non-coding, regions of the telomerase reverse transcriptase (TERT) gene—a cancer-associated gene that encodes a component of telomerase, an enzyme known to help protect the ends of chromosomes and support cell longevity—may be at the root of most melanomas, according to two papers published today (January 24) in Science.

In both studies, researchers identified mutations that created new binding sites in the TERT promoter for particular transcription factors and resulted in increased transcriptional activity at the TERT promoter, which may in turn lead to increased expression of the gene and the endless cell division characteristic of cancer cells. The findings suggest that mutations in regulatory parts of the genome, in addition to those in protein-coding sequences, may be a key mechanism causing the growth of certain types of cancer.

“I am excited by the finding that regulatory mutations can apparently act as drivers of carcinogenesis,” Elaine Mardis, a cancer geneticist and co-director of the Genome Institute at Washington University, Missouri, who was not involved in the research, said in an email. “This is great news for labs like ours that have always emphasized the importance of whole genome sequencing over exome or targeted sequencing.”

Until recently, sequencing efforts focused almost exclusively on the protein encoding regions of cancer genomes, due to the high cost of whole genome sequencing and the fact that it’s easier to identify effects of mutations in protein-coding genes. As a result, scientists have identified many recurrent mutations in protein-coding regions that contribute to cancer development, but very few in non-coding regions.

To see if tumor genomes also harbor mutations in these under-explored regulatory regions, Franklin Huang and Eran Hodis of Harvard Medical School and colleagues took a closer look at whole genome sequences of malignant melanomas published last May. Sure enough, they found two somatic mutations, which they called C228T and C250T, in the TERT promoter region in 71 percent of the tumors they analysed—making them more common than the known melanoma mutations in the coding regions of the genes BRAF and RNAS.

“The fact that these mutations occur so frequently near what is a very important gene in cancer development was unexpected, but it was staring us in the face,” said Hodis.

Intriguingly, both mutations generated an identical DNA sequence containing a transcription factor binding site, increasing the transcription of reporter genes linked to the TERT promoter by 2- to 4-fold. This led the researchers to propose that these promoter mutations may be driving melanoma development by increasing TERT expression, which is tightly regulated in normal cells. When TERT is over-expressed, cells produce elevated levels of telomerase, prompting the regeneration of chromosome-capping telomeres and resulting in cells that can divide limitlessly. Mutations that increase TERT expression could thus be expected to promote cancerous growth.

“The fact that these mutations create a transcription factor binding site, although we haven’t shown it actually binds a transcription factor, is a clue that this could be one mechanism for how it increases activation of TERT,” said Hodis.

In a separate study, Susanne Horn of the German Cancer Research Center in Heidelberg and colleagues compared the whole genome sequences of tumors from a melanoma-prone family who did not carry two known germline mutations linked to melanoma, and identified a germline mutation in the TERT promoter in individuals with the cancer. Once again, the sequence change created a new binding pattern for certain transcription factors and increased transcription activity.

“[We think] the binding of transcription factors up-regulates the telomerase gene in the developing tumors,” Horn said. “High levels of telomerase may then lead to cells that can divide more often.”

Horn and her colleagues also screened the TERT promoter in 168 cell lines derived from metastatic melanomas from the general population, and found recurrent somatic mutations in 74 percent of them. The majority of those mutations generated new transcription factor binding sites.

Together, the studies show that “although our focus has been on the 1 percent of the genome that codes for proteins, there are potentially important discoveries in the rest of the genome,” said Huang. Indeed, Mardis added, if researchers continue to focus on exome or targeted sequencing of cancer genomes, “we are going to miss the clues available from analysis of the whole genome that may . . . ‘matter’ to driving the cancer growth.”

F.W. Huang et al., “Highly recurrent TERT promoter mutations in human melanoma,” Science, doi: 10.1126/science.1229259, 2013.

S. Horn et al., “TERT promoter mutations in familial and sporadic melanoma," Science, doi: 10.1126/science.1230062, 2013.

[Jacob & Monod (1961, Nobel in 1965) discovered over half a Century ago, that their (in retrospect "primitive") "Operon-regulation" is driven by "promoter" and "operator" sequences, OUTSIDE of genic borders. Should they be alive, they would strongly back Elaine Mardis (who took notice of FractoGene at its Cold Spring Harbor Laboratory presentation, invited by George Church, 2009). Dr. Mardis puts in this article "exomics" decisively into its proper ballpark.

"Genes" are 1.3% of the full human DNA, "exons" are the smaller fraction of 1.3% ("non-coding" introns are usually much longer).

While there is zero question that already at least 3,000 diseases are known to be caused by glitches of "exons", these are typically early-onset and rare diseases. Pharma just came out for a drug for cystic fibrosis, but it is effective for 4% of the patients, and the drug costs over $200 thousand per year.

The real economic driver (mega-billions already spent) is in cancer - where initially they may be nothing wrong with (the hundreds, or even thousands of) genes involved; but their recursive fractal regulation is derailed (sets of genes can stop producing excess proteins). Most cancers are known to be late-onset, rather common diseases. It is widely acknowledged that they are "genome regulation diseases". .

The "new war on cancer", thus narrows on the battlefield of structural variants affecting "genome regulation". With the FractoGene patent now available, utilization of software-enabling algorithms will help provide the "geek power" Dave Haussler is calling for. - Pellionisz, ]

DNA pioneer James Watson takes aim at "cancer establishments"

Reuters/Reuters - Dr. James Watson, co-discoverer of the DNA helix and father of the Human Genome Project, became the first human to receive the data encompassing his personal genome sequence at Baylor College …more of Medicine in Houston in this May 31, 2007 file photo. REUTERS/Richard Carson/Files

By Sharon Begley

NEW YORK | Wed Jan 9, 2013 6:34am EST

NEW YORK (Reuters) - A day after an exhaustive national report on cancer found the United States is making only slow progress against the disease, one of the country's most iconic - and iconoclastic - scientists weighed in on "the war against cancer." And he does not like what he sees.

James Watson, co-discoverer of the double helix structure of DNA, lit into targets large and small. On government officials who oversee cancer research, he wrote in a paper published on Tuesday in the journal Open Biology, "We now have no general of influence, much less power ... leading our country's War on Cancer."

On the $100 million U.S. project to determine the DNA changes that drive nine forms of cancer: It is "not likely to produce the truly breakthrough drugs that we now so desperately need," Watson argued. On the idea that antioxidants such as those in colorful berries fight cancer: "The time has come to seriously ask whether antioxidant use much more likely causes than prevents cancer."

That Watson's impassioned plea came on the heels of the annual cancer report was coincidental. He worked on the paper for months, and it represents the culmination of decades of thinking about the subject. Watson, 84, taught a course on cancer at Harvard University in 1959, three years before he shared the Nobel Prize in medicine for his role in discovering the double helix, which opened the door to understanding the role of genetics in disease.

Other cancer luminaries gave Watson's paper mixed reviews.

"There are a lot of interesting ideas in it, some of them sustainable by existing evidence, others that simply conflict with well-documented findings," said one eminent cancer biologist who asked not to be identified so as not to offend Watson. "As is often the case, he's stirring the pot, most likely in a very productive way."

There is wide agreement, however, that current approaches are not yielding the progress they promised. Much of the decline in cancer mortality in the United States, for instance, reflects the fact that fewer people are smoking, not the benefits of clever new therapies.


"The great hope of the modern targeted approach was that with DNA sequencing we would be able to find what specific genes, when mutated, caused each cancer," said molecular biologist Mark Ptashne of Memorial Sloan-Kettering Cancer Center in New York. The next step was to design a drug to block the runaway proliferation the mutation caused.

But almost none of the resulting treatments cures cancer. "These new therapies work for just a few months," Watson told Reuters in a rare interview. "And we have nothing for major cancers such as the lung, colon and breast that have become metastatic."

The main reason drugs that target genetic glitches are not cures is that cancer cells have a work-around. If one biochemical pathway to growth and proliferation is blocked by a drug such as AstraZeneca's Iressa or Genentech's Tarceva for non-small-cell lung cancer, said cancer biologist Robert Weinberg of MIT, the cancer cells activate a different, equally effective pathway.

That is why Watson advocates a different approach: targeting features that all cancer cells, especially those in metastatic cancers, have in common.

One such commonality is oxygen radicals. Those forms of oxygen rip apart other components of cells, such as DNA. That is why antioxidants, which have become near-ubiquitous additives in grocery foods from snack bars to soda, are thought to be healthful: they mop up damaging oxygen radicals.

That simple picture becomes more complicated, however, once cancer is present. Radiation therapy and many chemotherapies kill cancer cells by generating oxygen radicals, which trigger cell suicide. If a cancer patient is binging on berries and other antioxidants, it can actually keep therapies from working, Watson proposed.

"Everyone thought antioxidants were great," he said. "But I'm saying they can prevent us from killing cancer cells."


Research backs him up. A number of studies have shown that taking antioxidants such as vitamin E do not reduce the risk of cancer but can actually increase it, and can even shorten life. But drugs that block antioxidants - "anti-antioxidants" - might make even existing cancer drugs more effective.

Anything that keeps cancer cells full of oxygen radicals "is likely an important component of any effective treatment," said cancer biologist Robert Benezra of Sloan-Kettering.

Watson's anti-antioxidant stance includes one historical irony. The first high-profile proponent of eating lots of antioxidants (specifically, vitamin C) was biochemist Linus Pauling, who died in 1994 at age 93. Watson and his lab mate, Francis Crick, famously beat Pauling to the discovery of the double helix in 1953.

One elusive but promising target, Watson said, is a protein in cells called Myc. It controls more than 1,000 other molecules inside cells, including many involved in cancer. Studies suggest that turning off Myc causes cancer cells to self-destruct in a process called apoptosis.

"The notion that targeting Myc will cure cancer has been around for a long time," said cancer biologist Hans-Guido Wendel of Sloan-Kettering. "Blocking production of Myc is an interesting line of investigation. I think there's promise in that."

Targeting Myc, however, has been a backwater of drug development. "Personalized medicine" that targets a patient's specific cancer-causing mutation attracts the lion's share of research dollars.

"The biggest obstacle" to a true war against cancer, Watson wrote, may be "the inherently conservative nature of today's cancer research establishments." As long as that's so, "curing cancer will always be 10 or 20 years away."

(Reporting by Sharon Begley; Editing by Jilian Mincer and Peter Cooney)

[No reader should have the wrong impression that "The Nobel Laureate Champion of DNA; Dr. Watson" wrote just an Op-Ed on cancer, asking for $1Bn on yet another "Big Science" project (while ditching both the1971 "War on Cancer" - the federal government has spent well over $105 billion on the effort, Kolata 2009b and now withdrew his support from "The Cancer Genome Atlas" project, starting in 2005, with uncounted hundreds of billions of dollars). To dispell any mistaken impressions, his full single-author scientific publication is available from this website: "Oxidants, antioxidants and the current incurability of metastatic cancers"

His approach of seeking a "miracle chemical" (as basic as oxygen) is to be contrasted, however, with the vision of Dave Haussler, who stated recently in an extremely forceful 4-minute video (with transcript) that "cancer is a digital disease and it will have a digital cure".

The entire "fractal school" (yours truly from 1989, 2002 recently summarized) with "big guns" since 2009 "Mr. President, the Genome is Fractal!") outlines a digital approach, based on the principle of recursive genome function 2008. In the same year, the spectacular NOVA Special Video on Fractals illustrated (see below) that cancers are fractal - and as reviewed lately in 2012 clogging the recursive genome function by large CNV-s are linked by dozens of independent experimental evidence to cancer(s) and a slew of genome (mis)regulation diseases.

See the spectacular NOVA Special on Fractals, YouTube 2008

As elaborated in a just-out Springer Textbook Chapter by fractalist co-authors, cancer is unlikely to be treated (let alone cured) without a digital understanding of genome (mis)regulation - and groping for understanding it at the level(s) of full-blown complexity misses the chance of grasping the rudimentary, therefore simple derailment (Faraday: "there is nothing simpler than a problem solved"). Such "don't work the problem, work the causes" approach may call for a better definition of "Data Science" as "Science and Technology of Data Analytics". The present collapse of "DNA Data Generation" because of an oversupply of data while there is no sufficient demand by robuts-enough analytics, is most dramatically manifest by having to sell a crown-jewel of Silicon Valley (Complete Genomics) at greatly depressed valuation to the fiercest global competitor of the USA.

Cancer data generation (without sufficient analytics) may become the "Next Glut". The problem is NOT with the "cancer establishments" - but with the delay how many of us has to perish before fractal analysis of cancerous genomes becomes commonplace - in hospitals. At the field at large one may be astonished that FRACTAL CANCER words already yield 3.7 MILLION hits on Google! - Pellionisz

China, Regulation and Securing the Operating System of Life

The Committee on Foreign Investment in the United States recently approved the sale of Complete Genomics, based in Mountain View, California to China-based BGI (formerly known as the Beijing Genomics Institute). Some decried the committee’s investigation as the overarching meddling of government in business affairs while others hailed the committee’s efforts as an important measure necessary to protect national security. In fact, both sides were right.

Attempts to regulate or restrict the export of American biotechnology are likely to backfire and hurt American competitiveness. We’ve seen this pattern before. Efforts by the US government to ban the export of encryption technologies during the 1990’s did little to prevent their use around the world. In fact, just the opposite occurred, it spawned the development of foreign firms in the encryption space and the launch of competing products. In 2001, President George W. Bush banned federal funding for stem cell research, delaying important and potentially life-saving research into illnesses ranging from cancer to Parkinson’s disease. The result: the US fell behind in this area and some of our best scientists went overseas to continue their research unfettered by American political affairs. Regulating dynamic, fast-changing technologies is difficult.

This said, newly emerging technologies ranging from robotics to nanotechnology do raise significant national security concerns, as do the advances in genetics and synthetic biology. Were we to ignore these concerns, we would do so at our own peril. Whether or not we realize it, we are at the dawn of a new information revolution. This time however, the information stored and processed won’t be with 1′s and 0′s on silicon chips, but rather encoded in the operating system of life itself: DNA. Genetic engineering and synthetic biology empowers people to alter the molecular mechanisms of cells and viruses, agents that can replicate and spread, potentially beyond human control. This shouldn’t just be a national security concern. It should be a global security concern.

Though we are in the earliest days of developing the emerging field of synthetic biology, in the coming years, it promises to have massive impact on everything from business to medicine and energy to warfare. The Chinese government and BGI clearly understand this and are pouring tremendous resources into research and development of these biotechnologies. That US Representative Frank R. Wolf, Republican of Virginia, was the only member of Congress known to have publicly expressed concern about BGI’s purchase of Complete Genomics is not just startling. It is also emblematic of how far the rest of Congress is from understanding how quickly the biotech revolution will be upon us and how dramatically it will impact all facets of our world.

For America to remain competitive, the appropriate public policy response is to ban neither research nor international trade, but rather to invest heavily in both. The United States government, through its public funding of DARPA, was responsible for the creation of the Internet and our nation reaped untold wealth as the progenitor of the information revolution. Yet the economic gains realized from the Internet may be dwarfed by coming boom in genetics and biotechnology. What role the United States will play in that brave new world is yet unanswered. In the meantime, it is worth studying the progress being undertaken by other nations, including China, and by companies such as BGI, not as a means of inhibiting their scientific progress, but as a catalyst for driving our own.

[Fine, the first question is "what global security concern?" Consider e.g. the clip below from a peer-reviewed paper that appeared in 2010 by the author of not-very-threatening country of UGANDA:

"...a "bio-weapon" may be developed in the laboratory by continuous cycles in which an acutely fatal retrovirus of zoonotic origin is co-cultured in human cell lines, rendering the human cells permissive to that retrovirus tropism. The same procedure may be used to select an appropriate animal carrier or "vector", say chickens, pigs, or even cows. Herein, shedding of the retroviral bio-agent may be enhanced by vaccination of these vector-hosts if they are appropriately adapted to act as natural hosts. Several other models for retrovirus-based bio-weaponry are possible, including starting with a known human retrovirus such as HIV and recombinantly engineering it to be acutely fatal (say by pseudo-enveloping it with or enabling it to express Ebola/Marburg gp1, 2, the major pathogenic protein of filovirus hemorrhagic fever). Additional modifications such as altering the transmission dynamics of the retrovirus from contact with infected body fluid to air- or water-borne transmission would make it more damaging, though it is not immediately clear how that could be achieved. More peacefully and productively, the mathematical formalism of retrovirology advanced here also underscores strategies for avoiding or mitigating the impact of retrovirus-based bio-weapons, such as the development of therapeutic interventions and avoidance of contact..."

The above (along with the generalized tensor-theory of mathematical, thus software- and synthetic genomics-enabling treatise of retroviruses) can be found in its entirety on the web.

Do we have to fear (author) Misaki Wayengera in Uganda? Probably not. However, what can be done in Uganda, cannot be done just anywhere in the World?

Were physicists (Drs. Szilard and Teller) signaling the Germans who started to mine uranium-ores in the Czech mountains? Yes, leading not only to the Manhattan Project, but also to the facilities of Alamogorodo and later Lawrence-Livermore (the latter today the single facility of the Department of Homeland Defense). Was the Soviet Sputnik a signal of global threat by means of intercontinental ballistic rockets possibly reaching any point of the USA (just as a virus could today)? Yes, (via JFK' historical call) leading to Congress creating an entirely new government-branch of NASA (with a facility of Ames Res. Ctr. in the heart of Silicon Valley - perhaps less important for US government space projects than the host of the summer-school of "Singularity" :-) What NIH, NSF and DARPA could not do thus far for Genome Informatics, can not be realistically expected from the same. This worker, having worked as a National Science Academy "National Research Council" scientist assigned to NASA Ames Res. Ctr., over two decades ago (1990) was at that time somewhat naive to propose their cooperation, still found on the web - but in frustration detoured by the award by the Humboldt Prize by Germany. It is respectfully submitted, that today no single US government Agency, much less any of their "cooperation", could do what only Congress might accomplish, e.g. when bringing to life the Manhattan Project, or NASA (respectively). Significant progress could be achieved by even less; e.g. by switching the Ames Res. Ctr. of Silicon Valley from NASA to the Department of Homeland Defense, with a unified command of the Lawrence-Livermore facility for highly classified genome projects, and deploying the Ames Res. Ctr. (similarly as it was deployed for the "Information Superhighway", a.k.a. "Internet") to spearhead developments comparable how the Chinese Government utilizes a "private company" (Beijing GENOME Institute). Food for thought - Pellionisz, holgentech_at_gmail_dot_com ]

Playing Well with Others (when Industrialization of Genomics is no longer played only in Academia)

Despite the criticism Myriad Genetics receives for its business practices regarding BRCA testing, the company has stayed on message about two things. One, that its exclusive licenses and patents on BRCA 1 and BRCA 2 mutations, which essentially give it a monopoly over the BRCA testing market for hereditary breast and ovarian cancer, is good for business. And two, that the enforcement of its IP rights hasn't been harmful for patients or for researchers looking to develop better tests.

Researchers and patients are, of course, challenging Myriad on these very points in Association for Molecular Pathology et al. v. USPTO et al. In the case, slated for the Supreme Court this year, plaintiffs are challenging patents on BRCA 1 and BRCA 2 mutations held by the University of Utah and exclusively licensed to Myriad, alleging that Myriad's patents are invalid because they claim gene sequences in the body, which are naturally occurring substances and cannot be patented under US law.

While the plaintiffs in AMP v. USPTO assert that Myriad's patent position is stifling research and patient access to innovative tests, industry observers say that most diagnostic companies don't enforce their patents in the manner Myriad has. In the latest article painting Myriad to be a bad industry player, Bloomberg's Robert Langreth highlights the stories of patients who haven't been able to access the most accurate test results and researchers who aren't able to develop and offer the best test science allows because of the company's business practices.

One patient with fallopian tube cancer, Tory Galloway, received a negative result for disease-linked mutations by Myriad's test, and told her four sisters that the disease was unlikely to be hereditary. However, after being tested by the BROCA Cancer Risk Panel at the University of Washington, Galloway found out that her cancer was due to a gene mutation that wasn't part of Myriad's test.

Daily Scan's sister publication Clinical Sequencing News previously reported that the inventors of BROCA — breast cancer genetics pioneer Mary-Claire King and UW's Tom Walsh — excluded BRCA1 and BRCA2 from the panel of genes the targeted sequencing test gauges. The researchers will not add these genes to their test until "the patent situation is regularized," King told CSN.

The Bloomberg piece also discusses what many breast and ovarian cancer clinicians have been saying for some time, that Myriad is not playing nice with other researchers as it keeps its data on variants of unknown significance in a proprietary database. The impact of this practice is illustrated by the example of Runi Limary, who found a cancerous lump in her right breast at the age of 28. Limary had the breast removed and received months of chemotherapy and antibody treatment and, eventually, was able to get Myriad's test after her employer-provided insurance agreed to cover it.

Testing revealed Limary had an extremely rare BRCA1 mutation and Myriad could not tell her definitively if it was harmful or not. Limary, a plaintiff in AMP v. USPTO, believes that if Myriad’s proprietary database was public and more companies were offering BRCA testing, then she might have had more information on what her BRCA mutations meant for her health.

Our sister publication Pharmacogenomics Reporter recently detailed the disagreement among researchers and industry players about whether or not to share gene-disease association data for rare or uncertain markers. Some clinicians and industry players say that sharing of such databases is critical as next-generation sequencing technologies become more commonplace in research and patient care. Others are of the view that the personalized healthcare revolution will be led by those that can interpret patients' molecular data and, therefore, making public the kind of database Myriad has amassed would be foolish from a competitive standpoint.

Unsurprisingly, Myriad falls in the latter camp. Characterizing Myriad as an "unabashed financial success," the Bloomberg piece also quotes CEO Peter Meldrum defending the company's efforts to keep its VUS database secret. Sharing "doesn't make a lot of business sense," Meldrum says.

[Nobelist Jim Watson was right to resist "patenting" - (yes, TWENTY years ago...) when Genomics was in the Academic Discovery Stage. In the new age of Industrialized Genomics, however, huge global investments at the size of Intel, Samsung, Siemens, Roche, China's BGI (etc, etc) are in a dog-fight over even hotly competed "small entities" like Complete Genomics or Illumina. The global competition is to the tune of $Bn-s already (Baylor's "Moon Shot" over cancer is ticketed $3 Bn). Even at the tiny level of an individual, investing decade(s)-worth of efforts to create novel Intellectual Property, not only without any backing at all, but against the strongest of head-winds, extracts an untold saga of time (life), blod and tears - how would substantial global investors be required to give up accepted legal instruments of IP protection (patents)? Quest Diagnostics invested close to a $Bn into genomic patent(s) - without legal protection genomics will be left high and dry with government funds dissipating - if the avalanche of smart money from industrial investors would be left unprotected. - Pellionisz]

The Decade of Genomic Uncertainty is Over (R.I.P. 2002-2012) -

The new era of Genomic Certainty has turned 10 years young.

Now over a "Decade of Genomic Uncertainty" ago, in 2002 Silicon Valley Journalist wrote in the e-version of "San Francisco Chronicle":

"When the human genome was first sequenced in June 2000, there were two pretty big surprises. The first was that humans have only about 30,000-40,000 identifiable genes, not the 100,000 or more many researchers were expecting. The lower -- and more humbling -- number means humans have just one-third more genes than a common species of worm.

The second stunner was how much human genetic material -- more than 90 percent -- is made up of what scientists were calling "junk DNA." The term was coined to describe similar but not completely identical repetitive sequences of amino acids (the same substances that make genes), which appeared to have no function or purpose. The main theory at the time was that these apparently non-working sections of DNA were just evolutionary leftovers, much like our earlobes.

But if biophysicist Andras Pellionisz is correct, genetic science may be on the verge of yielding its third -- and by far biggest -- surprise."

After an arduous agony of an entire decade, with ENCODE kicked in by 2003 and concluded in 2007, the "gene-junk-central dogma" concept, that Craig Venter rightly called "we're at a frighteningly unsophisticated level of genome interpretation"; with ENCODE-2012 the old science establishment of genome function interpretation had finally collapsed.

Now the challenge is how the fractal seeds planted as early as 2002 shoot into the strong stem of clinical applications, especially in fighting cancer, provide an ecosystem for the "industrialization of genomics", as part of "genome based economy".

As listed already, a brief timeline provides a review of formative events of the "Decade of Genomic Uncertainty" - Pellionisz

A Perspective; 2002-2012

from Inception in 2002 to Proofs of Concept and Impending Clinical Applications by 2012

National Medal of Science Awarded to Leroy Hood, MD, PhD, President and Co-founder, Institute for Systems Biology


Dr. Leroy Hood was awarded the National Medal of Science in recognition of his visionary work in science and engineering.

Dr. Leroy Hood is the recipient of a 2012 National Medal of Science.

Dr. Hood is a world-renowned scientist, inventor, entrepreneur and visionary. His discoveries have permanently changed the course of biology and revolutionized the understanding of genetics, life, and human health. Dr. Hood developed automated technologies for analyzing proteins and genes that enabled the mapping of the human genome and revolutionized the field of genomics. He is a pioneer in the field of systems biology and has spent his career advancing an interdisciplinary, systems approach to biological research and clinical medicine.

Dr. Hood is being honored for his significant body of work in the study of molecular immunology, biotechnology and genomics. Dr. Hood is a pioneer of the systems approach to biology and medicine that focuses on innovation in health, wellness and disease prevention through P4 (predictive, preventive, personalized and participatory) Medicine. His work in this area is contributing to the emergence of a healthcare system that will deliver more effective clinical care at a lower cost.

“I am deeply honored to receive a National Medal of Science, and am profoundly grateful to the many fantastic colleagues and partners with whom I have worked throughout the years. Transforming human health is my life’s work and I am proud of all we have accomplished.”

– Dr. Leroy Hood

The National Medal of Science is one of the highest honors bestowed by the United States Government upon scientists, engineers and inventors.

Interview: A systematic future?

19 February 2007

Leroy Hood talks to Katherine Vickers about Google, prions and the human genome project.

Who or what originally inspired you to become a scientist?

I guess there were several things. I grew up in Montana, where my father was an electrical engineer for the mountain state telephone company. Very early on, while I was still in high school, he got me involved in the courses he taught on topics like electronic engineering.

During my last three summers of high school I worked at a summer camp that was managed by my grandfather, a geology camp in southwestern Montana for students from Princeton and Yale, and I ended up taking courses with the students that went out for that.

And finally, at high school; three of the best teachers I ever had were math and science teachers. They started me thinking seriously about a career in science. One of them was instrumental in persuading me to go to Caltech as an undergraduate, and that's where my career in science got started seriously.

What is systems biology?

The idea of systems biology is actually very old. 150 years ago people were interested in homeostasis, and that's the idea that you look globally at a system, not just at one protein or one gene at a time, to understand how it functions. But what's new today is that we can now do global analysis of many types of information, for example genomes, RNA, (in theory) proteins, metabolites and things like that. We're also learning how to integrate different levels of such information, which will help the understanding of systems. [Interestingly, the RNA System is largely an enigma, why/how coding- and non-coding RNA, mathematically of covariant and contravariant valences, impact by RNA interference - AJP]

What research projects are you working on at the moment?

"We've developed a much deeper understanding of the kind of changes that occur in prostate cancer, and from these studies we've developed totally new, very-early-on blood diagnostic approaches to detection. "We're working on a series of projects to do with new technological developments. So, we're working with collaborators making nanotechnology devices that we hope, in five years time, will be able to quantitatively measure a thousand blood proteins from a fraction of a droplet of blood.

We're collaborating with a company called Helicos BioSciences Corporation with single strand DNA sequencing, and I see this as the gateway to preventive medicine in the future. Each individual will have their genome sequenced and that will be the basis for future health predictions.

And then we're working on a series of microfluidic devices that will let us analyse single cells, and I think an understanding of single cells is going to be one of the next frontiers in biology.

On the systems biology end we're very interested in using systems approaches to study disease. The disease we've studied for the longest time is prostate cancer. We've developed a much deeper understanding of the kind of changes that occur in prostate cancer, and from these studies we've developed totally new, very-early-on blood diagnostic approaches to detection.

One of the major projects we're working on is prion disease in mice. We want to look at the dynamics of the disease and to see how the biological networks and cells of the brain actually change in correspondence to the pathophysiology of the disease. We found that some of the early diagnostic tests we discovered for prostate cancer are going to work for this infectious disease as well.

The other thing we're doing is developing a series of computational analyses. One example will let us analyse the blood molecular fingerprint of specific organs in mice and humans. From those measurements we can actually deduce the nature of the disease perturbed networks in the corresponding tissues.

What would you say has been the biggest challenge you've faced in your research career?

I would say that managing science, rather than the science itself, has been the biggest challenge. New ideas really need new organisational structures and it is often the newer generations of scientists that are more open to these new ideas. This was the motivation behind setting up the Institute for Systems Biology.

You were involved in the start of the human genome project. How do you think this has influenced science today?

Yes, I was involved, mainly because of our DNA sequencing machine, and was supportive of the start of the genome project. It brought about DNA arrays, promoted the idea of systems biology, and the realisation of the importance of computation and technologies in biology, and the view of biology as an informational science.

How far do you think we are away from personalised and predictive medicine?

"We will see a big change in the way we practise medicine and today's medical students are probably being taught incorrectly."Very close. In the next five to ten years we will have powerful tools for analysing individuals' genomes. There will be billions of measurements made on each patient, and then the problem arises of how to handle all this data. This is something we have approached Google and Microsoft about and we will be working with them. We will see a big change in the way we practise medicine and today's medical students are probably being taught incorrectly. Medicine will become digitalised and this will probably reduce the cost of healthcare and provide better allowances for the developing world. People are going to be living more actively in their 80s, and changes will need to be made in society to reflect these changes.

One final question - if you weren't a scientist what would you be?

I think I would be a writer, that's something I've always been interested in. But actually if I'm honest I couldn't imagine being anything other than a scientist.

[A Compelling Case for Fractal Analysis of Cancer and DNA] Is the Cure for Cancer Inside You?


New York Times

Claudia Steinman saw her husband’s BlackBerry blinking in the dark. It had gone untouched for several days, in a bowl beside his keys, the last thing on anybody’s mind. But about an hour before sunrise, she got up to get a glass of water and, while padding toward the kitchen, found an e-mail time-stamped early that morning — “Sent: Monday, Oct. 3, 2011, 5:23 a.m. Subject: Nobel Prize. Message: Dear Dr. Steinman, I have good news for you. The Nobel Assembly has today decided to award you the Nobel Prize in Physiology or Medicine for 2011.” Before she finished reading, Claudia was hollering at her daughter to wake up. “Dad got the Nobel!” she cried. Alexis, still half-asleep, told her she was crazy. Her father had been dead for three days.

The Nobel Foundation doesn’t allow posthumous awards, so when news of Ralph Steinman’s death reached Stockholm a few hours later, a minor intrigue ensued over whether the committee would have to rescind the prize. It would not, in fact; but while newspapers stressed the medal mishap (“Nobel jury left red-faced by death of laureate”), they spent less time on the strange story behind the gaffe. That Steinman’s eligibility was even in question, that he’d been dead for just three days instead of, say, three years, was itself a minor miracle.

In the spring of 2007, Steinman, a 64-year-old senior physician and research immunologist at Rockefeller University in New York, had come home from a ski trip with a bad case of diarrhea, and a few days later he showed up for work with yellow eyes and yellow skin — symptoms of a cancerous mass the size of a kiwi that was growing on the head of his pancreas. Soon he learned that the disease had made its way into nearby lymph nodes. Among patients with his condition, 80 percent are dead within the first year; another 90 percent die the year after that. When he told his children about the tumor over Skype, he said, “Don’t Google it.”

But for a man who had spent his life in the laboratory, who brought copies of The New England Journal of Medicine on hiking trips to Vermont and always made sure that family vacations overlapped with scientific symposia, there was only one way to react to such an awful diagnosis — as a scientist. The outlook for pancreatic cancer is so poor, and the established treatments so useless, that any patient who has the disease might as well shoot the moon with new, untested therapies. For Steinman, the prognosis offered the opportunity to run one last experiment.

In the long struggle that was to come, Steinman would try anything and everything that might extend his life, but he placed his greatest hope in a field he helped create, one based on discoveries for which he would earn his Nobel Prize. He hoped to reprogram his immune cells to defeat his cancer — to concoct a set of treatments from his body’s own ingredients, which could take over from his chemotherapy and form a customized, dynamic treatment for his disease. These would be as far from off-the-shelf as medicines can get: vaccines designed for the tumor in his gut, made from the products of his plasma, that could only ever work for him.

Steinman would be the only patient in this makeshift trial, but the personalized approach for which he would serve as both visionary and guinea pig has implications for the rest of us. It is known as cancer immunotherapy, and its offshoots have just now begun to make their way into the clinic, and treatments have been approved for tumors of the skin and of the prostate. For his last experiment, conducted with no control group, Steinman would try to make his life into a useful anecdote — a test of how the treatments he assembled might be put to work. “Once he got diagnosed with cancer, he really started talking about changing the paradigm of cancer treatment,” his daughter Alexis says. “That’s all he knew how to do. He knew how to be a scientist.”

First, Steinman needed to see his tumor. Not an M.R.I. or CT scan, but the material itself. The trouble was that most people with his cancer never have surgery. If there’s cause to think the tumor has spread — and there usually is — it may not be worth the risk of having it removed, along with the bile duct, the gallbladder, large portions of the stomach and the duodenum. Luckily for Steinman, early scans showed that his tumor was a candidate for resection. On the morning of April 3, 2007, less than two weeks after his diagnosis, he went in for the four-hour procedure at Memorial Sloan-Kettering Cancer Center, just across the avenue from his office at Rockefeller University.

After two hours on the operating table, his surgeon, Dan Coit, lifted the tumor from his abdomen. It was about two and a half inches long. Coit stitched a short thread across its top and a longer one on the side — an embroidered code to help the pathologists get oriented — and sent the specimen upstairs, wrapped in a towel and nestled in a tray of ice.

Claudia and Alexis were waiting in the lobby, along with Sarah Schlesinger, a longtime friend and member of Steinman’s lab, who is also a board-certified pathologist. It would be her job to manage the disbursement of the tumor to Steinman’s colleagues around the world, so its every nuance could be tested and its fragments incorporated into the drugs that would compose his treatment. When she arrived at the lab upstairs and held the tumor, it was still so warm that she could feel the heat through her latex gloves.

She chopped and sliced the tumor into samples, based on a list that Steinman helped draw up beforehand. A few grams would be placed in screw-top vials filled with a preservative for their RNA. Steinman’s administrative assistant would take another piece to Boston on an afternoon train, and some would go to a former student, Kang Liu, so she could sew confetti-sized squares of the tumor into living mice. If there was any left, they would send it to a researcher in Baltimore named Elizabeth Jaffee, who had mastered the art of culturing pancreatic cancer in a dish.

The mass was big enough that Schlesinger could get through all the items on the list. In the days, weeks and months that followed, Steinman’s cancer was sent to labs in Boston and Baltimore, Toronto and Tübingen, Germany, Dallas and Durham, N.C. With help from friends and former students, he would squeeze every bit of data from his cancer that he could.

Steinman’s last experiment would be, in many ways, the culmination of a new trend in cancer research: designing custom treatments for each patient. When he got sick, Steinman knew that the five-year survival rate for his kind of tumor was, at most, 1 in 10, even at Sloan-Kettering, one of the best oncology centers in the world. Typically, patients live six months. But he also knew that his chances might not be as bad as they looked. The means and medians of his disease were drawn from populations and so did not reflect the fact that every tumor is unique. Even tumors that look the same — cancers starting from a common organ, or a common kind of cell — may behave in different ways: some shrink and some expand; some succumb to chemotherapy. Now doctors can scan each tumor for clues about its DNA and use those clues to determine its strengths and weaknesses. Steinman could have his case described right down to the letters of its genome, in hopes of figuring out which therapies might work best for him.

This “personalized” approach to treating cancer, which subdivides the classic types according to distortions in their genes, has been growing at a rapid pace. In the past few years, laboratories financed by the government have set out to build a comprehensive atlas of the cancer genome — to collect 500 tumors from each of 25 kinds of the disease and then to analyze their DNA and RNA at a cost of more than $100 million a year. The advent of inexpensive genome sequencing has produced a gold rush in the commercial sector, too, with the promise that anyone’s tumor can be sliced and processed and analyzed, until its genetic fingerprint is decoded.

“It was thought a while ago that cancer would be too complex for us to really get our hands around it,” says Raju Kucherlapati, one of the principal investigators on the Cancer Genome Atlas and a professor of genetics at Harvard Medical School. But current research showed that “the total number of major biochemical pathways that are altered is not limitless.” If that’s true, then doctors might use these genomic data to improve their patients’ odds. Instead of applying a one-size-fits-all approach to treatment, they could select a mix of therapies from a standard arsenal, choosing only those that matched the features of a patient’s tumor. “I would venture to say that within the next 10 years, we could see a very significant revolution in the way that we think about and treat cancer,” Kucherlapati says.

The genomic approach that Kucherlapati and others have advanced sees every person’s cancer as a snowflake — a crystal made from several dozen basic shapes. But this idea has lately run across a deeper layer of complexity and one that is only now being outlined in the lab. For a paper published in the spring of 2012, a group of scientists based in London looked at tiny pebbles of disease from four kidney-cancer patients. Instead of limiting their analysis to a single piece of each tumor — one piece of tissue, excised after surgery or drawn out through a needle — the researchers took malignant cells from all over the patients’ bodies. They sliced specimens from more than half a dozen spots on the primary tumor, and then more from places where the cancer had spread: in the lungs, the chest wall and the fat surrounding the kidneys. When they compared the genomes at each location, they found a whole suite of tumor types with only a distant family resemblance, as if each spot and organ had become the home for its own phylum of disease. The growths were related — they had all descended from a common ancestor — but the cancer had mutated in new directions, sprouting a canopy of branches and twigs on its evolutionary tree. Samples drawn right from a kidney — as close as possible to where the tumor started — shared only a third of their mutations with the other offshoots.

A number of recent studies came to similar conclusions. Taken together, they reiterate what has long been known but not quite grasped in such detail: that even a single cancer patient carries a private ecosystem of pathology within her body, a tropical rain forest of disease. If the old chemotherapies and radioactive treatments worked like napalm to blast away the canopy, the new breed of personalized therapies target only specific plants. For some cancers, the more homogeneous ones, they do the job just fine. For others, though, the approach comes up against the relentless rules of Darwinian selection. Wipe out one subtype of a cancer — the clone that seems most aggressive, say, or the one that’s most prevalent in a biopsy — and you may have slowed the disease or thinned it out. But the cells left behind might represent a fitter strain and fill the niche.

Faced with this troubling complexity, doctors have fallen back on treating cancer like a game of Whac-A-Mole: find the harshest clone and knock it down, then repeat the process when the tumor reappears. Or else doctors will attack the tree right at its trunk, by finding those ancestral genes that every species in the body shares. But there’s another way to counter cancer’s biodiversity. Our bodies come equipped with a system custom-built to handle pathogens in all their many forms. If the immune organs could be activated against a cancer, we might find a pathway through the jungle and, maybe, to a cure.

“The work that the immune system does to sculpt itself around a cancer — that’s really the ultimate type of personalized medicine,” says Jedd Wolchok, a cancer immunotherapy expert at Memorial Sloan-Kettering who consulted on Steinman’s treatment. “The immune system’s job is to recognize the signs of danger and then with very exquisite precision to mobilize antibodies” and T-cells “that very, very precisely bind to individual targets.” Once that system locks on to its target, it can make adjustments, too, shaping the response to match the contortions and mutations of a tumor in real time. “It’s a therapy that lives,” Wolchok says, “rather than a medicine that passes in and out of the system.”

That’s the approach Steinman believed in most; it’s the one he was pursuing in his lab for many years before he got sick. But for a cancer vaccine to work, for any vaccine to work, the body has to learn the difference between its healthy cells and the ones that have been transformed into disease. It has to recognize its evil twin. And the part of the immune system that makes that possible, the mechanism by which our cells learn to kill one thing and leave another alone, was the focus of Steinman’s whole career.

The cell Steinman hoped would save his life looks something like a sea anemone or a ruffled shrimp dumpling. But when it’s viewed flat under the microscope, those squiggly sheets of membrane extend in cross section, like long, sinewy arms. That’s how they looked one day at Rockefeller in the early 1970s, when Steinman first spotted them in a dish of cells cultured from a crushed-up mouse spleen. When he announced his finding at a meeting in Leiden, the Netherlands, in 1973, he said those appendages reminded him of his tall and graceful wife. He thought about calling them claudiacytes.

Instead, with the assent of his supervisor at Rockefeller, the cell biologist Zanvil Cohn, Steinman declared his cells “dendritic,” from the Greek dendron for tree. This was, he intuited, a kind of cell that had never before been characterized and that served as the missing link in the body’s adaptive response to pathogens. Over the next few decades, Steinman would devote all of his work to the expansion of this idea: he would show his immune cell was not, as many suspected, just an oddball form of the macrophages, but something else entirely — a sentinel that guards our bodies from infection by teaching the soldiers of the immune system to distinguish their enemies from their friends.

The dendritic cell can lurk in the outer layers of the skin, in the throat, in the lining of the intestines and on any other surface where a bacterium or virus might try to edge its way into our flesh. When the cell grabs hold of something strange, it absorbs that foreign matter, digests it and drapes the macerated bits along its membrane. Then the cell inches its way along lymphatic ducts to the places in the body where immune cells gather and communicate and presents these bits as signs of an invasion.

Few took this work seriously in the early years. Lab mates dismissed Steinman’s spindly plasms; in the late 1970s, he lost his government grants. But the work went on, with Steinman evangelizing for his discovery until he inspired a network of immunologists to join his field. “He loved to see himself as a dendritic cell,” Schlesinger says. In a talk he gave in 2007, after winning the Lasker Award for Basic Medical Research, he waved his arms around in demonstration, like the conductor of a symphony with a dendrite baton.

By the 1990s, his discovery had given life to an old idea: that a more perfect knowledge of our immune system would lead to vaccines for otherwise intractable diseases. If the dendritic cell could be hijacked and put to use, if those markers on its membranes could be manipulated, then doctors might be able to inoculate their patients against H.I.V., tuberculosis or even cancer. Early experiments based on this premise came to little in clinical trials, though; Steinman and his colleagues learned it wouldn’t be enough to load the dendritic cells with antigen, to give the body’s bloodhounds sweaty socks. The cells would need another signal too — something to inspire them to share their message with the rest of the immune system. In the absence of that “go” signal, a dendritic cell might do the opposite of what was intended: it might parade its antigens around the lymph nodes as an example of what should be ignored, not what should be killed. Depending on the context, a dendritic cell could induce action or inaction, immunity or tolerance.

But Steinman never lost faith in his discovery as a vehicle for medicine. When he learned that he was sick, he signed up to have his tumor engineered into three existing, experimental vaccines. Each of these had been in testing for patients with other types of cancer, but Steinman had them customized with samples from his own disease. First he tried one, called GVAX, made from his irradiated cancer cells and fitted with a gene that, upon injection, sounds a warning call that recruits dendritic cells. Then he tried a pair of treatments using dendritic cells that were filtered from his blood, loaded with his cancer’s RNA (in one) or peptides (in the other) and put back into his body. In each case, fragments of his tumor would serve as both the quarry and the bait.

“It was just like the old days,” says Ira Mellman, a former trainee in Steinman’s lab and, by the time Steinman got sick, vice president of research oncology at Genentech in San Francisco. “We were all sitting around discussing what next week’s experiments should look like, except this time the experiments were him.” As the treatment plan took shape, Schlesinger managed reams of paperwork. For access to each experimental drug, Steinman would need to enroll himself in a single-patient, compassionate-use protocol with approval from the Food and Drug Administration. (The government receives around 1,000 applications for these one-person treatments every year and grants almost all of them, as long as the patient has cooperation from doctors and the relevant drug companies.)

Schlesinger also served as Steinman’s physician for the vaccine treatments, administering the shots, taking blood and checking up to see how he was doing. The team kept track of his response to each immune-based treatment as it played out in his T-cells. But the real benchmark, and the better index of his disease, was a carbohydrate protein called CA19-9 — a tumor byproduct that was also measured in his blood. When his levels were going down, it meant the cancer was in retreat. After each phase of his experiment, Steinman plotted out his readings and pasted them into slides on PowerPoint.

The same vaccines that Steinman received have shown promise in other patients. The irradiated-cell approach may increase survival for some patients with metastatic prostate cancer. A team based at Baylor University in Dallas has found encouraging results for reinfused dendritic cells in Stage 4 melanoma. But for the man who would later win the Nobel Prize for discovering dendritic cells, would these treatments work at all?

Steinman stayed in good health for the first few years — he still went for runs in Central Park or along the Charles in Boston — though the numbers from his blood tests were at times disheartening. His T-cells showed some signs of activation: they could recognize the markers from his cancer, but there was no way to tell if they were getting inside his tumor. “He wanted to see a much better response,” says Rafick-Pierre Sekaly, an immunologist at the Vaccine and Gene Therapy Institute of Florida who helped to analyze the data. In between the experimental treatments, Steinman was taking a drug called gemcitabine, a chemotherapy traditionally used in the treatment of pancreatic cancer to which he had a very good response. When he took gemcitabine, his CA19-9 would founder; the cancer would start to disappear. When he switched onto the vaccines, the tumor readings inched back up. “That was so upsetting to him, that he always needed the chemotherapy,” Sekaly says.

When he wasn’t on vaccines or chemotherapy, Steinman tried whatever else he could find. He had his tumor’s genome sequenced, to check for special vulnerabilities. At Genentech, Mellman tested a sample of Steinman’s tumor in a dish against the company’s whole library of pharmaceuticals. “We threw at his cells every drug that we had in development at the time,” he says, including many that hadn’t yet entered clinical trials. Meanwhile, the mice that received pieces of Steinman’s tumor served as minifactories for the production of his cancer and also as his patient-avatars in the lab. When one of Mellman’s drugs showed promise in a dish — a signaling inhibitor called vismodegib — he sent it for a trial in the cancer-ridden mice. When they responded, too, Steinman took it himself. It did not appear to work.

Still, years went by and Steinman’s disease never spread far enough to kill him. Was it just the chemotherapy that kept his tumor growth in check? Or had his custom-made vaccines acted in more subtle ways? It’s now well known that immunotherapies can linger in the body even as a tumor grows, and then start to shrink the tumor later on. It’s also possible that the vaccines and chemo worked in concert. But with no other patients for comparison and so little time between treatments to let the data run their course, the details remained a mystery. Mellman expressed skepticism about the treatment’s efficacy. Schlesinger was more positive, as was Coit, his surgeon. “I mean, look at his course,” Coit said. “The average survival even after a complete resection is measured in months, maybe a year and a half, and yet he kept going and going and going. You can’t help wondering if some of it had to do with this very innovative, novel approach.” As for Steinman himself, he wouldn’t make a claim one way or the other. “He totally, definitely felt that it was helping him,” says his daughter Alexis, but feeling is different from knowing. Though he kept careful notes about his treatment and joked with Schlesinger of writing up his one-man trial for The New England Journal of Medicine — in a case study titled “My Tumor and How I Solved It” — in the end there wasn’t any proof.

“Ralph was this remarkable mixture of optimism and skepticism,” Mellman says. “He always knew how this was going to end, and that he was living on borrowed time.”

At her mother’s suggestion, Alexis Steinman flew to New York, on Sept. 11, 2011, and found her father in a sickly state. For the first time since he had the disease, Steinman had begun to deteriorate. He was coughing so violently, her mother had told her, that she thought he might have broken a rib.

Alone with Alexis, Steinman said: “I have cancer in my bones.” Until then, he lived with his disease in much the way he lived before: working long days in the lab and long nights at his computer; traveling to conferences around the world; treating the lab to Entenmann’s cake. Now, for the first time since his diagnosis, he started losing hope in his treatment plan. He became depressed.

The cancer had stopped responding to gemcitabine, and his CA19-9 readings were out of control. On Sept. 18, he tried one more drug — a targeted therapy that had shown some very modest benefits and seemed well suited to his case, at least according to the data from his cancer genome. But it was too late; the disease had already spread throughout his body.

Steinman started planning for the end. “You know how they have those events in the Caspary” — the auditorium at Rockefeller University — “where somebody comes and plays classical music and they talk about you?” he asked Claudia. “I don’t want any of that.” He also told her that there should be no sitting shiva on his behalf. (“I don’t want people coming to the house for seven days,” he said.) Then he met with his closest friend at Rockefeller, a former grad student named Michel Nussenzweig. They discussed what would happen to Steinman’s students and his postdocs. Some he called himself, apologizing for leaving them before their work was done.

On the night of Sept. 24, Steinman ate dinner with his family in a faculty apartment on the Upper East Side of Manhattan. Claudia was there, and their three children and three grandchildren, too. The next morning, sitting on his bed, Alexis saw that he was finding it very hard to breathe. “I think I need to go to the hospital,” he announced. When they arrived at Sloan-Kettering to see his oncologist, he said, “I don’t think I’m getting out of here.”

He died five days later.

On a sunny day last August, almost one year after Steinman won the Nobel Prize, I saw his tumor for myself. Its cells were plastered to the bottom of a plastic case, 20 million tiny cancers crowded into a space the size of a large matchbox. A few days before my visit, the cancer was taken out of the freezer and left to thaw. As I peered at the last living remnants of Steinman’s body through a low-power scope, Sara Solt, a lab technician at Johns Hopkins, gave me her assessment: “Those handlike substances,” she said, referring to some spears of cytoplasm, “they almost look mean.”

For someone who has never seen a pancreatic cancer cell, though, Steinman’s disease didn’t look so mean at all — not black or jagged, just a bunch of soft-edged pentagons and distorted squares, with a few translucent tendrils jutting from their membranes.

The lab at Hopkins is run by Elizabeth Jaffee, the expert on vaccines for pancreatic cancer who received a part of the tumor for analysis. The vaccine she is testing in the clinic matches one of those Steinman received: it mixes bits of tumor — targets for the patient’s immune response — with a signal that recruits dendritic cells. As we sat together in her office, Jaffee reviewed what remains unknown about the method. It’s not yet clear how best to pick those targets. Steinman could have used a more standardized approach, with certain proteins preselected to maximize response; instead, he went with samples of his own disease, hoping these would give his dendritic cells something more to go on. But his tumor might have yielded a thousand targets for his T-cells, a protein soup swimming with red herrings. We still don’t know which strategy works best, Jaffee told me.

There’s another challenge, too, that Steinman had little chance to work around. Any cancer that has grown big enough to harm your health is one that has already figured out a way to hinder any T-cells that come after it. It has evolved a path around the body’s natural defenses. So it stands to reason that if you want to make an immune-based treatment work, you have to add in some other tumor-fighting drug, one that counteracts the tumor’s schemes for keeping immunity in check. “Vaccines alone are not going to be enough,” Jaffee said. “When in cancer, especially metastatic cancer, has one agent ever cured anybody? It doesn’t do it.”

Scientists have only just begun to understand how a tumor can shield itself from T-cells and to make a set of drugs that work against those mechanisms. When Steinman began his treatment, he and others in the field knew of one drug, called ipilimumab, that could do just this. Taken on its own, the drug appeared to extend the lives of patients with metastatic melanoma by months or even years. Yet the company that makes it, Bristol-Myers Squibb, was trying hard to get approval for single-agent use and wouldn’t allow Steinman to pair the drug with his vaccines. Researchers may have worried that the untested combination could have side effects that would delay its approval. (Citing company policy against discussing individual cases, Bristol-Myers declined to comment on Steinman’s treatment.) So Steinman tried the drug on its own in 2010. Instead of charging up his immune cells to fight off the pancreatic cancer, it knocked his T-cells into overdrive. They attacked his intestines and his pituitary gland, leading to dehydration and diarrhea. He ended up in the hospital.

“One of the problems we have in our field is that it’s very hard to combine two agents,” Jaffee said, referring to the bureaucratic hurdles she has faced in using ipilimumab. When she put the drug together with one of the vaccines that Steinman received, both treatments were enhanced. More than a fourth of those enrolled in her preliminary trial for pancreatic cancer — patients who expected to live for two or three months on average — have now survived for at least a year. Even so, Jaffee had trouble getting enough doses from Bristol-Myers Squibb to start a second, bigger test. The company eventually agreed, after ipilimumab was approved by the F.D.A., but the whole process set her research back by a couple of years. “This is my biggest frustration,” she said.

The same was true for Steinman. As the years went by, he was confronted time and again with the limits of what was understood and what was possible. He hoped to integrate his vaccines with chemotherapy and take the treatments simultaneously rather than in sequence. Jaffee’s lab has shown that this approach can enhance the immune response in a different way than ipilimumab does, by killing off a kind of T-cell that’s friendly to a tumor. Or else he might have combined the immunotherapies with drugs selected on the basis of his tumor’s DNA. But no one really knows how best to put these things together, just as no one really knows which antigens a vaccine should target nor how best to mobilize dendritic cells. Scientists now realize that dendritic cells come in dozens of different forms, some of which may be more effective in vaccines than others.

The disconnect between the extraordinary promise of cancer immunotherapies and the vagaries of their application, between the possible and the merely doable, always bothered Steinman. He used to tell his family that his work on dendritic cells might not be relevant until long after he was dead — that it would take years to determine whether vaccines based on his discovery could truly be effective in the treatment of disease. “All of this stuff was literally developing in real time as Ralph’s disease was developing,” Mellman says, “and the disease was ahead, unfortunately.” If Steinman’s personalized treatments worked at all, it was in spite of everything that was still unknown. “It was a laboratory experiment that worked for a while, we think, but we can’t go back and repeat it, so we’ll never know for sure,” Mellman says.

More experiments are on the horizon. Jaffee is building on Steinman’s work by combining the latest round of immune boosters with a dendritic-cell vaccine. There is progress in immunotherapy for other cancers, too: ipilimumab is being used for treating melanoma, and related drugs are in the pipeline that make a tumor more vulnerable to attack. In 2011, The New England Journal of Medicine published the results of a method known as “adoptive T-cell transfer,” in which T-cells are extracted from the body and reprogrammed to go after cancer cells. This has proved a potent treatment for some patients with advanced leukemia, but it poses greater health risks than the vaccines that rely on dendritic cells. “We’re going to learn a lot over the next 10 years,” Jaffee said, as we walked through the lab. “We’re just at the beginning. This is going to be the start of a whole new field.”

Steinman knew he wouldn’t live to see that field reach its full potential. It has been almost 40 years since he discovered the dendritic cell, and doctors have only now begun to make immunotherapies that work. By all accounts, that sluggish pace was deeply frustrating to Steinman, even before he got sick. “His mind went so fast, and he always wanted everything done yesterday,” Schlesinger says. Years ago, the two of them were on their way to their lab, and Steinman was in a foul mood because a trial they hoped to run was taking longer than expected. After some back and forth about the details, he stopped to consider what he had accomplished in his long career. “He said to me, ‘You know, all this time has gone by, and we haven’t cured cancer or found a vaccine for H.I.V.’ ” And then he paused, and told her, “We’ve got to get to work.”

Daniel Engber writes about science and culture. He has a weekly column in Slate.

The FractoGene Decade [collation of sources is available in .pdf with links]

A Perspective; 2002-2012

from Inception in 2002 to Proofs of Concept and Impending Clinical Applications by 2012

Illumina Stock Leaps On Roche Acquisition Reports

Thu, Dec 20 2012 00:00:00 E 00_WEB

By Kevin Shalvey, Investor's Business Daily

Posted 11:50 AM ET

Genome research firm Illumina's (ILMN) shares were up 7% in early trading Thursday, near 55.75, on reports that Swiss pharmaceuticals company Roche Holding (RHHBY) has agreed to acquire the company.

As first reported in Swiss newspaper L'Agefi, Roche might have already agreed to buy Illumina for $66 per share, which would put the purchase price at more than $8 billion. The story was picked up Thursday by Bloomberg and Reuters. Alan Hippe, Roche chief financial officer, says his company is eyeing acquisitions, Bloomberg reported. [Note the plural in acqusitionS. One wonders how quickly the Land Grab will propagate from consolidating Sequencing to major purchases of Analytics IP - Pellionisz]

Shares of Illumina were trading at 16-month highs, though this isn't the first takeover report for the gene-sequencing firm.

The agreement is said to have happened last week, reports say.

Rumors of the possible acquisition have been bouncing around Wall Street for a few weeks, as had a rumor that GlaxoSmithKline (GSK) might have been interested in buying Illumina, as IBD reported. ["Pharma must go Genomics". After Merck (with BGI) and Roche (with Genentech and now it looks, Illumina), GlaxoSmithKline might well be a component in "Party J". With Sequencing consolidated, the Next Big Thing is Analytics - Pellionisz]

Fractal Organization of the Human T Cell Repertoire in Health and Following Stem Cell Transplantation

Jeremy Meier1*, Allison F Hazlett, MS1*, Kassi Avent, MS2*, Jennifer Berrie2*, Kyle Payne2*, David Hamm, MS3*, Cindy Desmarais, PhD3*, Catherine Sanders, PhD3*, Kevin T Hogan, PhD4*, Steven Grant, MD5, Kellie J Archer, PhD6*, Masoud H Manjili, DVM, PhD2*, Catherine Roberts, PhD1* and Amir A Toor, MD1*

1Internal Medicine, Virginia Commonwealth University, Massey Cancer Center, BMT Program, Richmond, VA

2Microbiology & Immunology, Virginia Commonwealth University, Massey Cancer Center, Richmond, VA

3Adaptive Biotechnologies, Seattle, WA

4Massey Cancer Center, Richmond, VA

5Virginia Commonwealth University, Massey Cancer Center, Richmond, VA

6Biostatistics, Virginia Commonwealth University, Massey Cancer Center, Richmond, VA

T cell repertoire diversity is generated by recombination of variable (V), diversity (D) and joining (J) segments in the T cell receptor (TCR) locus. Further variability and antigen recognition capacity is introduced by nucleotide insertion (NI) in the recombined sequences resulting in a complex repertoire, the organization of which is poorly understood. We postulate that TCR b D, J and V gene segment usage in an individual would result in a TCR repertoire with a fractal, self-similar frequency distribution of T cell clones with respect to gene segment usage. To determine this, the TCR repertoire of donors and recipients of HLA matched-related and unrelated allogeneic stem cell transplantation (SCT) was evaluated by high-throughput (HT) sequencing of the CDR3 region of TCR b.

Ten SCT donor-recipient pairs were selected for HT-TCR b sequencing. cDNA was isolated from T cells obtained from the donors at baseline and recipients at day 100, 1 year post SCT or at the time of graft-versus-host disease (GVHD) diagnosis. HT-TCR β sequencing was performed and analyzed using the ImmunoSEQ analyzer tool (Adaptive Biotechnologies, Seattle, WA). TCR b clone frequencies were used to determine the TCR self-similarity score (SSS = log clone frequency x log scale), evaluating clonal frequency at each gene segment-scale (J, VJ and VJ+NI). This revealed a TCR SSS with a relatively narrow distribution of 1.64 ± 0.1 (mean ± SD) for J, 1.69 ± 0.2 for VJ, and 1.41 ± 0.01 for VJ+NI, which was consistent between all normal stem cell donors analyzed.

Relative proportional distribution (RPD) graphs were then generated to allow for the depiction of the TCR b D, J, V distribution for simultaneous comparison at an individual level. Representative data in Figure 1 shows the relatedness across donors at the TCR b J segment level. Relative clonal frequency was determined for each unique TCR clone at the specified segment level and plotted according to frequency-rank. Slope of the resulting linear regression lines from log-log plots of rank-frequency was used to determine self-similarity and fractal dimension. These plots were comparable among donors with resulting slopes of 1.6 ± 0.01 and 1.8 ± 0.1, respectively for TCR J and VJ containing clones (Figure 2). The plots also revealed a hierarchy of T cell clones, with few dominant clones occupying the high ranks and a multitude of clones in the later ranks.

For donor-recipient comparisons, we examined the dominant ranking clones which would be most likely to be involved in GVHD and response to infection. The ordered TCR clonal frequency distribution seen in donors was perturbed in recipients following SCT, with recipients demonstrating a lower level of complexity in their TCR repertoire, and a large shift in the frequency distribution of the dominant T cell clones compared to the donor. When dominant clones were compared between donors and recipients, recipients shared only a small proportion of TCR clonotypes with their donors despite full donor T cell chimerism. This difference did not change over time, suggesting an alternate T cell clonal hierarchy and repertoire develops in transplant recipients when compared with their donors.

Using simple mathematical analysis, we demonstrate that the TCR b repertoire has a fractal, self-similar pattern with a hierarchy of dominant and minor clones. We note that the complexity of the TCR repertoire is diminished and TCR b hierarchy is altered following SCT. Restoration of this order may serve as a marker for post-SCT immune reconstitution. Further, by demonstrating shifts in TCR clonal dominance, fractal analysis comparing donor and recipient T cell repertoire may allow for more accurate monitoring of immunotherapy of malignancies in general, beyond allogeneic SCT.

Land Rush

There is an increasingly heated-up nation-wide speculation, reaching far into the unforeseeable future, about potential security threats to the USA with Industrialization of Genomics.

We have seen such dire times before. When nuclear industry emerged from the disruptive science of quantum mechanics to strategically decisive applications pertaining to energy, the US responded by securing nearly all the intellect from the World that could, and did, make the difference.

Some futuristic scenarios aside, global players may wish to address economy as an immediate issue.

As genomics has turned into a globally competitive industry, by a land-rush to acquire know-how can and will, as Juan Enriquez predicted over a decade ago, gain dominance over others by gobbling up intellectual property (along with the purchase of assigned IP, or even easier if such is presently un-assigned). Thus, using the leverage of cash in the buy/build classic dilemma, the luckiest parties could gain an extra profit by collecting royalties over the sweat and blood of creating wealth in the first place.

When a Silicon Valley company is acquired, the patent-portfolio assigned to the company is one of the greatest assets. Un-assigned personal IP is perhaps the singularly best investment for security. - Andras Pellionisz

2012 After a Decade of Uncertainty, Genomics is at Crossroads

As calendar year 2012 is wrapping up in a few days, it seems clear that after a "Decade of Uncertainty" (2002-2012) Genomics reached sevenfold crossroads.

1) Old School versus Informatics Science. The most dramatic turn-around for any disruptive technology happens when (see "energy") the underlying science (see "nuclear physics") reaches a change of axioms compelling for science leadership. Comparably to earlier examples, Industrialization of Genomics started with Genentech (based on the "gene" [and Junk]), interpreted by the oversimplified Central Dogma of a DNA>RNA>Protein "arrow model"). However, by September 2012 the ENCODE program concluded for the second time after 2007 that "the scientific community must re-think long held beliefs", calling for a holistic approach to Genomics/Epigenomics/Informatics, see the perspective given by the .pdf compilation The FractoGene Decade. Estimating from the fact that genomics took half a decade (2007-2012) to consolidate a conceptual paradigm-shift from "Junk" to "Function", it is expected that The Principle of Recursive Genome Function (2008) that makes mathematical sense why the fractal folding of DNA structure must provide "functional proximity" in a massively parallel recursion (thus unites the fractal folding structure with the fractal recursive iteration function) might also take half a decade to be fully appreciated by 2013.

2) Sequencing versus Analytics. In 2012 it became evident that pure sequencing supply-business goes bankrupt without the market-pull through analytics. The glut is not confined to any single company - it is characteristical to the entire industrial genomics.

3) Analytics by Hand versus by Computers. Haussler (UCSC) says "In the minute it took me to walk on stage, another person in the U.S. died of cancer. We’ve reduced the death rate from heart disease by about 70 percent over the last 50 years; cancer, only about 10 percent. In the next two years, cancer will replace heart disease as a number one killer in the United States. The white coats have done their best, but we actually need the computer geeks to get involved at this point. We need you, we need your creativity, we need your drive. Why is it the geeks’ turn? Cancer is a digital disease, and it will have a digital cure. Cancer is caused by mutations created by a few cells in your body, causing them to grow in uncontrolled fashion. There are thousands of different types of mutations that occur in a huge number of different combinations. It’s not comprehensible by an unaided human mind, but it would be with the power of a computer-aided analysis". The call for automated analytics by arguably the most qualified creator of "genome browser" is contrasted by Tina Hambuch (Illumina), who says "Illumina is now offering the interpretation of the 344 genes as an option for its Individual Genome Sequencing service, and is able to customize that gene set somewhat on a case-by-case basis...although there are many software tools to aid with steps in the interpretation process, the final assessment of weighing the evidence will be difficult to automate. "There really just isn't a software that can do that at this point in time," Hambuch said. "And in fact, that's not even easy for people to do. We actually did have this team of people, and we would really argue about these things. Some of these are not easy to decide...The analysis required about 19 hours of manual review per genome". To a professional informatics expert, in full agreement with Dave Haussler, scaling of manual analysis of 344 genes (out of about 20,000) to potentially the entire human genome (6.2 million thousands of A,C,T,G-s, massively changing e.g. in the course of cancer/chemo) appears eminently untenable.

4) Analytics must be able to parse parametric (human diversity) "structural variants" from syntax-errors (fractal defects, directly linked to pathology). Ample evidence of an enigmatic wealth of "structural variants" (both very large, such as Copy Number Variations/Alterations (CNV/CNA), or ultimately small such as a Single Nucleotide Polymorphism (SNP) - and every size of repeats in between - renders either manual or computer-aided analytics an exercise of futility unless and until a theoretical (mathematicsl) understanding how to parse them apart is available. Presently, FractoGene is a leading candidate of an algorithmic parsing of myriads of structural variants, see particularly the outline of its global scalable clinical applications (2012).

5) Academia versus Industry. Traditionally, disruptive research & technology inventions have been incubated in Academia (see Internet language of UNIX by Bill Joy, browser by Marc Andressen, search engine by Sergey Brin and Larry Page, etc, etc) - entreprises that quickly outgrew their University home (Sun, Netscape, Google, etc). A major new challenge is that the traditional powerhouses of academic research (NIH in the USA, ENCODE support in UK/EU) experience constraints. Fortunately, just as the Internet transitioned from Academia/Government to Private Domain (1994), the entire DNA Sequencing industry in already in Private Domain, plus SAMSUNG for Analytics marked by Sept. 1st, 2011 a similar transition, though major Academic Centers (Stanford, Cold Spring Harbor, etc) continue to pave way to major advances.

6) National versus Global. USA versus China, with India and Russia "sleeping giants", Korea and Brazil poised to jump.

7) Free versus IP, as early Internet, or Intellectual Property as in Google/Microsoft/Apple/Samsung

Genome Data Analysis, San Francisco 27-29, 2012

Have you cracked the data bottleneck? [See my 2-cents worth at it in paper and google-tech-talk, 2008, 2002 utility secured Oct. 2nd, 2012, write-up Nov. 1st, 2012 and 2013 - AJP]

You’ll know the cost of analysis can outweigh cost of sequencing by 10 to 1, which is a huge headache for anyone trying to actually understand genome information. Answering the fundamental challenges of how to effectively store, transfer and interpret sequencing data will be key to fully unlock the meaningful information contained inside the genome.

These challenges are universally recognized but as yet there are no clear cut answers as to how to overcome this expensive hurdle. Bringing together the world’s brightest minds in data analysis, the World Genome Data Analysis Summit will, for the first time ever, create a truly unique forum where these issues can be addressed.

Featuring cutting-edge case studies from the likes of Roche, BMS, Pfizer, GSK, Sanger Institute, Washington University and many others, you’ll gain access to the latest strategies to control, analyze and interpret your genomic data. Discover new software tools to help efficient transfer of large data volumes, uncover cloud storage solutions to manage data warehousing and hear the industry leaders explain how they’re managing to achieve effective high throughput analysis of their genome sequencing.

[Waiting (busily) for the Next Meeting (Software-enabling approaches to Recursive Genome Function) one wonders if it is an accident that exactly at the time of the SF meeting a third, as yet un-named, "Party J" approached Complete Genomics, hopefully not just to sequence, store DNA data, but also with algorithmic understanding to put the analytics into clinical applications, most notably against cancer? - AJP]

Architecture Reveals Genome’s Secrets

Three-dimensional genome maps are leading to a deeper understanding of how the genome’s form influences its function.

By Sabrina Richards | November 25, 2012

Genome sequencing projects have provided rich troves of information about stretches of DNA that regulate gene expression, as well as how different genetic sequences contribute to health and disease. But these studies misses a key element of the genome—its spatial organization—which has long been recognized as an important regulator of gene expression. Regulatory elements often lie thousands of base pairs away from their target genes, and recent technological advances are allowing scientists to begin examining how distant chromosome locations interact inside a nucleus. The creation and function of 3-D genome organization, some say, is the next frontier of genetics.

Genome spatial organization is critical for gene regulation, explained Job Dekker, a molecular geneticist at the University of Massachusetts Medical School, and “everything else chromosomes do involves three dimensions,” as well. Chromosomes have to replicate, separate properly during division, and change shape during the cell cycle—all without tangling. The genome is “rebuilt entirely after cell division,” Dekker said.

The mechanisms for such delicate orchestration have remained unclear, however. About 10 years ago—just as the human genome project was completing its first draft sequence—Dekker pioneered a new technique, called chromosome conformation capture (C3) that allowed researchers to get a glimpse of how chromosomes are arranged relative to each other in the nucleus. The technique relies on the physical cross-linking of chromosomal regions that lie in close proximity to one another. The regions are then sequenced to identify which regions have been cross-linked. In 2009, using a high throughput version of this basic method, called HiC, Dekker and his collaborators discovered that the human genome appears to adopt a “fractal globule” conformation—a manner of crumpling without knotting.

In the last 3 years, Dekker and others have advanced technology even further, allowing them to paint a more refined picture of how the genome folds—and how this influences gene expression and disease states.

Conversing chromosomes

Dekker’s 2009 findings were a breakthrough in modeling genome folding, but the resolution—about 1 million base pairs—was too crude to allow scientists to really understand how genes interacted with specific regulatory elements. More detail was needed to understand how cells know which areas of the genome “should be talking [to each other], and which shouldn’t,” said Dekker. After all, “you don’t want everybody talking to each other; you want [your genome] to have a decent conversation.”

Recent advances in deep sequencing are now providing researchers with a way to glean that detail. Dekker and his colleagues discovered, for example, that chromosomes can be divided into folding domains—megabase-long segments within which genes and regulatory elements associate more often with one another than with other chromosome sections. The DNA forms loops within the domains that bring a gene into close proximity with a specific regulatory element at a distant location along the chromosome. Another group, that of molecular biologist Bing Ren at the University of California, San Diego, published a similar finding in the same issue of Nature.

Between the two groups, the researchers identified these domains in mouse and human embryonic stem cells and human fibroblasts, suggesting that they are “a fundamental property of the genome,” Ren said. Additionally, both groups found that deleting boundary sections of domains threw gene regulation into disarray, causing previously silent genes to be transcribed and vice versa. These results demonstrate that “domain structure is essential to keep the gene program tightly regulated,” said Ren.

“I think the discovery of [folding] domains will be one of the most fundamental [genetics] discoveries of the last 10 years,” Dekker said. The big questions now are how these domains are formed, and what determines which elements are looped into proximity.

Chromosomes and cancer

In addition to its effect on gene regulation, chromosome folding may also play a role in cancer development. Somatic copy number alterations (SCNAs), or the deletion or amplification of genes, are a hallmark of cancer’s genomic instability. Leonid Mirny’s lab at Massachusetts Institute of Technology, who collaborated with Dekker on the 2009 discovery of “fractal globules,” found that the genome’s loops contribute to the formation of particular SCNAs. Comparing SCNA maps to the 3-D architectures of human cancer genomes, Mirny and colleagues found that genomic regions that formed the ends of the loop—and were therefore in close physical proximity—are likely to be boundaries where the intervening section is deleted or amplified, creating SCNAs.

Translocations, or the abnormal arrangements of chromosome sections, are another hallmark of certain cancers, and also seem to be facilitated by spatial organization. Mirny and his group found that the break points for two well-known translocations—Bcr-Abl in chronic myelogenous leukemia and between Myc and immunoglobulin genes in Burkitt’s lymphoma—are frequently found near each other in normal cells, and especially in cells of the lineages prone to these tumor types.

Tissue-specific differences in translocations may point to subtle differences in genome organization based on cell type. “Presumably in different tissue types there are specifics of the genome organization that we have yet to discover,” said Mirny. How differences in chromosome organization are achieved is another ripe area for study, said Dekker. For example, chromosome folding domains could be determined by some sort of marker in the cell, depending on type and environmental factors. “If boundaries to domains are flexible—turning on or off by cell type—suddenly genes have access to a whole new set of regulatory elements,” Dekker speculated.

In addition to better understanding cancer, chromosome folding may help predict it. As normal cells transition into tumor cells, genes can change their spatial organization in characteristic ways, said Tom Misteli, a cell biologist at the National Cancer Institute at the National Institutes of Health who is using the genome’s 3-D architecture to develop diagnostic tools. His team has shown that in breast cancer, certain genes “change position dramatically as their cells transform into cancer cells,” allowing Misteli and his colleagues to “look at an unknown tissue biopsy, localize genes, and with high accuracy determine whether its cancer or normal,” he said.

[To paraphrase a classic wisdom of biology, it appears that "Nothing makes as much sense about the genome if not interpreted from the viewpoint of principle of recursive genome function (2008)". Given a (Hilbert-fractal) structure of the genome, that enables "functional proximity" of physically distant sections it would be difficult to explain how "they are talking to one-another", if functional recursion (stated as "fractal iterative recursion") could not be formulated into a software-enabling approach. The fractal stages of development of a neuron (Pellionisz, 1989) assumed that the genome is revisited (a double heresy since proteins were not supposed to recurse to DNA information, moreover such recursion would make no sense if the revisited sequences were void of information, would be Junk DNA). Similarly, at an early stage, Grosberg (1993) promulgated the fractal folding of DNA-strand. From the former approach FractoGene emerged (2002-2012), from the latter the Hilbert-fractal was invoked (2009). An overview of Fractal Defects Clogging Recursive Genome Function (linked to cancerous mis-regulation) was provided recently (see .pdf above in full, Pellionisz, 2012), concept illustrated below]

Fractal defect of CNV clogs genome function recursion in Hilbert-curve [.pdf here]

Thanksgiving - having counted our blessings it is time to address the "horror vacui"

Having counted all our ample blessings, also with genomics, it may be time to face a historical challenge. After a "Decade of Uncertainty" in Genomics (2002-2012) with the first conclusion of ENCODE-2007, finally confirmed by a hesitant bulk of ~350 top scientists in ENCODE-2012, a "vacuum exists in general acceptance of software-enabling systemic understanding of genome function and (mis)regulation". Since science abhors any conceptual vacuum, the "horror vacui" have urged pioneers to fill the void. By now efforts towards a deeper understanding are widening into to a mainstream of hard-core science & technology branch. In an avalanche, "tomorrow" it might even be taken for granted (though formerly granting was outright denied).

Perhaps the most succint summation to characterize the "Decade of Uncertainty" is by Venter (2010) "We're at a frighteningly unsophisticated level of genome interpretation"

Such summary statement is probably meant for the rapidly dwindling (yet still not zero) minority of old-schooler workers who somehow omitted to perceive the collapse of the intellectual prison of "gene and junk, further constrained by the prohibition of feedback by some central dogmatic misnomers".

Dozens of independent experimental Proof of Concept papers have been reviewed recently (proceedings is available upon request).

Those wishing to be listed as proponents of hologenomics, both in the sense that the whole DNA might require analysis of some function (beyond "genes" that do not even have now a universally accepted single definition...) and that the whole genome/epigenome requires a system-approach, email Pellionisz at the address of holgentech_at_gmail_dot_com. Names and affiliation will be listed on site.

Formula Unlocks Secrets of Cauliflower's Geometry

ScienceDaily (Oct. 23, 2012) — The laws that govern how intricate surface patterns, such as those found in the cauliflower, develop over time have been described, for the first time, by a group of European researchers.

In a study published October 24, in the Institute of Physics and German Physical Society's New Journal of Physics, researchers have provided a mathematical formula to describe the processes that dictate how cauliflower-like patterns -- a type of fractal pattern -- form and develop.

The term fractal defines a pattern that, when you take a small part of it, looks similar, although perhaps not identical, to its full structure. For example, the leaf of a fern tree resembles the full plant and a river's tributary resembles the shape of the river itself.

Nature is full of fractal patterns; they can be seen in clouds, lightning bolts, crystals, snowflakes, mountains, and blood vessels. The fractal pattern of the cauliflower plant is ubiquitous and can be spotted in numerous living and non-living systems.

The properties of fractals, such as their shapes, sizes and relative positions, have been studied extensively; however, little is known about the processes involved in their formation.

To identify this, the researchers, from Comillas Pontifical University, Universidad Carlos III de Madrid, Instituto de Ciencia de Materiales-CSIC, École Polytechnique and Katholieke Universiteit Leuven, firstly grew thin films using a technique known as chemical vapour deposition (CVD).

CVD is a technique used to grow a solid, in which a substrate is exposed to a number of precursors that react and/or decompose on its surface to create a specific thin film. The researchers tailored the CVD process so the film would grow into shapes similar to those seen on a cauliflower, but limited to the submicron scales.

From this the researchers were able to derive the formula which described how the cauliflower-like patterns develop over time. They proved that the formula was able to successfully predict the final cauliflower-like patterns by comparing them to actual cauliflower plants and combustion fronts, both of which occur at much larger scales.

Co-author of the paper, Mario Castro, said: "In spite of the widespread success of fractal geometry to describe natural and artificial fractal shapes, purely geometrical descriptions do not provide insight into the laws that govern the emergence of the shapes in time.

"We believe that by knowing the general laws that dictate how these patterns form and grow, it will help to identify the biological and physical mechanisms that are at play."

Cauliflower. The laws that govern how intricate surface patterns, such as those found in the cauliflower, develop over time have been described, for the first time. (Credit: © Africa Studio / Fotolia)

Cauliflower Romanesca, with the intricate structural pattern, described as governed by the fractal (recursive iteration) of genome function (Pellionisz, 2008)

[Mario Castro and colleagues properly describe the physics of the surface of cauliflower - "a cabbage with college education", said Mark Twain. Their "first time" article, however, does not even mention "genome" (or "DNA"). The challenge as a result of their great work, therefore is very straightforward - once the DNA of the cauliflower romanesco is available, preferably along with the full DNA of cabbage. With the FractoGene utility, in 2007 CIP specifically illustrating "cauliflower romanesco" it will be revealed how its fractal genome governs the fractal growth. Since fractal theory is, in full generality, is now out in the open (Alexei Kurakin) and he also claims that e.g. the "C-value enigma" is just an epiphenomenon, time seems not too far to understand "college education" of cauliflower over less repetitively schooled cabbage in genomic terms - Pellionisz]

Szentagothai Centenary Tribute in New York City

Janos Szentagothai, who carried the legacy of structure of CNS neural networks from Ramon y Cajal to the function of modern neural net theories (eventually leading to a geometric unification of neuroscience and genomics), was celebrated in the Consulate of Hungary in New York City, November 12, 2012.

Software developers analyzing patterns to boost odds against cancer

Software engineers are moving to the fore in the war on cancer, designing programmes that sift genetic sequencing data at lightning speed and minimal cost to identify patterns in tumors that could lead to the next medical breakthrough.

Their analysis aims to pinpoint the mutations in our genetic code that drive cancers as diverse as breast, ovarian and bowel. The more precise their work is, the better the chance of developing an effective new drug.

Ever since James Watson and Francis Crick discovered the structure of DNA in 1953, scientists have been puzzling over how genes make us who we are. The confluence of computing and medicine is accelerating the pace of genetic research.

But making sense of the swathes of data has become a logjam.

That, in turn has created an opportunity for computer geeks and tech firms such as Microsoft, SAP and Amazon.

Oncology is the largest area of therapy in the global drugs market with market researcher IMS predicting it will increase to $83-$88 billion by 2016 from $62 billion in 2011. Computational genomics - using computers to decipher a person's genetic instructions and the mutations in cancerous cells - is emerging as the driver of this growth.

Life Technologies Corp and Illumina Inc are among firms developing equipment that can extract a person's entire genetic code - their genome - from a cell sample.

The newest machines are about the size of an office printer and can sequence a genome in a day, compared with six to eight weeks a few years ago. They can read the 3.2 billion chemical "bases" that make up the human genetic code for $1,000, compared with $100,000 dollars in 2008.

Growing numbers of software engineers are needed to help make sense of all this data.

"Many labs can now generate the data but fewer people or labs have the expertise and infrastructure to analyze it - this is becoming the bottleneck," said Gad Getz, who heads the Cancer Genome Analysis group at the Broad Institute in Boston, jointly run by MIT and Harvard.

Getz is one of a new generation of computational biologists who develop algorithms to parse data from tens of thousands of cell samples, shared with research institutes around the globe.

He and his team of 30 are trying to establish recurring patterns in the mutations and how they are linked to tumor growth. They are using some 1,200 processing units, each with 4-8 gigabytes of random access memory - about the computing power that comes with most desktop PCs.

Harvesting knowledge

Eli Lilly CEO John Lechleiter sees potential for progress.

"We are starting to harvest the knowledge that we gained through the sequencing of the human genome, our understanding of human genetics, disease pathways. We've got new tools that we can use in the laboratory to help us get to an answer much, much faster," said Lechleiter, whose firm is co-owner of the rights to bowel cancer drug Erbitux.

Approved drugs that take genetic information into account include Amgen's Vectibix and AstraZeneca's Iressa. But both these drugs derive from a single mutation. Sequencing has laid bare many more mutant genes - often hundreds in any given tumor - and highlighted the need for a subtler approach to cancer treatment.

Roche, the world's largest maker of cancer medicines, has spent several million euros on information technology for a pilot scheme examining how cancer cells in petri dishes react to new drugs. The scheme involves crunching hundreds of terabytes of gene sequences.

"It's the first large-scale in-house sequencing project for Roche and we expect more to follow in the near future," said Bryn Roberts, Roche's head of informatics in drug research and early development.

Roberts said the project, which uses processing power equivalent to hundreds of high-end desktop PCs, was self contained but there were plans to draw in external data. This would require advances in cloud computing - using software and computing power from remote data centers - but Roberts said the technology would soon be available.

"The scale of the problem means the solution will be on an international collaborative scale," he said.

Opportunities in clouds

The trend of using cloud computing networks to allow commercial and public researchers to share cancer data is promising for the likes of IBM and Google which according to GBI Research are already established providers of cloud computing to drug makers' research efforts.

Amazon, with its cloud computing unit AWS, said it is benefiting as life science researchers rethink how data is stored, analyzed and shared. "We are happy with the growth we are seeing," a spokesman said, declining to provide figures.

Microsoft said it was dedicating "significant resources" to the expansion of cloud computing in the health and life sciences markets.

"Pharma R&D will be working with other technology companies, like Microsoft, in developing new algorithms, methodologies and indeed even therapies themselves," said Les Jordan, chief technology strategist at Microsoft's Life Sciences unit.

The world's largest business software company SAP has teamed up with German genetic testing specialist Qiagen. They are modifying SAP database software so that certain cancer diagnostic tests, which now keep a network of super computers busy for days, can be run on a desktop PC within hours.

Genetic analysis has revealed that types of cancer, now treated as one because they are in the same organ and look the same under the microscope, are driven by different genetics.

Hans Lehrach at the Max Planck Institute for Molecular Genetics in Berlin says every single tumor should be seen as an "orphan disease", using a term for rare illnesses that typically prompt drug regulators to make drug approval easier.

He has designed a software he describes as a virtual patient. It suggests a drug or a mix of drugs based on each tumor's genetic fingerprint. A single case can take several days to be processed.

Lehrach, a geneticist who says he has written software code throughout his scientific career, likens his approach to that of a meteorologist who regards every day's set of readings as unique.

Taking the analogy further, he says the convention of stratifying cancer patients is equivalent to a weather forecast based on simple rules such as 'red sky in the morning, sailor take warning'.

At a unit of Berlin's Charite university hospital, 20 patients left with no other treatment options for their aggressive type of skin cancer are being diagnosed based on Lehrach's computer model.

The trial is exploratory and there are no results yet on the overall treatment success, but the project, like many others, is driven by the hope that cancer can be wrestled down by sheer computing power.

[“With time a Microsoft or Google type IT will acquire – or build – an IT-led pharma.” - said a pharma-guru, cited here. What software-enabling approach to genome (mis)regulation will IT use?]

Genomics Industrialized. Patents Drive Innovation

[Genomeweb lists, for a fee, a number of issued patents in genome informatics. It may be a signal of the new times of genome informatics (very much like formerly the Internet), that from a largely "government-subsidized research and development" this boom is also turning into an industry on its own. Since the Genomeweb-list of patents is "for fee", it can not be reproduced here. Suffice to note that FractoGene, issued to Pellionisz is on the list (Fractal genome governs fractal organisms).

There may be an opinion that the emergence of industrialized genomics, ruled by traditional business interests, might not be a good thing - a topic certainly worth discussing (Twitter @holgentech or Andras Pellionisz on FaceBook).

This columnists makes a point that innovations can be extrordinarily taxing (for a long time now, developing a new drug costs fortunes, and if the innovation can not be protected, the drive to develop new drugs disappears). Likewise, paradigm-shift innovations need to be rewarded - otherwise genomics might be suffocated to remain "data-development R&D" that in itself may not lead to clinical applications, see Thomas Kuhn's classic book "The Structure of Scientific Revolutions" - Pellionisz]

FractoGene Emerges in a Global, Scalable Business Model, with Protected IP and an Avalanche of Independent Experimental Proof of Concept Results

[Cover page, for full Abstract and References of the avalanche of Proof of Concept results, click here]

Fractal Defects in the genome, repeat structural variants with their largest example of Copy Number Variations
clog the functional transparency of the Hilbert-fractal of DNA. Clinical applications 'focus like a laser-beam' on
diagnosis by geometric analysis, exact measurement of the efficacy of therapies, as well as drug-targetable neutralization
of Fractal Defects

FractoGene Patent Licensed to Seven in Southern California in its First Week

FractoGene Patent 8,280,641 was licensed to seven in Southern California in its first week after issue. Dr. Pellionisz, with his cross-domain expertise of Ph.D-s. in computer engineering, biology and physics is committed to the success of efforts. As expressed in the Press Release (below), there is also a great interest from BRIC countries to obtain precious access to USA markets in genome informatics (see e.g. news of the Chinese BGI offer to acquire Complete Genomics in the middle of California Silicon Valley at depressed prices of $117 M after it sustained a $500 M loss in valuation; the BGI transaction is presently litigated). For FractoGene Patent 8,280,641 an expert in international licencing is wanted. The preferred candidate represents an entity proven in the type of opportunity ("jobs").

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US Patent Office Issues FractoGene Patent to HolGenTech Founder Pellionisz

After PRWeb - October 2nd, 2012

HolGenTech Inc., a pioneer in genome analytics, announces that the USPTO issued patent No. 8,280,641 for a “Utility of Genomic Fractals Resulting in Fractals of Organisms” to founder Dr. Andras Pellionisz.


US Patent Office Issues FractoGene Patent

Recognizes breakthrough research; validates business model

This method and system is critical to the application of industrial genomics in clinical settings, most especially in the fight against cancer. The computation of genomic fractal defects can parse individual diversity from pathology, and thus represents a quantum leap in early diagnosis, personal therapy, and genome-based drug development.

click to enlarge

Pursuant to decades of research in applying mathematics to neuroscience and genomics, Pellionisz, who has three doctoral degrees, submitted his provisional application on August 1st, 2002. Recognition by the US government may well have been delayed due to its cross-disciplinary nature. The greatest hurdle was most likely the required paradigm shift - moving from the “Junk DNA” model to a fractal iterative recursion paradigm, which was initially perceived by many as a “lucid heresy.”

The status quo began to give way a few years ago, beginning with the results from the ENCODE Project, when in 2007 its leader Francis Collins urged the scientific community to “re-think long held fundamentals.” Such progress was made in Pellionisz’s presentation at George Church’s meeting in Cold Spring Harbor, Sept. 16, 2009. Another landmark was the publication by Eric Lander et al. in the Oct. 9, 2009 of Science, featuring the Hilbert-fractal of a genome on the cover.

“A protracted period of examination was costly and occasionally painful, but the issue could not be better timed for deployment,” said Pellionisz. He was delighted that legal recognition arrived via an “Issue Notification,” dated September 12, 2012. It was a heady time. The notice came less than a week after the release of 30+ papers from ENCODE on September 6th, 2012 - again concluding that “Junk DNA” was a myth.

Progress accelerated in 2008, when Pellionisz disseminated his new approach in a peer-reviewed publication on “The Principle of Recursive Genome Function.” He was also the guest speaker that year for a Google Tech Talk entitled “Is IT Ready for the Dreaded DNA Data Deluge?

As the old school of thought has finally come to an end, a new program based on recursive fractal iteration can proceed at full steam.

Pellionisz was also decorated in Hyderabad, India on the anniversary of the first decade of the “eureka moment of FractoGene” on February 15, 2012. There he announced the first independent experimental proof of concept, showing that fractal defects are implicated in cancer. He also accurately predicted that within six months about half a dozen further confirmations were likely to appear.

Dr. Andras Pellionisz’s openness to involving the subcontinent in a global transformation of genome informatics for his fair share lends a remarkable opportunity to India,” stated Prof. Erithrean Rajan, Director of the Pentagram Institute, who invited Pellionisz to a Three-State Guest of Honor Keynote Speech and lecture tour. Prof. Rajan writes:

"The Big Picture that Pellionisz is promoting for India lends a special opportunity for Bharat to catch up to China, where the Beijing Genome Institute (BGI) in Shanzhen pursues genomic syndromes in a strategic relationship with Merck Beijing, with sequencing, analytics and clinical trials pursued abroad by the USA to optimize economic feasibility by outsourcing."

Prof. Rajan’s comments are timely, given that BGI tendered an offer to acquire Complete Genomics at a depressed price once it sustained a $520 million loss of valuation due to the predicted “Dreaded DNA Data Deluge.” Pharma expert Dr. Karoly Nikolich quoted Ernst & Young in their 2009 Churchill Club YouTube video [at 1:04:30], “With time a Microsoft or Google type IT will acquire - or build - an IT-led pharma.”

The algorithmic approach to fractal recursive genome function appears to be perfectly timed, given the recently announced $3 billion “moon shot” cancer program of M.D. Anderson. Underscoring the vital importance of his invention, Pellionisz points to the hundreds of millions of people gravely suffering from genome regulation syndromes amidst global economic hardship.

Pellionisz is delighted to be among those who have lived to witness their scientific paradigm-shift come to pass and bear fruit in practical applications.

Dr. Pellionisz can be reached at holgentech [at]

[This announcement can be commented on the FaceBook of Andras Pellionisz and @holgentech on Twitter]

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(Sep 06-15) ENCODE Gets out from a 40-Year Dead-End; up to a New Era of Global Industrial Genomics

On September 6, 2012 the "official" Nature lead-article (along with 30-40 academic papers and ~500 general media-outlets) marked Ohno's "Junk DNA" (for 98.7% of the human DNA there "for the importance of doing nothing" see verbatim quote from the facsimile) not only a closed chapter, but virtually the entire R&D Establishment (80 Institutes and Companies with about 350 leading authors) finally arrived at the same conclusion as the ENCODE architect over 5 years ago: "the scientific community will need to rethink some long-held views" (Francis Collins on June 13, 2007).

Possible reasons for revisiting with so much PR a 5 year old conclusion?

Plenty. The simplest may be that in spite of the strong voice of conclusion by Francis Collins, for five years many were hoping against hope that perhaps the 35 year young "Junk DNA" misnomer was not quite dead yet (dying from a thousand wounds, RIP at 40). For instance, the leader of "ENCODE post-mortem era" Ewan Birney lost "a case of vintage champagne" with his 2007 bet with John Mattick - well masked by 30+ top papers. In a much starker legal sense, the long list of hundreds of researchers can be seen as an indemnification, rendering harmless the part of community that in a class action could be found negligent, overlooking 98.7% of human DNA in some long list of diseases; see Lee Silver's "Annus Mirabilis" article omitted from Newsweek, perhaps for the same reason, from the USA/Canada edition (the facsimile is from the European Edition), though it went to print in the other 3 editions.

In a scientific sense, Francis Collins' call "to re-think" was immediately answered by Pellionisz' "The Principle of Recursive Genome Function" (widely disseminated in his Google Tech Talk YouTube, both in 2008), since those who never believed either the "Junk DNA" or "Central Dogma" mistaken "axioms" did not have to "re-think" PLUS have been ready for years with the replacement-paradigm (see FractoGene since 2002).

In the sense of many $Bn losses, major sequencing companies lost the lion-share of their valuation due to the predicted "Dreaded DNA Data Deluge" - investors & industries perhaps should have listened (in addition to the 15,000+ viewers who viewed, but perhaps with some disbelief).

Much more sobering may be that the global balance of the emerging Industrial Genomics may have changed as a result of 4-5 years of delays & mis-steps. R&D in Europe (symbolized by Ewan Birney) and in the US (symbolized by the looming 10%+ cut of the budget of Francis Collins' NIH) appear to stumble, while (symbolized by BGI bid to acquire Complete Genomics for a mere $117 M, a loss of about half a billion dollars) China may catapult based on Genomics Industrialized, perhaps upsetting even the Asian balance (unless India, Korea or Japan launches a competitive initiative).

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What Went Wrong and When? Was the Misfiring of a Mega-Billion Dollar Business Inevitable?

Forbes Analyst: The Better Desktop DNA Sequencer May Be Losing The Marketing War

[Matthew Herper, Expert Analyst of the Forbes staff puts his light touches on a delicate subject, picturing what an anonymous commenter bluntly terms as "the market is ... going to crash down" from the angle of a "marketing war". True that the two (not pure-play) sequencer companies of Illumina versus Life Technologies. Fig. 1 (Estimated quarterly units shipped) could, indeed, be seen as some "marketing war" (with one firm with more muscle and shoe leather slightly outdoing the other) - but the numbers (columns, rather) reveal a more serious condition of the (predictable and predicted) unsustainability of mega-billion dollar sequencing business. While in just one quarter one firm outdid the other (with marketing hype reminescent of Happy Meal commercials...) the columns show that both companies actually sell less units than a mere few quarters ago - though full-range companies that do not focus on "pure play sequencing" can afford to mask the crisis better than "pure-play" Pacific Biosciences (trading today at $1.85) or Complete Genomics (today at $2.51) - while 18 months ago both were above $15 per share. - AJP]

Anonymous commenter [paints a starker picture than some "marketing war"]:

elmatos 1 day ago

First of all, complete genomics is totally out of the picture,almost everyone has left the raft… they just constantly have to lower their price against the likes of BGI who feed massive sums in ILMN. Sorry but the market is only going to crash down.

Second, Jim Creamer, ILMN does not own 15% of Oxford, it has taken equity in the company and has absolutely NO IP on nanopore sequencing. ONT will burn also.

Pac Bio, we don’t even care about, no plan B, will just burn the fuel (one system sold in the last quarter, enough said).

Now about PGM numbers, no one here, sadly because you are stock price mongrels have even looked at revenue volume per install. It’s pretty simple in that case, ILMN just totally destroys Life tech in NGS, why, because PGM has been sold as a toy, often bundled with other needless toys for large labs. PGMs arrive in boxes, stay in boxes for months, then finally they need to start using it, screw up their library prep, get tired and service out. That’s the PGM reality, same crappy old chemistry as 454. ILMN on the hand, because of the front is very easy to utilise, in a prognostic setting, there is no comparison. And yes, people turn on their miseqs as soon as they get them and run them 24-7, sending thousands of POs on material with really high margins…

Also, Life tech did not choose to de-emphasize sales of their SOLID, they had just singned a massive agreement with Hitachi, to which they promised a certain build volume. That went crashing down badly, why ? Because SOLID was an utter piece of crap, a unit that never even made profit. To this day, the same can be said of IT. And while Life is completely defocusing all volume related business such as PCR QPCR and cell sciences, they are also focusing on making less money.

You see, this market is in an endless fight to reduce cost and increase volume, it’s a scientists dream to have the fastest corvette, very typical of the community who still fails to see the big picture: The excessive data dump is worthless

And while these companies constantly ramp up, to bring the cost down they can only see one fine silverlining on the horizon: Less money at every new versions. Why ? Because the market is not interested, the billion dollar market becomes the million dollar market, the floors are saturated with these boxes and the next new ones cost even less.

During this time, weather you want to believe it or not, NGS is simply not gaining acceptance in clinical diagnostic, it’s pretty simple and if you think that the T21 test will help the market, you have no clue. The reality is that the true applied markets for these machines is eons away, there are still many generations to go and in the meantime you can look at all these companies go at each other, with the resulting discount battles and placement…

The car is too fast and the highway is completely jammed. And next time you hear a NGS lab rat tell you that NGS is used in hospitals, go to a pathology unit, even a molecular one and ask them: “How much routine work are you doing here ” and listen closely at the “ we are setting up, we want to be ready, we are doing a pilote… gibberish”.

People don’t give a crap about their genome, they want a quick fix and right now small mutation panels are just not NGS ready nor will they be and companies like ONT better have a much pricier machine to sell if they want to survive… The fact is, a single instrument company simply does not thrive in life sciences anymore…

And yes, ILMN would have done well if Roche had planned to invest properly in them, why ? Because Roche has the diag and pharma might no one else has… Shares back in the 30s when this nightmare is over. And if you talk to anyone in the NGS world, you will know it is not thriving, reps fired, downsizing, increased quota, increased territory. I know a lot of people losing sleep over this balloon.

[Since I published "The Principle of Recursive Genome Function" in 2008 (manuscript submitted for peer review a few months after ENCODE concluded earlier than planned, in part due to the World Conference of PostGenetics Society in October, 2006 officially abandoning obsolete axioms of Central Dogma and Junk DNA), moreover I widely publicized the messages in Google Tech Talk YouTube "Is IT Ready for the Dreaded DNA Data Deluge", it would be easy to dismiss any "I told you so". Were it not the case that not only the danger costing us billions of dollars - and even more precious years - was predicted (and now a starking reality) - but the actual science agenda was also laid out. No, scientists are not to be blamed (actually, some key leaders listened carefully) but Industrialization of Genomics were considered, and is still considered, as a "pure technology-run", building on its own momentum. Not unlike "the fastest Corvette" cited by the anonymous commenter, as if Detroit would build cars regardless of the availability of roads, gas-stations - or exert extra marketing effort when exports to Japan dipped - instead of putting the steering wheel to the side the Japanese actually use. Remember the Manhattan Project. Nuclear technology would have been not only a failure, but a very dangerous one, if the scientific-technological advancement weren't guided by the World's best scientific minds; first of all creating Quantum Mechanics in a truly global effort. Likewise, in 2012, a Decade after FractoGene-Discovery one respectfully disagrees with the anonymous commenter that clinical applications are "eons away". The road is already laid out (see Springer Textbook, 2012 and Proceedings of the Hyderabad Conference, 2012 in submission) - Pellionisz, comments at Facebook "Andras Pellionisz, or Twitter "@Holgentech"]

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A Quest for Clarity [or Understanding?]

Genomeweb, July/August, 2012

by Tracy Vence

Projects supported by the US National Institutes of Health will have produced 68,000 total human genomes — around 18,000 of those whole human genomes — through the end of this year, National Human Genome Research Institute estimates indicate. And in his book, The Creative Destruction of Medicine, the Scripps Research Institute's Eric Topol projects that 1 million human genomes will have been sequenced by 2013 and 5 million by 2014.

"There's a lot of inventory out there, and these things are being generated at a fiendish rate," says Daniel MacArthur, a group leader in Massachusetts General Hospital's Analytic and Translational Genetics Unit. "From a capacity perspective ... millions of genomes are not that far off. If you look at the rate that we're scaling, we can certainly achieve that."

The prospect of so many genomes has brought clinical interpretation into focus — and for good reason. Save for regulatory hurdles, it seems to be the single greatest barrier to the broad implementation of genomic medicine. [As belabored in the 2008 Google Tech Talk YouTube, the single greatest barrier to implementation of genomic medicine is NOT the "Dreaded DNA Data Deluge" - now a predicted reality of an industry show-stopper "glut" - but the lack of Information Theory. If your computer is ailing, the question to the repairman is NOT "how many hundreds of malfunctioning computers are around?" - but the crucial question if the repairman knows what he/she is doing; understands the functioning or just pretends to?]

But there is an important distinction to be made between the interpretation of an apparently healthy person's genome and that of an individual who is already affected by a disease, whether known or unknown.

In an April Science Translational Medicine paper, Johns Hopkins University School of Medicine's Nicholas Roberts and his colleagues reported that personal genome sequences for healthy monozygotic twin pairs are not predictive of significant risk for 24 different diseases in those individuals. The researchers then concluded that whole-genome sequencing was not likely to be clinically useful for that purpose. (See sidebar, story end.) [The Genome is only one part of the Genome/Epigenome ying-yang; the HoloGenome. If one monozygotic twin has worked a lifetime in an asbestos mine and the other did not, it is not their genome that will determine which one will get lung cancer]

"The Roberts paper was really about the value of omniscient interpretation of whole-genome sequences in asymptomatic individuals and what were the likely theoretical limits," says Isaac Kohane, chair of the informatics program at Children's Hospital Boston. "That was certainly an important study, and it was important to establish what those limits of knowledge are in asymptomatic populations. But, in fact, the major and most important use cases [for whole-genome sequencing] may be in cases of disease."

Still, targeted clinical interpretations are not cut and dried. "Even in cases of disease, it's not clear that we know now how to look across multiple genes and figure out which are relevant, which are not," Kohane adds. [In an orchestra which musical instrument is "relevant" and which one isn't ?  In Bartok, percussion instruments are more relevant compared to Wagner's horns]

While substantial progress has been made — in particular, for genetic diseases, including certain cancers — ambiguities have clouded even the most targeted interpretation efforts to date. Technological challenges, meager sample sizes, and a need for increased, fail-safe automation all have hampered researchers' attempts to reliably interpret the clinical significance of genomic variation. But perhaps the greatest problem, experts say, is a lack of community-wide standards for the task.

Genes to genomes

When scientists analyzed James Watson's genome — his was the first personal sequence, completed in 2007 and published in Nature in 2008 — they were surprised to find that he harbored two putative homozygous SNPs matching Human Gene Mutation Database entries that, were they truly homozygous, would have produced severe clinical pheno-types.

But Watson was not sick.

As researchers search more and more genomes, such inconsistencies are increasingly common.

"My take on what has happened is that the people who were doing the interpretation of the raw sequence largely were coming from a SNPs world, where they were thinking about sequence variants that have been observed before, or that have an appreciable frequency, and weren't thinking very much about the single-ton sequence variants," says Sean Tavtigian, associate professor of oncology at the University of Utah.

"There is a qualitative difference between looking at whole-genome sequences and looking at single genes or, even more typically, small numbers of variants that have been previously implicated in a disease," Boston's Kohane adds.

"Previously, because of the cost and time limitations around sequencing and genotyping, we only looked at variants in genes for which we had a clinical indication. Now, since we can essentially see that in the near future we will be able to do a full genome sequence for essentially the same cost as just a focused set-of-variants test, all of the sudden we have to ask ourselves: What is the meaning of variants that fall outside where we would have ordinarily looked for a given disease or, in fact, if there is no disease at all?"

Mass General's MacArthur says it has been difficult to pinpoint causal variants because they are enriched for both sequencing and annotation errors. "In the genome era, we can generate those false positives at an amazing rate, and we need to work hard to filter them back out," he says.

"Clinical geneticists have been working on rare diseases for a long time, and have identified many genes, and are used to working in a world where there is sequence data available only from, say, one gene with a strong biological hypothesis. Suddenly, they're in this world where they have data from patients on all 20,000 genes," MacArthur adds. "There's a fundamental mind-shift there, in shifting from one gene through to every gene. My impression is that the community as a whole hasn't really internalized that shift; people still have a sense in their head that if you see a strongly damaging variant that segregates with the disease, and maybe there's some sort of biological plausibility around it as well, that that's probably the causal variant." [Amen]

It's no crystal ball, but whole-genome sequencing has shown to be clinically useful, particularly for patients with genetic diseases. Still, scientists working toward targeted clinical interpretation of human genomes face several challenges, not the least of which is a lack of community standards.

Studies have shown that that's not necessarily so. Because of this, "I do worry that in the next year or so we'll see increasing numbers of mutations published that later prove to just be benign polymorphisms," MacArthur adds.

"The meaning of whole-genome -sequence I think is very much front-and-center of where genomics is going to go. What is the true, clinical meaning? What is the interpretation? And, there's really a double-edged sword," Kohane says. On one hand, "if you only focus on the genes that you believe are relevant to the condition you're studying, then you might miss some important findings," he says. Conversely, "if you look at every-thing, the likelihood of a false positive becomes very, very high. Because, if you look at enough things, invariably you will find something abnormal," he adds.

False positives are but one of the several challenges scientists working to analyze genomes in a clinical context face.

Technical difficulties

That advances in sequencing technologies are far outstripping researchers' abilities to analyze the data they produce has become a truism of the field. [Truism, yes, funding no]. But current sequencing platforms are still far from perfect, making most analyses complicated and nuanced. Among other things, improvements in both read length and quality are needed to enable accurate and reproducible interpretations.

"The most promising thing is the rate at which the cost-per-base-pair of massively parallel sequencing has dropped," Utah's Tavtigian says. Still, the cost of clinical sequencing is not inconsequential. "The $1,000, $2,000, $3,000 whole-genome sequences that you can do right now do not come anywhere close to 99 percent probability to identify a singleton sequence variant, especially a biologically severe singleton sequence variant," he says. "Right now, the real price of just the laboratory sequencing to reach that quality is at least $5,000, if not $10,000."

However, Tavtigian adds, "techniques for multiplexing many samples into a channel for sequencing have come along. They're not perfect yet, but they're going to improve over the next year or so."

Using next-generation sequencing platforms, researchers have uncovered a variety of SNPs, copy-number variants, and small indels. But to MacArthur's mind, current read lengths are not up to par when it comes to clinical-grade sequencing, and they have made supernumerary quality-control measures necessary.

"There's no question that we're already seeing huge improvements. ... And as we add in to that changes in technology — for instance much, much longer sequencing reads, more accurate reads, possibly combining different platforms — I think these sorts of [quality-control] issues will begin to go away over the next couple of years," MacArthur says. "But at this stage, there is still a substantial quality-control component in any sort of interpretation process. We don't have perfect genomes."

In a 2011 Nature Biotechnology paper, Stanford University's Michael Snyder and his colleagues sought to examine the accuracy and completeness of single-nucleotide variant and indel calls from both the Illumina and Complete Genomics platforms by sequencing the genome of one individual using both technologies. Though the researchers found that more than 88 percent of the unique single-nucleotide variants they detected were concordant between the two platforms, only around one-quarter of the indel calls they generated matched up. Overall, the authors reported having found tens of thousands of platform-specific variant calls, around 60 percent of which they later validated by genotyping array.

For clinical sequencing to ever become widespread, "we're going to have to be able to show the same reproducibility and test characteristic modification as we have for, let's say, an LDL cholesterol level," Boston's Kohane says. "And if you measure it in one place, it should not be too different from another place. ... Even before we can get to the clinical meaning of the genomes, we're going to have to get some industry-wide standards around quality of sequencing."

Scripps' Topol adds that when it comes to detecting rare variants, "there still needs to be a big upgrade in accuracy."

Analytical issues

Beyond sequencing, technological advances must also be made on the analysis end. "The next thing, of course, is once you have better -accuracy ... being able to do all of the analytical work," Topol says. "We're getting better at the exome, but every-thing outside of protein-coding -elements, there's still a tremendous challenge."

Indeed, that challenge has inspired another — a friendly competition among bioinformaticians working to analyze pediatric genomes in a pedigree study.

With enrollment closed and all sequencing completed, participants in the Children's Hospital Boston-sponsored CLARITY Challenge have rolled up their shirtsleeves and begun to dig into the data — de-identified clinical summaries and exome or whole-genome sequences generated by Complete Genomics and Life Technologies for three children affected by rare diseases of unknown genetic basis, and their parents. According to its organizers, the competition aims to help set standards for genomic analysis and interpretation in a clinical setting, and for returning actionable results to clinicians and patients.

"A bunch of teams have signed up to provide clinical-grade reports that will be checked by a blue-ribbon panel of judges later this year to compare and contrast the different forms of clinical reporting at the genome-wide level," Kohane says. The winning team will be announced this fall and will receive a $25,000 prize, he adds.

While the competition covers all aspects of clinical sequencing — from readout to reporting — it is important to recognize that, more generally, there may not be one right answer and that the challenges are far-reaching, affecting even the most basic aspects of analysis.

"There is a lot of algorithm investment still to be made in order to get very good at identifying the very rare or singleton sequence variants from the massively parallel sequencing reads efficiently, accurately, [and with] sensitivity," Utah's Tavtigian says.

Picking up a variant that has been seen before is one thing, but detecting a potentially causal, though as-yet-unclassified variant is a beast of another nature.

"Novel mutations usually need extensive knowledge but also validation. That's one of the challenges," says Zhongming Zhao, associate professor of biomedical informatics at Vanderbilt University. "Validation in terms of a disease study is most challenging right now, because it is very time-consuming, and usually you need to find a good number of samples with similar disease to show this is not by chance."

Search for significance

Much like sequencing a human genome in the early- to mid-2000s was more laborious than it is now, genome interpretation has also become increasingly automated.

Beyond standard quality-control checks, the process of moving from raw data to calling variants is now semiautomatic. "There's essentially no manual intervention required there, apart from running our eyes over [the calls], making sure nothing has gone horribly wrong," says Mass General's MacArthur. "The step that requires manual intervention now is all about taking that list of variants that comes out of that and looking at all the available biological data that exists on the Web, [coming] up with a short-list of genes, and then all of us basically have a look at all sorts of online resources to see if any of them have some kind of intuitive biological profile that fits with the disease we're thinking about."

Of course, intuitive leads are not foolproof, nor are current mutation data-bases. (See sidebar, story end.) And so, MacArthur says, "we need to start replacing the sort of intuitive biological approach with a much more data-informed approach."

Developing such an approach hinges in part on having more genomes. "If we get thousands — tens of thousands — of people sequenced with various different phenotypes that have been crisply identified, that's going to be so important because it's the coupling of the processing of the data with having rare variants, structural variants, all the other genomic variations to understand the relationship of whole-genome sequence of any particular phenotype and a sequence variant," Scripps' Topol says.

Vanderbilt's Zhao says that sample size is still an issue. "Right now, the number of samples in each whole-genome sequencing-based publication is still very limited," he says. At the same time, he adds, "when I read peers' grant applications, they are proposing more and more whole-genome sequencing."

When it comes to disease studies, sequencing a whole swath of apparently healthy people is not likely to ever be worthwhile. According to Utah's Tavtigian, "the place where it is cost-effective is when you test cases and then, if something is found in the case, go on and test all of the first-degree relatives of the case — reflex testing for the first-degree relatives," he says. "If there is something that's pathogenic for heart disease or colon cancer or whatever is found in an index case, then there is a roughly 50 percent chance that the first-degree relatives are going to carry the same thing, whereas if you go and apply that same test to someone in the general population, the probability that they carry something of interest is a lot lower."

But more genomes, even familial ones, are not the only missing elements. To fill in the functional blanks, researchers require multiple data types.

"We've been pretty much sequence-centric in our thinking for many years now because that was where are the attention [was]," Topol says. "But that leaves the other 'omes out there." [Amen]

From the transcriptome to the proteome, the metabolome, the microbiome, and beyond — Topol says that because all the 'omes contribute to human health, they all merit review.

"The ability to integrate information about the other 'omics will probably be a critical direction to understand [here is the word; if the Genome is Life's Code, it must be mathematically understood] the underpinnings of disease," he says. "I call it the 'panoromic' view — that is really going to become a critical future direction once we can do those other 'omics readily. We're quite a ways off from that right now." [Recursive Genome Function, tracking fractal iterations that can be derailed by fractal defects, does HoloGenomics already - the business of HolGenTech]

Mass General's MacArthur envisages "rolling in data from protein-protein interaction networks and tissue expression data — pulling all of these together into a model that predicts, given the phenotype, given the systems that appear to be disrupted by this variant, what are the most likely set of genes to be involved," he says. From there, whittling that set down to putative causal variants would be simpler.

"And at the end of that, I think we'll end up with a relatively small number of variants, each of which has a probability score associated with it, along with a whole host of additional information that a clinician can just drill down into in an intuitive way in making a diagnosis in that individual," he adds.

According to MacArthur, "we're already moving in this direction — in five years I think we will have made substantial progress toward that." He adds, "I certainly think within five years we will be diagnosing the majority of severe genetic disease patients; the vast majority of those we'll be able to assign a likely causal variant using this type of approach."

Tavtigian, however, highlights a potential pitfall. While he says that "integration of those [multivariate] data helps a lot with assessing unclassified variants," it is not enough to help clinicians ascertain causality. Functional assays, which can be both inconclusive and costly, will be needed for some unclassified variant hits, particularly those that are thought to be clinically meaningful.

"I don't see how you're going to do a functional assay for less than like $1,000," he says. "That means that unless the cost of the sequencing test also includes a whole bunch of money for assessing the unclassified variants, a sequencing test is going to create more of a mess than it cleans up."

Rare, common

Despite the challenges, there have been plenty of clinical sequencing success stories. Already, Scripps' Topol says there have been "two big fronts in 2012: One is the unknown diseases [and] the other one, of course, is cancer." But scientists say that despite the challenges, whole--genome sequencing might also become clinically useful for asymptomatic individuals in the future.

Down the line, scientists have their sights set on sequencing asymptomatic individuals to predict disease risk. "The long-term goal is to have any person walk off the street, be able to take a look at their genome and, without even looking at them clinically, say: 'This is a person who will almost certainly have phenotype X,'" MacArthur says. "That is a long way away. And, of course, there are many phenotypes that can't be predicted from genetic data alone."

Nearer term, Boston's Kohane imagines that newborns might have their genomes screened for a number of neonatal or pediatric conditions.

Overall, he says, it's tough to say exactly where all of the chips might fall. "It's going to be an interesting few years where the sequencing companies will be aligning themselves with laboratory testing companies and with genome interpretation companies," Kohane says. [This is a key, and presently BGI/Merck is the scalable global business model to follow. In China, outside of US regulatory jurisdiction, the World's largest sequencing power is already integrated with an IT arm of 5,000 software developers (average age is 27) - and strategic partner Merck Beijing can do clinical trials outsourced. HolGenTech leverages a model to catch up with the leading example of China with another BRICs country; India]

Even if clinical sequencing does not show utility for cases other than genetic diseases, it could still become common practice.

"Worldwide, there are certainly millions of people with severe diseases that would benefit from whole--genome sequencing, so the demand is certainly there," MacArthur says. "It's just a question of whether we can develop the infrastructure that is required to turn the research-grade genomes that we're generating at the moment into clinical-grade genomes. Given the demand and the practical benefit of having this information ... I don't think there is any question that we will continue to drive, pretty aggressively, towards large-scale -genome sequencing."

Kohane adds that "although rare diseases are rare, in aggregate they're actually not — 5 percent of the population, or 1 in 20, is beginning to look common."

Despite conflicting reports as to its clinical value, given the rapid declines in cost, Kohane says it's possible that a whole-genome sequence could be less expensive than a CT scan in the next five years. Confident that many of the interpretation issues will be worked out by then, he adds, "this soon-to-be-very-inexpensive test will actually have a lot of clinical value in a variety of situations. I think it will become part the decision procedure of most doctors."

[Sidebar] 'Predictive Capacity' Challenged

In Science Translational Medicine in April, Johns Hopkins University School of Medicine's Nicholas Roberts and his colleagues showed that personal genome sequences for healthy monozygotic twin pairs are not predictive of significant risk for 24 different diseases in those individuals and concluded that whole-genome sequencing was unlikely to be useful for that purpose.

As the Scripps Research Institute's Eric Topol says, that Roberts and his colleagues examined the predictive capacity of personal genome sequencing "without any genome sequences" was but one flaw of their interpretation.

In a comment appearing in the same journal in May, Topol elaborated on this criticism, and noted that the Roberts et al. study essentially showed nothing new. "We cannot know the predictive capacity of whole-genome sequencing until we have sequenced a large number of individuals with like conditions," Topol wrote.

Elsewhere in the journal, Tel Aviv University's David Golan and Saharon Rosset noted that slightly tweaking the gene-environment parameters of the mathematical model used by Roberts et al. showed that the "predictive capacity of genomes may be higher than their maximal estimates."

Colin Begg and Malcolm Pike from Memorial Sloan-Kettering Cancer Center also commented on the study in Science Translational Medicine, reporting their -alternative calculation of the predictive capacity of personal sequencing and their analysis of cancer occurrence in the second breast of breast cancer patients, both of which, they wrote, "offer a more optimistic view of the predictive value of genetic data."

In response to those comments, Bert Vogelstein — who co-authored the Roberts et al. study — and his colleagues wrote in Science Translational Medicine that their "group was the first to show that unbiased genome-wide sequencing could illuminate the basis for a hereditary disease," adding that they are "acutely aware of its immense power to elucidate disease pathogenesis." However, Vogelstein and his colleagues also said that recognizing the potential limitations of personal genome sequencing is important to "minimize false expectations and foster the most fruitful investigations."

[Sidebar] 'The Single Biggest Problem'

That there is currently no comprehensive, accurate, and openly accessible database of human disease-causing mutations "is the single greatest failure of modern human genetics," Massachusetts General Hospital's Daniel MacArthur says.

"We've invested so much effort and so much money in researching these Mendelian diseases, and yet we have never managed as a community to centralize all of those mutations in a single resource that's actually useful," MacArthur says. While he notes that several groups have produced enormously helpful resources and that others are developing more, currently "none covers anywhere close to the whole of the literature with the degree of detail that is required to make an accurate interpretation."

Because of this, he adds, researchers are pouring time and resources into rehashing one another's efforts and chasing down false leads.

"As anyone at the moment who is sequencing genomes can tell you, when you look at a person's genome and you compare it to any of these databases, you find things that just shouldn't be there — homozygous mutations that are predicted to be severe, recessive, disease-causing variants and dominant mutations all over the place, maybe a dozen or more, that they've seen in every genome," MacArthur says. "Those things are clearly not what they claim to be, in the sense that a person isn't sick." Most often, he adds, the researchers who reported that variant as disease-causing were mistaken. Less commonly, the database moderators are at fault.

"The single biggest problem is that the literature contains a lot of noise. There are things that have been reported to be mutations that just aren't. And, of course, a lot of the databases are missing a lot of mutations as well," MacArthur adds. "Until we have a complete database of severe disease mutations that we can trust, genome interpretation will always be far more complicated than it should be."

[Consider a library of Russian books that is littered with lots of trashy books from the Soviet Union. Is the main problem if the library is not open to everyone? Do we need, perhaps, a ten- or thosand times bigger library?? Should we spend uncounted tax-dollars to weed out Soviet propaganda-books???  All the above might make sense - once that the far the most important requirement will have been satisfied: "The Reader Understands the Russian Language". As for the HoloGenome, focuses in a single-minded manner on the absolutely crucial breakthrough: the mathematical understanding of Fractal Recursive Genome Function; healthy regulation and cancerous misregulation; immediately translated into clinical applications. We have some summer weeks to think about the challenge and best solutions; see Facebook page of Andras Pellionisz and Twitter: @Holgentech]

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Summer Solstice in Industrialization of Genomics - Celestial Recursion

As documented below, in the past 6 months 4 top papers (3 Nature, 1 PNAS, a combined 137 authors, Worldwide) published independent experimental Proof of Concept, all cited on (“News”) that fractal defects, particularly CNV-s, are implicated in cancer. Accordintly, attention is catapulting astronomically.

Maybe the Summer Solstice on the Northern Hemisphere prompted the following answer yesterday, apparently from Australia, to the YouTube Comment “Is IT Ready for the Dreaded DNA Data Deluge?

The Comment (earlier) was: “This presentation is eye-opening for those who no longer wish to hide their heads in the sand. The aim of his talk is not to intimidate, but to enlighten and instill hope. Pellionisz single-handedly drags the audience into the future where the merger of genomics and IT will save and improve lives. The revolutionary ideas he presents are often attacked by cynics, but as Albert Einstein once said: "Great spirits have always encountered violent opposition from mediocre minds"

The Anwser yesterday reads: “So true: ‘Great spirits have always encountered violent opposition from mediocre minds’. Look how Galileo was treated by the Roman Inquisition or the Catholic Church's response when Copernicus tried to show us that the Earth moved in an orbit around the sun.”

The Answer is sensible enough to leave unmentioned the burning image of Giordano Bruno, though he had to pay an even heavier price for the paradigm-shift than Galileo Galilei or Nicolaus Copernicus. It is telling that 400 years after the execution of Giordano Bruno was apparently not enough to rectify a serious error in judgement against him by the establishment, though nobody (else) died because of the fact that the Earth moved in an elliptical orbit around the Sun (and not vice-versa).

Also unmentioned is a more contemporary and thus much milder case, when it took “only” 40 years to rectify ridiculing Dr. Barbara McClintock as a “Kook” for her paradigm-shift. The tenfold acceleration in the speed of backpedaling on an oversight occurred perhaps because hundreds of millions died every year caused by the disregard/ridicule of genomic paradigm-shifts.

Additional tenfold acceleration is happily observed that in less than 4 years ample independent experimental Proof of Concept was published for the fractal approach in the interpretation of Recursive Genome Function (published in peer reviewed publication and generally disseminated in 2008, with unification of Neuroscience and Genomics in 2012). “Recursive Genome Function”, “of course”, yields today several orders of magnitude less “secret” Google hits and – reverse IP weblog-monitored downloads – compared to its scholarly citations. (Still, can not complain; Watson & Crick paper was not cited by anyone in the first seven years… and the Unification has been amply cited though at the moment it is still In Press with Springer).

How many billions must die before Industrialization of Genomics realize that the bottleneck is not the supply-side of “sequencing” (even if it is spectacularly affordable but too low in demand to sustain “sequencing only”)? Algorithmic, thus software enabling understanding of Genome Function, most particularly of Genome Regulation, e.g. the current wave of identification of Fractal Defects derailing Fractal Recursive Iteration, is the bottleneck to be neatly uncorked for Genome Analytics and thus resulting in a sustainable Industrialization of Genomics.

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The Lost Decade; Too Many Genomic Melt-downs (We Could Do Better)

By far the most painful "genome-meltdown" has been experienced by the uncounted hundreds of millions of cancer victims. Massive re-arrangement of DNA with structural variants as long as hundreds of thousands of A,C,T,G bases ("Copy Number Alterations, CNA-s", upsetting normal "Copy Number Variations, CNV-s") are now reported (see below) in independent experimental investigations of world-leader scientists (an overlapping 137 authors from all academic corners of the Globe), within 6 months appearing in 3 leading Nature papers (Boston, Cambridge UK, Ann Arbor MI) plus a PNAS paper (NY, led by an Institute endowed by a $10 M gift from a Prince of Saudi-Ariabia, the paper edited by Eric Lander, a Science Advisor to the US President). CNA-s are implicated in cancers by CNA-s constituting some of the biggest "fractal defects" (CNV-alterations). The Hilbert-fractal of DNA folded into the cell nucleus in a knot-free manner (for glitch-free transcription), furthermore ultra-dense (for the 2m long DNA-strand to fit into a 6 micron diameter cell-nucleus) was put on the Science Cover article on Oct. 9, 2009 to the effect of "Mr. President, the Genome is Fractal!" - yet the decade-old 2002 FractoGene concept 1,see in 2 Fig. 3. , 3 (Principle of Recursive Genome Function), YouTube 2008 32:10, 4 (Cold Spring Harbor, Sept. 16, 2009), 5 (2012 Springer; Geometrical Unification of Neuroscience and Genomics, In Press) of fractal genome governing growth of fractal organisms still (now, evidently fractal defects of DNA causing visibly and obviously misregulated fractal growths, otherwise known as cancers) can not be openly referenced for IP considerations. Although Leroy Hood also in the same year declared that "Genomics became Informatics" (Kyoto Prize to Leroy Hood, 2002), only the General Systems Theory of Ludwig von Bertalanffy (1936) could be put to use, the mathematical identification of the "system" (as fractal iterative recursion) constituted a "lucid heresy" double-fold, as it "violated" the two prevailing (mistaken) axioms (of "Central Dogma" by Crick, pontificating that recursion of information from proteins to DNA "never happens", held since his misconception in 1956 till his passing away in 2004, and of "Junk DNA" by Ohno, who used his veritable credentials of genome-scientist in 1972 to daresay that "too much Junk" is in our DNA "for the importance of doing nothing" - implying [till his passing away in 2000] that even if there was a recursion, from the "junk DNA" no information would be gained). Thus - unfortunately perhaps - against advice of those seasoned in informatics the US and allied governments spent time and money from 2003-2007 on "big science" of ENCODE, to arrive at the same conclusion of ENCODE in 2007 what math of informatics dictated prior to the start of exercise; "Junk DNA is anything but". In 2012, to the day a Decade after its inception, the fractal approach was decorated to the Guest of Honor and Keynote Speaker in a lecture-tour in India; a math- and informatics-savvy science community that did not have to make an about-face, as they were never chained to fundamentally misled establishments.

Science and clinical applications (most notably, cancer) aside, an "Industrial Melt-down" also happened in Genomics, illustrated by the above collated stock-meltdown of four leading public DNA sequencing companies. Predictably (and predicted specifically by 2008 YouTube), "Industrialization of Genomics" went out on the single limb of "sequencing" (dashing for an erroneously "magic" $1,000 Human Genome Sequence), not heeding advice that the imbalance of strong supply and (without matching analytics) a weak demand for sequences will render the path towards industrialization economically untenable. As seen above, even though the two leading sequencing companies (especially since they never were "pure play full DNA sequencing firms") sustained significant loss of market-valuation of their shares, Illumina already was subjected to repeated hostile "take-over" bids by Roche, but to this they prevailed on its own (refusing an elevated $6.6 Bn take-over offer of Roche). As seen above, hardest hit are the two "pure-play sequencing firms" PacBio (PACB) and Complete Genomics (GNOM) - to the extent that on June 6th GNOM issued a SEC filing, "seeking strategic re-structuring, including the possibility of sale of the company":

Complete Genomics axes 55 staffers
Fierce Biotech IT
June 6, 2012 | By Ryan McBride

Complete Genomics ($GNOM) is slumping. The provider of whole genome sequencing and informatics support has decided to cut about 20% of its roster to conserve cash, and the company has hired a financial adviser to aid in its hunt for "strategic alternatives."

With problems in the current whole-genome sequencing market, Complete Genomics plans to boost its focus on clinical sequencing applications in anticipation of growth in demand from hospitals and healthcare providers wishing to decode the DNA of their patients. Meanwhile, the company plans to keep servicing its existing research customers in academia and biopharma. The cutbacks will claim the jobs of 55 employees at the Complete Genomics' base in Mountain View, CA, and those of field workers in the U.S., the company said on Tuesday. Most of the layoffs will take place before the end of this month, with restructuring charges expected to hit $1.5 million.

Complete Genomics hired Jeffries & Company to serve as its financial adviser, and, though no decisions have been made about specific strategic alternatives, the options on the table include a sale of the company, a merger, business combination and equity investment.

A number of factors appear to be hammering Complete Genomics, which has commercialized its proprietary sequencing platform and its informatics and software for managing genomic data in an outsourcing service model. As Cowen & Company analyst Doug Schenkel wrote in a note to investors this week, "[Complete Genomics] deserves credit for attempting to drive growth in a market that has traditionally been quite elastic, via a services model. Unfortunately, demand for whole genome sequencing has not been as robust as other sequencing applications."

Meantime, companies such as Life Technologies ($LIFE), with the Ion Torrent system, and others are developing desktop sequencers that make the technology accessible to individual labs. Plus, the cost of sequencing an individual genome has fallen faster than Moore's Law, pushing sequencing toward a commoditized service and forcing players in the game to rethink their business models.

For example, China-based BGI, the world's largest DNA sequencing provider, has put a lot of energy and investment into cloud computing and bioinformatics that improve the utility of whole genome data and help researchers analyze the huge amount of information. Complete Genomics has made similar investments in IT, for instance, enabling its customers to access their sequencing data on Amazon's cloud, Nature News reported in July.

[One of the main conclusions of Bio-IT World conference in Singapore in these days is, that China-based BGI is the current World-leader with its aggressively pursued, centralized government assisted integration of Sequencing (250 Illumina and Solid platforms, the World's most potent capacity surpassing the entire USA) with Analytics (5,000 software-developers, with the average age of 27, also putting to use the World's fastest supercomputer, surpassing by 40% the speed of fastest US supercomputer). In addition, BGI is aligned with Merck-Beijing subsidiary. This enables Merck with not only outsourced sequencing and analytics, but also affordable clinical trials not directly under FDA. For Big Pharma not only Merck and Roche are now on record to see their future based on Genomics, but e.g. Glaxo is also pursuing M/A penetrating genomics. So is the fervor from major IT companies, from the Korean SAMSUNG entering genome informatics last September to German SIEMENS, with their announcement this Spring.  The Global horse-race is on, leaving too many guesses to publicly list for the potentially most successful M/A, best suited for global and scalable business-model of Industrialization of Genomics - Comment by Andras Pellionisz]

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Chromosome structure fractal defects implicated in cancer

In about half a year we have seen three independent experimental Proof of Concept studies that fractal defects, the largest of which are Copy Number Variations, are implicated in cancer.

The first Nature study appeared by a HARVARD/MIT/BROAD/DANA-FARBER group in Boston, USA (4 authors)

The second Nature study carried the concept abroad to SANGER INSTITUTE in Cambridge, UK (63 authors, linked to 10 countries; UK, Belgium, Norway, China, Singapore, The Netherlands, Australia, Canada, USA, France)

The third Nature study was completed in USA MIDWEST, MICHIGAN, ANN ARBOR (27 authors, affiliation linked also to to India)

The above three PoC Nature papers are the easiest to understand by visualization of the rotating 3D Hilbert-curve of DNA-fractal, that is transparent in its pristine form, but Copy Number Alterations clog the transparency, thus the functional proximity of physically distant parts of the DNA, to be read in a parallel manner, is disrupted by fractal defects.


Now a fourth, PNAS study led by a NEW YORK CITY Institute, endowed by HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud of SAUDI ARABIA, also linked to the Mount Sinai Hospital and an affiliation in Italy (14 authors), the paper edited by Eric Lander (The Broad Institute) generalized the above findings to show that chromosome structure fractal defects are implicated in cancer. This study is not so easy to visualize as it pertains to the genome regulation aberrations at the DNA chromatin level (for early 2008 visualizations, see YouTube [at 30:26], cf. Fig. 6. of The Principle of Recursive Genome Function). The PNAS paper uses the analysis of functional proximities (by the properly cited experimental Hi-C method of Lieberman-Aiden et al, 2009, co-authored by Eric Lander, the paper hallmarked by the Science Magazine displaying on its cover the Hilbert-curve). It is interesting that the edited paper states in its Supplement info that "Interaction Data Support the Fractal Globule Model of Nuclear Organization".

[The above can be discussed in FaceBook page of Andras Pellionisz, and Tweeted @HolGenTech]

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In half a year, third independent experimental Proof of Concept that fractal defect of Copy Number Variation is implicated in cancer

The mutational landscape of lethal castration-resistant prostate cancer

Nature (2012) doi:10.1038/nature11125

Characterization of the prostate cancer transcriptome and genome has identified chromosomal rearrangements and copy number gains and losses, including ETS gene family fusions, PTEN loss and androgen receptor (AR) amplification, which drive prostate cancer development and progression to lethal, metastatic castration-resistant prostate cancer (CRPC)1. However, less is known about the role of mutations2, 3, 4. Here we sequenced the exomes of 50 lethal, heavily pre-treated metastatic CRPCs obtained at rapid autopsy (including three different foci from the same patient) and 11 treatment-naive, high-grade localized prostate cancers. We identified low overall mutation rates even in heavily treated CRPCs (2.00 per megabase) and confirmed the monoclonal origin of lethal CRPC. Integrating exome copy number analysis identified disruptions of CHD1 that define a subtype of ETS gene family fusion-negative prostate cancer. Similarly, we demonstrate that ETS2, which is deleted in approximately one-third of CRPCs (commonly through TMPRSS2:ERG fusions), is also deregulated through mutation. Furthermore, we identified recurrent mutations in multiple chromatin- and histone-modifying genes, including MLL2 (mutated in 8.6% of prostate cancers), and demonstrate interaction of the MLL complex with the AR, which is required for AR-mediated signalling. We also identified novel recurrent mutations in the AR collaborating factor FOXA1, which is mutated in 5 of 147 (3.4%) prostate cancers (both untreated localized prostate cancer and CRPC), and showed that mutated FOXA1 represses androgen signalling and increases tumour growth. Proteins that physically interact with the AR, such as the ERG gene fusion product, FOXA1, MLL2, UTX (also known as KDM6A) and ASXL1 were found to be mutated in CRPC. In summary, we describe the mutational landscape of a heavily treated metastatic cancer, identify novel mechanisms of AR signalling deregulated in prostate cancer, and prioritize candidates for future study.

[Copy Number Variations - the largest pieces of fractal defects - clog the transparency of the delicate fractal Hilbert-curve of DNA. In half a year, a Boston (MIT-Harvard-Broad-Dana Farber), a Cambridge UK (Sanger) and now a Michigan-group provides, what appears to be an undisputable evidence that massive fractal defects disrupt genome regulation in cancer. Now the question is no longer "if a Proof of Concept" is clinched, but only a matter of ramping up the fractal interpretation of the analysis of derailed genome regulation - Pellionisz]

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A Decade after Genomics was Declared to be Informatics; Vistas by Andras Pellionisz (Part II)

An Avalanche of Independent Experimental Proofs of Concept that Intact or Defective Fractal Genome Governs Physiological or Pathological Growth of Organs, Organelles and Organisms; FractoGene (2002)

Pellionisz’ “FractoGene” approach receives massive independent experimental “Proof of Concept”, published in top peer-reviewed journals (25-29, 31 in 2011 and 2012). POC-s stream within a single decade since inception and in spite of a need to shred both prevailing mistaken axioms of genomics defended with (ad hominem) “tools and nails” by ossified detractors of the old establishment.

While upon arrival of the first full human DNA (2000) it became evident that the old hypotheses of “Genes and Junk” were debased by the obvious lack of expected genes, moreover a fractal hypothesis was already seeded (1-2), Eric Lander declared a conceptual vacuum of “hypothesis free search for genes” (3). Nobody dared issuing any attacks against him, especially not “ad hominem” slur for this, since it at least permitted a “no brainer” activity to supposedly last forever. As a mathematician he knew that, without scientific hypotheses proving or disproving by rigorous check their validity, research degenerated into a serendipituous mode - in English, to the horrendously expensive “brute force” – much like as a ship that randomly navigates without a compass; see the famous bestseller of Thomas Kuhn entitled “The Structure of Scientific Revolutions”.

It took less than a decade, when Dr. Pellionisz already published his Principle of Recursive Genome Function (12) and he was invited by George Church to present it in Cold Spring Harbor (17) that the Science Advisor to the President, Eric Lander put the fractal concept of genome on the cover of Science magazine (18).

The ensuing tumultuous the three years brought endorsements based on due diligence: “Of most interest to me are Andras Pellionisz’ ideas around the fractal nature of genomes and how disruptions in such structure may drive phenotypic variation ... The detection of these structure and subsequent determination of their association with disease are computationally intense problems. If something like this were shown to be true (disruptions in the fractal structures lead to phenotypic change), it would be truly revolutionary” (Schadt E, written communication to prominent IT industry).

Now the long-requested Proofs of Concept are in, the trickle of first findings rapidly becoming an avalanche of massive evidence (instead of “hypothesis-free search for genes”). In (18) and (25) with personal co-authorship of the Science Advisor to the President, it is shown that the unique fractal property of ultra-dense and knotless folding of DNA also has a “see through” feature (bringing to functional proximity all parts of the DNA, in a parallel manner) – but this “transparency” is lost e.g. by the fractal defect of a copy numuber alteration (26).

Along with fervent experimental-theoretical research (18-31) it is now recognized that Dr. Pellionisz “... revolutionized the biological sciences with geometrization of neuroscience and genetics. This has been achieved by application of recursion Algorithms based on the principle that each state of the system is deduced from its previous states just like in algebraic series” (30). Germany embraced his geometrization by the Senior Distinguished American Scientist Humboldt Prize, was invited as Keynote Speaker on FractoGene (2003 Florida), to Hungary (2006), to Cold Spring Harbor (2009), India embraced his fractal concept by Guest of Honor and Keynote Lectures and Decoration of his Lifetime Achievement (2012, Hyderabad and Trivandrum), an is presently invited to Italy (Bologna, June 2012). Geometrization of neuroscience drew its consequences on philosophy in Neuroscience by Patricia Churchland (Neurophilosophy, MIT) and on Unified Neuroscience and Genomics in 2012 by Niraj Kumar in India (30). Further, the roadplan outlined e.g. in personalized medicine, most notably cancer, (32) became a linchpin in fierce global competition of scalable full business models of emerging countries.

Most concpicuously, cancer may or may not become the first disease solved by computers, but at this time it might take a veritable computer illiterate to dream that the “genome disease” (cancer) can ever be solved without the leadership of those with software enabling algorithmic hypotheses, now within a single decade way beyond the POC stage.


(1) 1989 Pellionisz AJ, Neural geometry: towards a fractal model of neurons. In: Cotterill RMJ (ed) Models of brain function. Cambridge University Press, Cambridge, pp 453–464.

(2) 1993 Grosberg A, Rabin Y, Havlin S, Neer A (1993) Crumpled globule model of the three-dimensional structure of DNA. Europhys Lett 23:373–378.

(3) 2000 Lander E. (2000) A Hypothesis-free Search for Genes. Keystone Millenium Meeting: A Trends Guide (Page 48 in Neurosciences at the Postgenomic Era, by Jacques Mallet, Yves Christen, Springer, 2003)

(4) 2002 Pellionisz A; FractoGene Provisional submission to USPTO

(5) 2002 Plotkin H. (2002) Junk DNA Revisited. Silicon Valley startup claims to have unlocked a key to its hidden language. San Francisco Chronicle,

(6) 2003 Pellionisz A; FractoGene Regular submission to USPTO

(7) 2003 Pellionisz A. (2003) FractoGene Design-Tool for Protein-Based Self-Assembling Nanostructures, Materials and Applications Keynote Lecture of the 204th Electrochemical Society, pp. 1195

(8) 2006 Pellionisz, A. (2006) PostGenetics: Genetics beyond Genes. The journey of discovery of the function of "junk" DNA. Peer-invited and peer-reviewed Keynote lecture at "European Inaugural of the International PostGenetics Society", 12. October, 2006, Budapest, Hungary, a Satellite to the International Congress of Immunogenomics and Immunomics, pp. 219., BCII2006

(9) 2006 Simons M, Pellionisz A (2006a) Genomics, morphogenesis and biophysics: triangulation of purkinje cell development. The Cerebellum 5(1):27–35.

(10) 2006 Simons M, Pellionisz A (2006b) Implications of fractal organization of DNA on disease risk genomic mapping and immune function analysis. Australasian and Southeast Asian Tissue Typing Association. In: 30th scientific meeting 22–24 Nov 2006, Chiangmai.

(11) 2007 Pellionisz A; FractoGene CIP submission to USPTO

(12) 2008 The Principle of Recursive Genome Function, Springer, Cerebellum. 2008;7(3):348-59.
Full .pdf
Supplementary material

(13) 2008 October 30, Is IT Ready for the Dreaded DNA Data Deluge? YouTube approaching 14 thousand views

(14) 2008 Shapshak P, Chiappelli, F, Commins D, Singer E, Levine AJ, Somboonwit C, Minagar A, Pellionisz, A (2008) Molecular epigenetics, chromatin, and NeuroAIDS/HIV: translational implications. Bioinformation 3(1):53–57. PMCID: PMC2586134

(15) 2008 Chiappelli F, Shapshak P, Commins D, Singer E, Minagar E, Oluwadara O et al (2008) Molecular epigenetics, chromatin, and NeuroAIDS/HIV: immunopathological implications. Bioinformation 3(1):47–52.

(16) 2009 Cartieri FJ (2009) Darwinism and Lamarckism before and after Weisman: a historical, philosophical, and methodological analysis. University of Pittsburg, pp 1–54.

(17) 2009 Pellionisz A. (2009 September 16) From the Principle of Recursive Genome Function of HoloGenome Regulation by Personal Genome Computers (Cold Spring Harbor Labs “Personal Genomes II.” invited by George Church)

(18) 2009 Erez Lieberman-Aiden, Nynke L. van Berkum, Louise Williams, Maxim Imakaev, Tobias Ragoczy, Agnes Telling, Ido Amit, Bryan R. Lajoie, Peter J. Sabo, Michael O. Dorschner, Richard Sandstrom, Bradley Bernstein, M. A. Bender, Mark Groudine, Andreas Gnirke, John Stamatoyannopoulos, Leonid A. Mirny, Eric S. Lander, Job Dekker (2009 October 9) The comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326. doi: 10.1126/science.1181369
Full .pdf at

(19) 2010 Perez JC (2010) Codon population in single-stranded whole human genome DNA are fractal and fine-tuned by the Golden Ration 1.618. Interdiscip Sci: Comput Life Sci 2(3):228–340. doi:10.1007/s12539-010-0022-0.

(20) 2010 Arneth BM (2010) Sequence variability and sequence evolution: An explanation of molecular polymorphisms and why many molecular structures can be preserved although they are not predominant. DNA Cell Biol 29(10):571–576. doi:10.1089/dna.2009.0942

(21) 2010 Oller JW (2010) The antithesis of entropy: Biosemiotic communication from genetics to human language with special emphasis on the Iimmune systems. Entropy 12:631–705. doi:10.3390/e12040631.

(22) 2011 Stagnaro S (2011) Glycocalix quantum-biophysical-semeiotic evaluation plays a central role in demonstration of water memory-information.

(23) 2011 Stagnaro S, Caramel S (2011) A new way of therapy based on water memory-information: the Quantum biophysical approach.

(24) 2011 Elnitski L, Piontkivska H, Welch JR (2011) In: Fedorov A, Fedorava L (eds) Advances in genomic sequence analysis and pattern discovery, Chapter 3. Science, engineering and biology informatics, vol 7. World Scientific, Singapore, pp 65–93

(25) 2011 The genomic complexity of primary human prostate cancer (2011) Nature. 470, 214-220, doi:10.1038/nature09744 Michael F. Berger, Michael S. Lawrence, Francesca Demichelis, Yotam Drier, Kristian Cibulskis, Andrey Y. Sivachenko, Andrea Sboner, Raquel Esgueva, Dorothee Pflueger, Carrie Sougnez, Robert Onofrio, Scott L. Carter, Kyung Park, Lukas Habegger, Lauren Ambrogio, Timothy Fennell, Melissa Parkin, Gordon Saksena, Douglas Voet, Alex H. Ramos, Trevor J. Pugh, Jane Wilkinson, Sheila Fisher, Wendy Winckler, Scott Mahan, Kristin Ardlie, Jennifer Baldwin, Jonathan W. Simons, Naoki Kitabayashi, Theresa Y. MacDonald, Philip W. Kantoff, Lynda Chin, Stacey B. Gabriel, Mark B. Gerstein, Todd R. Golub, Matthew Meyerson, Ashutosh Tewari, Eric S. Lander, Gad Getz, Mark A. Rubin, Levi A. Garraway
Full .pdf at

(26) 2011 High order chromatin architecture shapes the landscape of chromosomal alterations in cancer (2011) Fundenberg G, Getz G, Meyerson M, Mirny L.A.

(27) 2011 The genetic code, 8-dimensional hypercomplex numbers and dyadic shifts. (2011) Petoukhov, Sergey V. International Conference on Bioinformatics & Computational Biology (Las Vegas, USA, July 18-21, 2011)

(28) 2012 February 17 Human mitotic chromosomes consist predominantly of irregularly folded nucleosome fibres without a 30-nm chromatin structure (2012) Yoshinori Nishino, Mikhail Eltsov, Yasumasa Joti, Kazuki Ito, Hideaki Takata, Yukio Takahashi, Saera Hihara, Achilleas S Frangakis, Naoko Imamoto, Tetsuya Ishikawa and Kazuhiro Maeshima

(29) 2012 February 17 Toward Convergence of Experimental Studies and Theoretical Modeling of the Chromatin Fiber (2012) Tamar Schlick, Jeff Hayes and Sergei Grigoryev, doi: 10.1074/jbc.R111.305763 February 17, 2012 The Journal of Biological Chemistry, 287, 5183-5191.

(30) 2012 March 11, Niraj Kumar (2012) Sryantra – Mathematical Properties. Geophilosophy of India and Sriyantra.

(31) 2012 March 13 Human mitotic chromosome structure: what happened to the 30-nm fibre? Jeffrey C Hansen The EMBO Journal (2012) 31, 1621–1623. doi:10.1038/emboj.2012.66; Published online 13 March 2012

(32) 2012 Andras J. Pellionisz, Roy Graham, Peter A. Pellionisz and Jean-Claude Perez (In Press) Recursive Genome Function of the Cerebellum: Geometric Unification of Neuroscience and Genomics. In: Springer Handbook; "The Cerebellum and Cerebellar Disorders", Ed. by M. Manto. Submitted October 20, Accepted November 1, 2011, (In Press)
Full .pdf


It is a twist of life that Ohno’s scientifically erroneous notion “So much ‘Junk’ in Our Genome” (1972), where his original, meant-to-be “scientific” statement that almost all of our DNA was there for “the importance of doing nothing”, see page 367 was misinterpreted, like other half-baked assumptions such as “Central Dogma”, that together set back Genomics by half a Century. As a further and ultimate irony, John Mattick and Malcolm Simons arrived at their respective final conclusions about the same time when the superseeding fractal paradigm prevailed. Dear Malcolm Simons passed away January 25th, 2012 in his 73rd year unrecognized outside the 66 Founders of International Hologenomics Society (Founders overlaping with the list below), where he was the Honorary Chairman.  Very soon after, Dr. Mattick received a lifetime-award from HUGO on March 12, 2012.

Finally, it bespeaks volumes of ignorance caused by lack of domain expertise in abstract sciences coupled with remarkable arrogance shrouded by thick denial, that a detractor calls the awarded Dr. Mattick “stupid and irrational”: “I am criticizing Mattick's ideas, which I find to be quite silly and irrational. Saying that Mattick is stupid and irrational because of what he writes and draws is not an ad hominem fallacy”. Dr. Mattick, who heroically struggles with a mathematical interpretation of the RNA system, may be comforted by the well-known history that Dr. Barbara McClintock was also called a “kook” by similar detractors – and awarded by a Nobel Prize some 40 years after her paradigm-shift.

Partial List of Personal Commitments in the First Decade

Andras J. Pellionisz, Roy Graham, Peter A. Pellionisz, Jean-Claude Perez, Sergey V. Petoukhov, Michael F. Berger, Michael S. Lawrence, Francesca Demichelis, Yotam Drier, Kristian Cibulskis, Andrey Y. Sivachenko, Andrea Sboner, Raquel Esgueva, Dorothee Pflueger, Carrie Sougnez, Robert Onofrio, Scott L. Carter, Kyung Park, Lukas Habegger, Lauren Ambrogio, Timothy Fennell, Melissa Parkin, Gordon Saksena, Douglas Voet, Alex H. Ramos, Trevor J. Pugh, Jane Wilkinson, Sheila Fisher, Wendy Winckler, Scott Mahan, Kristin Ardlie, Jennifer Baldwin, Jonathan W. Simons, Naoki Kitabayashi, Theresa Y. MacDonald, Philip W. Kantoff, Lynda Chin, Stacey B. Gabriel, Mark B. Gerstein, Todd R. Golub, Matthew Meyerson, Ashutosh Tewari, Eric S. Lander, Gad Getz, Mark A. Rubin, Levi A. Garraway, Grosberg A, Rabin Y, Havlin S, Neer A, Plotkin Hal, Simons J. Malcolm, Shapshak P, Chiappelli, F, Commins D, Singer E, Levine AJ, Somboonwit C, Minagar A, Oluwadara O, Cartieri FJ, Erez Lieberman-Aiden, Nynke L. van Berkum, Louise Williams, Maxim Imakaev, Tobias Ragoczy, Agnes Telling, Ido Amit, Bryan R. Lajoie, Peter J. Sabo, Michael O. Dorschner, Richard Sandstrom, Bradley Bernstein, M. A. Bender, Mark Groudine, Andreas Gnirke, John Stamatoyannopoulos, Leonid A. Mirny, Eric S. Lander, Job Dekker, Arneth BM, Oller JW, Stagnaro S, Caramel S, Elnitski L, Piontkivska H, Welch JR, Fundenberg G, Getz G, Meyerson M, Mirny L.A. Yoshinori Nishino, Mikhail Eltsov, Yasumasa Joti, Kazuki Ito, Hideaki Takata, Yukio Takahashi, Saera Hihara, Achilleas S Frangakis, Naoko Imamoto, Tetsuya Ishikawa and Kazuhiro Maeshima, Jeffrey C Hansen, Tamar Schlick, Jeff Hayes, Sergei Grigoryev, Church GM, Schadt E, Ruis J, Flanagan B, Audrey S M Teo, Pramila N Ariyaratne, Naoto Takahashi, Kenichi Sawada, Yao Fei, Sheila Soh, Wah Heng Lee, John W J Huang, John C Allen Jr, Xing Yi Woo, Niranjan Nagarajan, Vikrant Kumar, Anbupalam Thalamuthu, Wan Ting Poh, Ai Leen Ang, Hae Tha Mya, Gee Fung How, Li Yi Yang, Liang Piu Koh, Balram Chowbay, Chia-Tien Chang, Veera S Nadarajan, Wee Joo Chng, Hein Than, Lay Cheng Lim, Yeow Tee Goh, Shenli Zhang, Dianne Poh, Patrick Tan, Ju-Ee Seet, Mei-Kim Ang, Noan-Minh Chau, Quan-Sing Ng, Daniel S W Tan, Manabu Soda, Kazutoshi Isobe, Markus M Nöthen, Tien Y Wong, Atif Shahab, Xiaoan Ruan, Valère Cacheux-Rataboul, Wing-Kin Sung, Eng Huat Tan, Yasushi Yatabe, Hiroyuki Mano, Ross A Soo, Tan Min Chin, Wan-Teck Lim, Yijun Ruan, S Tiong Ong, Niraj Kumar

[This entry can be discussed on the FaceBook page of Andras Pellionisz - full .pdf copies may be requested - AJP]

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Well, This Is Awkward

April 18, 2012

The Walrus magazine's Mark Czarnecki says that "to comprehend genomes is to begin to unlock the mysteries of life." But that, of course, has been tricky. In the meantime, he says, society has found itself "lost on the gene map" — while [some] researchers have not yet nailed down their interpretations of the human genome, direct-to-consumer firms are hawking genetic tests and that offer to "detail your risks for a menu of diseases." All the while, researchers have struggled to understand the ethical, legal, and social implications of genomics.

Now, Czarnecki says, "with whole-genome sequencing providing so much data that is so little understood, making the best ethical choice is more difficult than ever." He goes on to add that "as the demand for whole-genome sequencing grows, so will profits, but the big money in personalized medicine will come from the development of treatments. … A given mutation on a person's genome may not necessarily express as a malignant disease, so identifying the probability of a multigenic disease is extremely challenging."

Overall, Czarnecki says that at present, "the human genome is still a vast catalogue of the unknown and scarcely known," and that "as medical science struggles to apply these new discoveries to society's benefit, human genome research, now unstoppable, continues to evolve."

[Indeed, it is kind of "awkward". We know ever since the mouse was fully sequenced a decade ago (2002) that our (human) "genes" are 98% identical to those of the mice; thus "upon arrival" the half-a-century assumption that the genome rotates around the "genes", was dead. Some know that in the same year, a decade ago, Leroy Hood declared in 2002 that "Genomics=Informatics" and thus must be approached from some "Systems Biology" viewpoint (invoking Ludwig von Berthalanffy, 1934). Of course, but WHAT SYSTEM? Without system identification systems biology would be rendered serendipitous (in plain English; horrendously expensive). Thomas Kuhn recalled in his famous bestseller "The Structure of Scientific Revolutions" that through the history of science, amassing data alone was never enough - it always underwent the transformative revelation of what the data actually mean. Some recall that in 2002 Pellionisz' "FractoGene" (at that time a "double lucid heresy" flying in the face of the two prevailing dogmas) identified that "the genome is a fractal systems, governing the fractal growth of organelles, organs and organisms" (like normal lungs, brain cells, etc., and cancerous tumors). Has anyone ever seen a fractal object generating another fractal object? Here is some little help: "Clouds are not spheres... nor does lightning travel in a straight line" said the now late giant, Mandelbrot. To remind you having seen "fractals generating fractals" here is my rendering:

FractoGene: "Fractal Genome governs growth of fractal organelles, organs and organisms" (Pellionisz, 2002 see also Geometric Unification of Neuroscience and Genomics, in Press 2012)

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Moore's Law versus Javon's Law: Drawning in the Dreaded DNA Data Deluge is mandated by law, unless ...

View YouTube with the "Jevons Paradox" proving what I predicted three and a half years ago. I warned that IT was not ready (now causing a killer glut of sequences, seen below). Bud Mishra proves that drawning in the data deluge is mandated by the Jevons's Paradox (already experienced) and only a drastic change in the algorithmic architecture can save Industrialization of Genomics from an implosion:

Join viewers from pivotal (sub)continents (USA, India) that an over 40 months warning was issued to prevent a historical unsustainability.

[As usual, there are always workers who believe that the role of science is to provide more data (not so, claimed Thomas Kuhn in his classic bestseller, "The Structure of Scientific Revolutions"). The present cop out is to claim that the science of genomics might be "hypothesis free". Eric Topol points out the self-contradiction of the latest genomic misnomer in his present bestseller. Just because some do not have any hypothesis of e.g. what the new definition of "gene" might be (replacing the old one made obsolete by ENCODE), does not mean that the "FractoGene" algorithmic hypothesis has to move over because of the pushy brute force of (ultra expensive) "big science" schemes. This issue can be debated on the FaceBook page of Andras Pellionisz]

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A Decade after Genomics was Declared to be Informatics; Vistas by Andras Pellionisz (Part I)

In 2002, a pair of seminal notions were introduced, just months after the much-heralded "solves it all" misnomer of "cracking the code" (that was at best a $3Bn Big Science coup, resulting in a crude first draft of revealing - not decyphering - a composite human genome), by Leroy Hood and Andras Pellionisz (separately). Lee Hood, in his Kyoto Prize lecture (2002) declared that "Genomics became Informatics" and thus proposed that it should be approached by System Theory (of Ludwig von Bertalanffy, 1934). I went in the same year of 2002 on written record of USPTO, since no peer-reviewed forum would have accepted his "double lucid heresy", by System Identification; that is, "The genome is a fractal system, that governs fractal growth of organelles, organs and organisms; FractoGene" (Pellionisz, 2002).

After a tumultuous Decade, in a series of notes here Dr. Pellionisz provides the "vistas" how the initial axioms led to conquering the half-a-Century old interlocking (false) Dogmas (the frighteningly unsophisticated "Central Dogma" and comparably simplistic falsehood of "Junk DNA"), towards a breakthrough of today, when both an advanced mathematical treatise of Unification of Neuroscience and Genomics, In Press, (featuring the RNA system as a "genomic cerebellum"), plus at least "the magic trio" of independent experimental Proof of Concept is in high-ranking peer-reviewed journals to validate that "fractal defects cause hereditary diseases" like cancers.

While in the USA "the priesthood of the establishment" (to use the jargon of Eric Topol from his book of The Creative Disruption of Medicine) has fought this revolution all the way (and beyond), Drs. George Church and Eric Schadt have grown to acknowledge my effort by my name, and implicitly Drs. Eric Lander and his numerous co-authors recognize the cardinal notion of fractal genome - as e.g. sophisticated outsiders llike Ray Kurzweil have immediately did so.

Lately, and entire Subcontinent (of India) provided support to a global and scalable business model based on fractal genome and scientifically targeted search for fractal defects as root causes of hereditary diseases. The illustration below alludes the immediate realization that even if not all DNA is fractal, "the DNA of Indian architecture" is based on self-similar repetition, it is fractal.

While NONE of the methods of science can ever be "hypothesis-free" (as Eric Topol alludes in his bestseller to the inherent hypocrisy), the software-enabling mathematical (fractal) theory is particularly well above the level of usually ultra-expensive "brute force approaches" - that would further enhance "unsustainable trends" of the PostModern Industrialization of Genomics.

[To be continued; the issue can be debated on the FaceBook page of Andras Pellionisz]

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TKI Cancer Treatment Resistance Linked to Common Germline Variant in East Asian Populations

By Andrea Anderson

NEW YORK (GenomeWeb News) – A Singapore-led team has identified a germline polymorphism that appears to account for reduced drug response in some East Asian cancer patients treated with tyrosine kinase inhibitors.

As they reported online yesterday in Nature Medicine, the researchers used massively parallel paired-end digital tag sequencing to look for germline variationsassociated with reduced response to TKI drugs, which are used to combat certain cancers marked by excess kinase activity, including some forms of chronic myelogenous leukemia and non-small cell lung cancer.

Using blood samples from five CML patients whose cancers did or did not respond to TKI treatment, the team found a resistance-related deletion polymorphism in BIM, a gene that normally helps spur on apoptosis following TKI treatment.

While this deletion appears to be a fairly common germline variant in East Asian populations — turning up in just over 12 percent of healthy individuals tested in that population — it has not been found with any regularity in populations from Europe or Africa.

The investigators have already started looking for alternative treatments for individuals with the variant, focusing on ways to restore the apoptotic activity that's lost when deletion-containing BIM isoforms are expressed. Indeed, their preliminary cell line experiments hint that it is possible to combat TKI resistance in those carrying the BIM deletion by augmenting TKI treatment with drugs known as BH3 mimetics.

"Ideally we would like to conduct clinical trials using a combination of TKIs and BH3 mimetics in patients with the polymorphism who have failed or become resistant to standard TKI therapy," co-corresponding author S. Tiong Ong, a medical oncology researcher at Duke-National University of Singapore, told GenomeWeb Daily News in an e-mail message.

TKI drugs such as imatinib (marketed as Gleevec by Novartis) or gefitinib (marketed by AstraZeneca under the brand name Iressa) have been successfully used to treat many kinase-driven cancers that did not respond to cancer drugs used in the past, study authors explained. But a subset of cases — around 20 percent — remain resistant to TKI drugs.

To look into the genetic basis of this resistance, the team did paired-end digital tag sequencing, or DNA-PET, with Life Technologies' SOLiD platform to look for germline structural variants that might help explain treatment response heterogeneity, using blood samples from two imatinib-sensitive and three imatinib-resistant CML patients.

"We correlated the structural variations detected by DNA-PET with clinical resistance to Gleevec, and picked out SVs which were found only in samples from resistant patients," Ong said in his e-mail.

A 2,903 base pair deletion polymorphism in an intron of the BIM gene coincided with TKI treatment resistance, they found.

The germline polymorphism appears to be fairly common in East Asian populations, turning up with around 12 percent carrier frequency in their screening experiments on thousands of healthy individuals. But the BIM deletion was not found in any individuals from African or European populations.

In addition, retrospective analysis of more than 200 CML patients enrolled in two cohorts from Singapore and Malaysia or Japan indicated that individuals with the BIM deletion were almost three times as likely to show imatinib resistance than those without the polymorphism.

Similarly, in East Asian non-small-cell lung cancer patients with EGFR mutations, the researchers found evidence for shorter progression-free survival in individuals with the BIM polymorphism who received TKI treatment compared to those without the deletion.

The team's cell line and other experiments indicated that BIM deletion affects treatment outcome by influencing BIM splicing patterns in a way that alters the apoptosis-related interactions of the resulting protein.

Whereas cells without the deletion typically expressed exon 4 in the presence of TKI compounds, cells with the polymorphism predominantly expressed exon 3 of the gene, which does not code for a domain necessary for apoptosis.

"The BIM deletion polymorphism results in the splicing (and expression) of BIM isoforms lacking a critical BH3 domain that is required for BIM apoptotic function," Ong said.

"Without this domain, the BIM protein isoforms which are produced in response to the TKI are no longer capable of killing the cancer cells," he added.

Moreover, the researchers found that even a single copy of the polymorphism was enough to prompt TKI resistance in CML and EGFR-mutation containing NSCLC cell lines.

Given their mechanistic findings, the team speculated that it might be possible to curb this intrinsic TKI treatment resistance by combining TKI treatment and therapy with so-called BH3 mimetics, compounds that restore the apoptosis promoting activity missing from cells expressing exon 3 rather than exon 4 of the BIM gene.

Preliminary experiments in CML cell lines supported that prediction, since treatment with both imatinib and the BH3 mimetic ABT-737 seemed to spur apoptosis even in the presence of the BIM deletion.

The team has not yet looked at how the TKI treatment resistance differences associated with the BIM polymorphism relate to overall survival patterns in patients, if at all. Ong noted that such studies are complicated by the fact that individuals who initially show TKI resistance often receive other treatments later on, making direct comparisons difficult.

Still, he and his colleagues hope to do prospective controlled clinical trials to look more closely at such questions.

They are also interested in doing clinical trials to explore the effectiveness of combined BH3 mimetic and TKI therapy for individuals with inherent resistance related to the BIM polymorphism or for patients who have become resistant to the inhibitors through another mechanism.

BH3 mimetics have not yet secured approval from the US Food and Drug Administration, Ong said, but are being tested in clinical trials for other cancer types.

In addition, working with collaborators from the Genome Institute of Singapore and A*STAR's commercialization arm, Exploit Technologies Private Limited, Ong and his colleagues are developing a kit that would make it feasible to routinely test East Asian patients for germline mutations in BIM.

A common BIM deletion polymorphism mediates intrinsic resistance and inferior responses to tyrosine kinase inhibitors in cancer

Authors:• et al.

Cancer & Stem Cell Biology Signature Research Programme, Duke–National University of Singapore (NUS) Graduate Medical School, Singapore.

King Pan Ng, Charles T H Chuah, Wen Chun Juan, Tun Kiat Ko, Sheila Soh, John W J Huang, Chia-Tien Chang, Shenli Zhang, Dianne Poh, Patrick Tan & S Tiong Ong

Genome Institute of Singapore, Singapore.

Axel M Hillmer, Audrey S M Teo, Pramila N Ariyaratne, Yao Fei, Wah Heng Lee, Xing Yi Woo, Niranjan Nagarajan, Vikrant Kumar, Anbupalam Thalamuthu, Wan Ting Poh, Patrick Tan, Atif Shahab, Xiaoan Ruan, Valère Cacheux-Rataboul, Wing-Kin Sung & Yijun Ruan

Department of Haematology, Singapore General Hospital, Singapore.

Charles T H Chuah, Ai Leen Ang, Hae Tha Mya, Gee Fung How, Li Yi Yang, Hein Than, Lay Cheng Lim, Yeow Tee Goh & S Tiong Ong

Department of Hematology, Nephrology and Rheumatology, Akita University Graduate School of Medicine, Akita, Japan.

Naoto Takahashi & Kenichi Sawada

Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Yao Fei

Centre for Quantitative Medicine, Duke-NUS Graduate Medical School, Singapore.

John C Allen Jr

Department of Hematology-Oncology, National University Cancer Institute of Singapore, National University Health System, Singapore.

Liang Piu Koh, Wee Joo Chng, Ross A Soo & Tan Min Chin

Clinical Pharmacology Laboratory, National Cancer Centre, Singapore.

Balram Chowbay

University of Malaya, Kuala Lumpur, Malaysia.

Veera S Nadarajan

Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Wee Joo Chng

Cancer Science Institute of Singapore, National University of Singapore, Singapore.

Wee Joo Chng, Patrick Tan & Ross A Soo

Department of Pathology, National University Health System, Singapore.

Ju-Ee Seet

Department of Medical Oncology, National Cancer Centre, Singapore.

Mei-Kim Ang, Noan-Minh Chau, Quan-Sing Ng, Daniel S W Tan, Eng Huat Tan, Wan-Teck Lim & S Tiong Ong

Division of Functional Genomics, Jichi Medical University, Tochigi, Japan.

Manabu Soda & Hiroyuki Mano

Department of Respiratory Medicine, Toho University Omori Medical Center, Tokyo, Japan.

Kazutoshi Isobe

Institute of Human Genetics, University of Bonn, Bonn, Germany.

Markus M Nöthen

Singapore Eye Research Institute, Singapore National Eye Centre and National University Health System, Singapore.

Tien Y Wong

Department of Pathology and Molecular Diagnostics, Aichi Cancer Center, Aichi, Japan.

Yasushi Yatabe

Department of Medical Genomics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.

Hiroyuki Mano

Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore.

Wan-Teck Lim

Department of Biochemistry, National University of Singapore, Singapore.

Yijun Ruan

Department of Medicine, Division of Medical Oncology, Duke University Medical Center, Durham, North Carolina, USA.

S Tiong Ong

Tyrosine kinase inhibitors (TKIs) elicit high response rates among individuals with kinase-driven malignancies, including chronic myeloid leukemia (CML) and epidermal growth factor receptor–mutated non–small-cell lung cancer (EGFR NSCLC). However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individual's response to TKIs. Using paired-end DNA sequencing, we discovered a common intronic deletion polymorphism in the gene encoding BCL2-like 11 (BIM). BIM is a pro-apoptotic member of the B-cell CLL/lymphoma 2 (BCL2) family of proteins, and its upregulation is required for TKIs to induce apoptosis in kinase-driven cancers. The polymorphism switched BIM splicing from exon 4 to exon 3, which resulted in expression ofBIM isoforms lacking the pro-apoptotic BCL2-homology domain 3 (BH3). The polymorphism was sufficient to confer intrinsic TKI resistance in CML and EGFR NSCLC cell lines, but this resistance could be overcome with BH3-mimetic drugs. Notably, individuals with CML and EGFR NSCLC harboring the polymorphism experienced significantly inferior responses to TKIs than did individuals without the polymorphism (P = 0.02 for CML and P = 0.027 for EGFR NSCLC). Our results offer an explanation for the heterogeneity of TKI responses across individuals and suggest the possibility of personalizing therapy with BH3 mimetics to overcome BIM-polymorphism–associated TKI resistance.

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MSKCC, IBM Developing Tool for Personalized Cancer Diagnosis and Treatment

March 22, 2012

GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – Memorial Sloan-Kettering Cancer Center in New York and IBM today announced they will work together to develop a tool to help doctors create individualized cancer diagnostic and treatment recommendations based on current evidence.

The tool will use the computational power and natural language processing ability of IBM's Watson system and be combined with MSKCC's clinical knowledge, existing molecular and genomic data, and repository of cancer case histories. The goal, the partners said, is to give physicians access to detailed diagnostic and treatment options based on updated research to make better decisions about patient care.

MSKCC's oncologists will assist in developing IBM Watson to use patient medical information "and synthesize a vast array of continuously updated and vetted treatment guidelines, published research, and insights gleamed from the deep experience of MSKCC clinicians to provide an individualized recommendation to physicians," it and IBM said in a statement.

Development work has begun for the first application, which includes lung, breast, and prostate cancers, with a goal of providing solutions to a select group of doctors in late 2012 and a wider distribution planned for late 2013.

"The combination of transformational technologies found in Watson with our cancer analytics and decision-making process has the potential to revolutionize the accessibility of information for the treatment of cancer in communities across the country and around the world," MSKCC President and CEO Craig Thompson said in a statement. He added that in addition to improving the personalized care of individual patients, the center expects new research opportunities to emerge from the collaboration.

Financial and other terms of the deal were not disclosed.

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Recent CDx, NGS Deals Signal Siemens' Increasing Interest in Genomics Arena

March 14, 2012
By Tony Fong

NEW YORK (GenomeWeb News) – As companion diagnostics gain acceptance within the pharmaceutical sector and next-generation sequencing progresses toward clinical applications, Siemens is seeking a bigger role in the genomics space.

In the past few months, the German-based electronics company has announced three deals that signal its renewed interest in genomics after largely being a spectator in recent years. Last month, it entered into an agreement with UK-based ViiV Healthcare to develop a companion diagnostic for evaluating patients who may benefit the most from an HIV treatment.

At the same time, it obtained the rights from Tocagen to commercialize a companion diagnostic for the San Diego firm's gene therapy for primary brain cancer. And in November, Siemens said it would make its molecular HIV tests compatible with Illumina's MiSeq platform under a partnership between the firms.

Until about three years ago, Siemens had been active in the 'omics space, forging several partnerships, including ones with Laboratory Corporation of America; Beckman Coulter, which is now part of Danaher; and Celera, now part of Quest Diagnostics. It also established a molecular diagnostics laboratory in Germany.

Since then, however, while Siemens is repeatedly mentioned as a possible buyer whenever a life science tools firm is up for sale, the company has kept a relatively low profile in the 'omics space. But as the results of the Human Genome Project begin to have some impact on the practice of medicine, Siemens is joining a handful of other large, diversified firms that are poised to increase their presence in the genomics space.

With the ViiV, Tocagen, and Illumina deals, Siemens is telling the genomics market that it is "ready to play," Harry Glorikian, founder and managing partner of Scientia Advisors, said.

According to Trevor Hawkins, head of next-generation diagnostics at Siemens Healthcare Diagnostics, the deals represent starting points for the company, catalyzed by what it sees as new phases in genomics technology development and a growing acceptance of the technology by both pharma/biotech and the clinical world.

Hawkins declined to disclose the level of Siemens' investment in its diagnostics operations. Overall, R&D in Siemens Healthcare reached €1.2 billion ($1.59 billion) in fiscal 2011 ended Sept. 30, 2011, or 31 percent of the €3.93 billion spent on R&D companywide.

The Healthcare business generated €12.52 billion in revenues in 2011, or 17 percent of total revenues of €73.52 billion. Within Healthcare, Diagnostics generated €3.67 billion in revenues during the year, unchanged from fiscal 2010.

While Siemens has an established medical imaging and in vitro diagnostics business, the ViiV and Tocagen deals are Siemens' first forays into companion diagnostics, fueled by growing adoption of such tools by drug developers, Hawkins said.

"We feel that pharmaceutical companies are now receptive to the use of diagnostics as an empowering tool for improved therapeutics," he told GenomeWeb Daily News recently, "and we felt that Siemens is rather unique in that we can offer the entire spectrum of capabilities of companion diagnostics," from assay design to clinical trials to assay commercialization.

Siemens has experience working with various types of assays, including immunoassays and molecular-based assays, he added, as well as different technologies. Its collaboration with Tocagen, for example, includes both molecular and immunoassays, and will encompass mass spectrometry and PCR technology, Hawkins said.

Also, as imaging increasingly plays a larger role in companion diagnostics, Siemens is positioned to leverage its expertise in that area, "and we look forward to bringing together the in vivo and in vitro components as a single solution in the companion diagnostics arena," he said.

In addition to ViiV and Tocagen, Siemens is working with other pharma firms in the companion diagnostics space, though Hawkins did not elaborate.

According to Glorikian, Siemens recent activity is a clear indication that it is "willing to make deals to gain access to the technologies and content that are going to be driving diagnostics growth for the next decade or so," he said in an e-mail to GWDN. "Every diagnostics company needs a strategy here and these deals are signs that Siemens is executing on theirs."

He added that while the company may have been less conspicuous in the genomics market in recent years, it may have been due not to a lack of interest but rather because of internal work directed at integrating other healthcare-related acquisitions, managing a challenging economic environment, especially in imaging, and addressing opportunities in healthcare informatics.

Stepping into Next-generation Sequencing

In the same way that Siemens views the ViiV and Tocagen transactions as the seeds of a companion diagnostics business, Siemens views its partnership with Illumina as an initial step toward adopting next-generation sequencing for clinical assay development.

The deal focuses on making Siemens' Trugene HIV-1 molecular tests compatible with Illumina's MiSeq benchtop sequencer. The test, which has been on the market for about a decade, was the first DNA sequencing-based HIV test approved by the US Food and Drug Administration.

Trugene is based on a technology called slab gel sequencing, and while the test has been "a really good product," Siemens believes that next-gen sequencing will be a transformational technology, Hawkins said, and the company "really needed to be part of the conversation around how next-gen [sequencing] was going to impact clinical diagnostics."

Trugene, he said, offered Siemens a "great example" of what it would take to move an existing assay onto a new technology platform, and in the process shed light on how next-gen sequencing could have clinical use.

While next-gen sequencing has generated a tremendous amount of buzz in the research community, it has had limited use in the clinic, and it may still be several more years before clinical adoption occurs in any meaningful way. Recently, Quintin Lai, an analyst at RW Baird, said in a research note that broad use of the technology will take time as hurdles such as regulatory and payor support, and as well as cost, still need to be addressed.

Attendees at the Future of Genomic Medicine conference earlier this month expressed doubt that the clinical $1000 genome was obtainable in the near term because although sequencing costs are going down, the "all-in" costs including training and interpretation remain high enough to keep clinical sequencing prohibitively expensive, Lai said.

Additionally, Hawkins said that other issues, such as how regulators will view the technology in the clinic, the quality of the data, the laboratory workflow, and how the data should be interpreted and analyzed, still need to be addressed.

Siemens has programs seeking to tackle many of these questions, and its deal with Illumina is expected to provide some answers, at least in relation to the Trugene assay, Hawkins said.

Illumina is fighting to prevent a $5.7 billion hostile takeover by Roche, which launched its bid for the company in January. A spokesperson for Siemens told GWDN that a potential deal has no effect on its partnership with the sequencing technology firm, which it regards as "as a key element toward providing our customers with a broad, high-quality menu of solutions that address their laboratory diagnostic testing needs."

Siemens is in discussions with the FDA about its plans to move Trugene onto the MiSeq system, and it is comparing patients samples run side by side on Trugene and on a next-gen sequencing-based test. Within the next 12 months, Siemens hopes to move into formal clinical trials for the test and then to submit a regulatory filing, Hawkins said.

He added that in addition to the Trugene test, "we wholly anticipate future assays to be moved over onto next-generation sequencing as well as completely new assays that next-gen sequencing empowers," such as oncology assays.

Maturing Ecosystem

Siemens' renewed push into genomics comes at a time when other large, diversified firms that play in the space are also strategizing to increase their presence. An official with Novartis, for example, told GWDN in December that companion diagnostics is a key strategic focus for that company. A year ago, a Johnson & Johnson executive also outlined that firm's molecular diagnostics strategy.

Scientia's Glorikian said that companies such as Siemens want to see "a level of maturity in an ecosystem," so that they can understand the rules of the game.

"What we’ve seen recently is that the genomics ecosystem, particularly the companion diagnostics area, is slowly becoming better understood," he told GWDN. "Pharmaceutical firms are more actively seeking diagnostics partners … [and] regulatory requirements are becoming better understood.

"We believe that any organization that is serious about having a molecular diagnostics business has to be thinking about their companion diagnostics programs. But it is easier said than done," he added. "There is a level of complexity in the companion arena that most organizations may not appreciate yet."

Hawkins said that for Siemens it also is a matter of clinical value. More than a decade after the first draft of the Human Genome Project was released, "we've gone through the early research phases, and now we're starting to really see the clinical relevance of individual genes, and gene clusters and signatures, and how they are linked to disease," Hawkins said.

"We see molecular as an important part of diagnostics, and we see more and more molecular is a piece of the [clinical] equation," he added. "This is a jigsaw puzzle that you are building here when you're trying to give informed information to the physician, and … at Siemens we see molecular as a very important piece of the diagnostic equation going forward."

[The entry of SIEMENS into Genomics is far more important than the last September 1st entry by SAMSUNG. Siemens is not "just another global IT giant", but perhaps the most potent company of the certainly most potent country of Europe (Germany). The "low profile" for too long, is probably largely due to the "genomically ultraconservative" Germany - but "the growing acceptance of pharma and clinical relevance" has finally broken through and Germany is on a spectacular rise. The entire global equation is altered by this "game changer" - This entry can be discussed on the FaceBook page of Andras Pellionisz]

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The Creative Destruction of Medicine

New York Times; BOOKS

Genomics as a Final Frontier, or Just a Way Station


Published: February 27, 2012

The medical world is holding its breath, waiting for the revolution. It will be here any minute. Definitely by the end of the decade. Or perhaps it will take a little longer than that, but seriously, it’s right around the corner. More or less.

That’s the genomics revolution, with its promise of treatment focused on the individual rather than the group. At last, patients will be more than the product of their age, sex, ethnicity, illnesses and bad habits; treatments will be aimed like a laser at their personal genetic particulars, and if those genes are not quite what they should be, then those genes will be fixed.

Over the last few years, various breathless visions of this therapeutic future have been written out for public admiration. A particularly readable and comprehensive version can be found in Dr. Eric J. Topol’s new book, “The Creative Destruction of Medicine.”

Dr. Topol, a cardiologist and researcher at the Scripps Research Institute with the energy of 10 (if his prose style and his honor-laden biography are any indication), dispenses in short order with our current population-based medical strategies. They are wasteful and inexact, he points out, often marginally beneficial to the group and downright harmful to the individual.

He presents an array of far better ideas, a few now actually being practiced in rudimentary form. These include pharmacogenomics, in which specific genes that govern responses to medications are routinely assayed, and cancer treatments that probe tumors for specific genetic targets rather than relying on standard chemotherapy.

But that’s not all: Dr. Topol also points out that soon a person’s precise genetic data will be augmented by an extraordinary wealth of other digital data (provided by, say, the continuous monitoring of blood pressure, pulse and mood, and a variety of ultra-precise scans). The outcome will be nothing short of a new “science of individuality,” one that defines individuals “at a more granular and molecular level than ever imaginable.”


The Creative Destruction of Medicine by Eric Topol

“A must-read that lays out a road map for how new technologies in genomics, information technology, and mobile medicine may completely change the way we treat and prevent illness. It’s highly recommended, because Topol has a unique vantage point: he’s one of the few researchers to have played an important role in the old, mass-market medicine world and the newer, genetically focused one.”


“Topol demonstrates how the digital revolution can be used to change individual care and prevention, and even the economics of American healthcare. From cell phones that automatically collect medical data, to biosensors, advanced imaging, individualized prescriptions and gene-specific drugs, Topol’s book leads readers through science-fiction-sounding scenarios that may soon be a reality.”


“The Creative Destruction of Medicine - an allusion to economist Joseph Schumpeter’s description of ‘creative destruction’ as an engine of business innovation is a venture capitalist’s delight, describing dozens of medical technologies that show great promise. The book also provides colorful anecdotes about Dr. Topol’s own sampling of these products, as both a doctor and stand-in patient…. [The book’s] most important contributions are in portraying how medical innovation will coalesce to change clinical practice and what the coming changes mean for today’s policy debates…. In Dr. Topol’s vision, innovation that enables real-time diagnosis and personalized treatments is a certainty, though not because reluctant or ‘sclerotic’ doctors accept it or because Washington wills it into being. A seductive technology that works like a dream and improves lives will set off a consumer clamor, whether the new tool is an iPhone 4S or an implantable blood-sugar meter.”

Wall Street Journal

“Topol does an excellent job of explaining all, and his enthusiasm for the possibilities of what the future holds is infectious. It can only be hoped, as the convergence he so convincingly predicts materializes, that the barriers erected by the gatekeepers of yesterday’s paradigms will be easily dismantled so as not to impede the benefits it promises.”

Boston Globe

“An eye opening account of why conventional medicine is doomed…. [C]ompelling stuff…. [T]he book provides an excellent summary of the current state of medical genetics and how fast it is progressing, with examples that may surprise even those working in medicine.”

New Scientist

“Topol makes the case that the masses of macro-data at our fingertips (literally), will unleash micro-level diagnostic and curative solutions never before imagined or hypothesized. It’s a remarkably bold vision that many experienced physicians will call naïve since it defies conventional wisdom - which is precisely why I think he’s on to something big.”

Longwoods eLetter

[A] prescient view of the near future of medicine…. Every patient should read this book in order to understand the rapidly evolving role in they play in their own care…. The Creative Destruction of Medicine is a call to action for doctors and patients alike. We must see our world and our job as doctor and patient very differently. In a profession so uncertain of its future, we need precisely the vision and critical dialog offered here…. I suspect that 150 years from now when historians are looking back at the most dramatic flexion point in medicine’s history they’ll reference this book as one of the first to identify the start of medicine’s creative destruction.”

Bryan Vartabedian, MD, 33

Modern medicine needs a makeover. Topol, of the Scripps Research Institute, believes the process begins with embracing the digital world. His plan involves genomics, wireless biosensors, advanced imaging of the body, and highly developed health information technology. Smartphones will tie these elements together to make health care individualized,efficient, and accessible. Topol foresees a future medical landscape characterized by virtual house calls, remote monitoring, and a lessened need for hospitals.”

Sharon Begley, Kirkus Reviews

“The book makes a compelling case for the role of digital technology in bringing nimbleness to ossified healthcare systems worldwide.”

Calestous Juma, Harvard Kennedy School

Our sequencing of the human genome eleven years ago was the beginning of the individualized medicine revolution, a revolution that cannot happen without digitized personal phenotype information. Eric Topol provides a path forward using your digitized genome, remote sensing devices and social networking to place the educated at the center of medicine.”

J. Craig Venter,Chairman and President, J. Craig Venter Institute

“Eric Topol gives us an eye-opening look at what’s possible in healthcare if people can mobilize to charge the status quo. The Creative Destruction of Medicine is simply remarkable.”

Clayton M.Christensen, Robert and Jane Cizik Professor of Business Administration, Harvard Business School,and author of The Innovator’s Dilemma

“Eric Topol has been a longtime innovator in healthcare. In The Creative Destruction of Medicine, he cites the big waves of innovation that will save healthcare for the future. Real healthcare reform has not yet begun, but it will. The Creative Destruction of Medicine lays out the path.”

Jeffrey Immelt,Chairman and CEO of General Electric

“This is the one book to read for a complete and clear view of our medical future, as enabled by the convergence of digital, mobile,genomic, and life science breakthroughs. Dr. Topol explains how iPhones, cloud computing, gene sequencing, wireless sensors, modernized clinical trials,internet connectivity, advanced diagnostics, targeted therapies and other science will enable the individualization of medicine - and force overdue radical change in how medicine is delivered, regulated, and reimbursed. This book should be read by patients, doctors, scientists, entrepreneurs, insurers,regulators, digital engineers - anyone who wants better health, lower costs, and participation in this revolution.”

Brook Byers,Partner, Kleiner Perkins Caufield & Byers

“Eric Topol is that rare physician willing to challenge the orthodoxies of his guild. He recognizes that in the U.S., health care business-as-usual is unsustainable. But he does not despair. He bears witness to the rise of Homodigitus and the promise it holds to upend the inefficiencies and dysfunction so entrenched in clinical medicine. The Creative Destruction of Medicine is a timely tour de force. It is a necessary heresy.”

Misha Angrist, Assistant Professor, Duke Institute for Genome Sciences & Policy, and author of Here is a Human Being

“Much of the wealth created over the last decades arose out of a brutal transition from ABC’s to digital code. While creating some of the world’s most valuable companies, this process also upended whole industries and even countries. Now medicine, health care, and life sciences are undergoing the same transition. And, again, enormous wealth will be created and destroyed.This book is a road map of what is about to happen.”

Juan Enriquez,Managing Director, Excel Venture Management, and author As the FutureCatches You

Health care is poised to be revolutionized by two forces - technology and consumerism - and Dr. Eric Topol explains why. One-size-fits-all medicine will soon be overtaken by highly personalized,customized solutions that are enabled by breakthroughs in genomics and mobile devices and propelled by empowered consumers looking to live longer, healthier lives. Fasten your seat belts and get ready for the ride—and learn what steps you can take to begin to take control of your health.

Steve Case,co-founder, AOL, and founder of Revolution LLC

“If we keep practicing medicine as we know it today, healthcare will become an unbearable burden. We are in a real race between healthcare innovation and the resistance to change of the medical system. In a comprehensive and well researched tour de force, Eric Topol, always a clear and uncompromising thought leader of his generation, challenges us to imagine the revolutionary potential of a world where medical information no longer belongs to a few and can be automatically collected from the many to greatly improve healthcare for all. This is a must read!”

Elias Zerhouni, MD, President, Global R&D, Sanofi and former director, National Institutes of Health

Dr. Topol believes that medicine, catalyzed by extraordinary innovation that exploits digital information, is about to go through its biggest shakeup in history. His newest book calls for a ‘jailbreak’ from the ideas of the past. In the next phase of medicine, powerful digital tools including mobile sensors and advanced processors will transform our understanding of the individual, enabling creative ‘mash-ups’ of data that will spark entirely new discoveries and spawn ultra-personalized health and fitness solutions. And with over 5.7 billion mobile connections worldwide, the mobile technology platform will have a major impact on that vision - leading to what Dr.Topol describes as nothing less than a ‘reboot’ of the health care system. Qualcomm, and its partners all around the world, are working to bring wireless innovations to market that will contribute to the solution. And we share Dr.Topol’s view that individual consumers have the opportunity, and the power, to increase the pace of the titanic change that’s coming.”

Paul E. Jacobs,PhD, Chairman and CEO, Qualcomm Incorporated

What happens when you combine cellular phone technology with the cellular aberrations in disease? Or create a bridge between the digital revolution with the medical revolution? How will minute biological sensors alter the way we treat lethal illnesses, such as heart attacks or cancer? This marvelous book by Eric Topol, a leading cardiologist, gene hunter and medical thinker, answers not just these questions, but many many more.Topol’s analysis draws us to the very front lines of medicine, and leaves us with a view of a landscape that is both foreign and daunting. He manages to recount this story in simple, lucid language—resulting in an enthralling and important book.”

Siddhartha Mukherjee, author of The Emperor of All Maladies: A Biography of Cancer

“What happens when the super-convergence of smart phones further combines with million-fold lower-cost genomics and diverse wearable sensors? The riveting answer leads to a compelling call to activism—not only for medical care providers, but all patients and everyone looking for the next ‘disruptive’ economic revolution. This future is closer than most of us would have imagined before seeing it laid out so clearly. A must-read.

George Church,Professor of Genetics, Harvard Medical School

“Dr. Topol is the top thought leader in medicine today, with exceptional vision for how its future can be rebooted. This book will create and catalyze a movement for the individualization and democratization of medicine - and undoubtedly promote better health care.”

Greg Lucier, CEO, Life Technologies

“Eric Topol is the perfect author for this book.He has a unique understanding of both genomics and wireless medicine and has a remarkable track record as a charismatic pioneer, visionary, and change agent in medicine. I’m sure this book will reach a very large number of people with information that can both empower and help transform their lives for the better.”

Dean Ornish, M.D., Founder and President, Preventive Medicine Research Institute, and author of The Spectrum

“Dr. Eric Topol is an extraordinary doctor. He’s started a leading medical school, identified the first genes to underlie development of heart disease, led major medical centers, and been a pioneer of wireless medicine. But he is also a remarkable communicator - one of the few top-flight scientists in medicine to be able to genuinely connect with the public. He was, for example, the first physician researcher to question the safety of Vioxx - and unlike most who raise safety questions, actually succeed in bringing the concerns to public attention. I have known and admired Dr. Topol for a long time. I recommend him highly.”

AtulGawande, M.D., author of The Checklist Manifesto

“Eric Topol is uniquely positioned to write such a timely and important book. He leads two institutions - one in genomics and one in wireless health - that will each play a huge role in transforming medicine in the twenty-first century. From this vantage point, he can see unifying themes that will underlie the coming revolution in population and personal health, and he communicates his vision with vibrant energy. Everyone will want to read this book.”

James Fowler,Professor of Medical Genetics and Political Science, UC San Diego, and author of Connected

[Dr. Eric Topol says in his book that "the train has already left the station". Indeed, this column cited on Oct. 15, 2007 "The Year of Miracles" Newsweek article by Prof. Lee Silver . As the column's remarks observed, however, in five years ago (2007), precisely since the article foreshadowed a "Creative Destruction of Medicine", the artilce "Annus Mirabilis" by Prof. Lee Silver was published in all Editions of Newsweek - EXCEPT in the US-Canadian Edition (where there wasn't a single word about it). This colum cited the paper from the European Edition...

The Year of Miracles (Annus Mirabilis) by Lee Silver (full paper)

Likewise, the establishment did not take it very well that Genomics became Informatics (in 2002 Leroy Hood framed Genome Informatics in terms of Systems Biology, while Andras Pellionisz defined it as a Fractal System; FractoGene 2002). Particularly crass detractors came to the fore when Pellionisz published the peer-reviewed science paper "The Principle of Recursive Genome Function" (popularized by the Google Tech Talk YouTube in the same year of 2008), and subsequent YouTube-s on Personal Genome Computing and Personalized Genome Assistant mobiles (for an age when e.g. in India many more people carry smart phones than the number with access to a sewage system):

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A scalable global business model and a (sub)continent offers support of Pellionisz' Fractal Approach: Ten slides winning over a (sub)continent for funding Pellionisz' Fractal Approach

Dr. Andras Pellionisz was a Guest of Honor as well as Keynote Speaker at the ICSCI-2012 "International Conference on Systemics, Cybernetics and Informatics" in Hyderabad, Andhra-Pradesh (February 15-18, 2012, organized by Prof. E.G. Rajan), and subsequently at the ICETT-2012 "International Conference on Emerging Technology Trends on Advanced Engineering Research" in Kollam, Kerala (February 20-21), organized by Prof. B. Kumar. His biophysics-approach, using tensor- and fractal geometry to unify genomics and neuroscience was awarded at both international congresses. In the third state of Karnataka, in Bangalore, he conducted discussions in addition to Academia with Private sector, and Government officials. As also reflected by a visit a few weeks earlier by Dr. Francis Collins NIH Director (see below in this column), India flexes muscles to answer the challenge that the genome informatics initiatives of China (BGI) and Korea (Samsung) represent.

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Roche’s Illumina Bid May Spur Buying in DNA Test Land Grab

January 31, 2012, 12:32 PM EST


By Robert Langreth, Meg Tirrell and Ryan Flinn

(Updates with closing share price in the fifth paragraph.)

Jan. 26 (Bloomberg) -- Less than 10 years after the first human genome was decoded, Roche Holding AG’s hostile $5.7 billion bid for Illumina Inc. may spark additional deals as companies race to bring DNA scanning into routine medical use.

Illumina competes with Life Technologies Corp., Affymetrix Inc. and other companies to sell gene-decoding machines that are just starting to be used to tailor therapies for patients with cancer and inherited diseases. While scientific excitement around genome sequencing is high, the companies’ shares have plummeted over the last year because their target customers are mostly scientists dependent on grants in a tough economy.

Getting the technology out of the lab and into doctors’ offices and hospitals could vastly expand the existing $1.5 billion market for gene sequencing machines, industry officials and analysts said.

“This is going to be an enormous opportunity, and now you see it unfolding,” said Greg Lucier, chief executive officer of Life Technologies, based in Carlsbad, California, in a telephone interview. The bid Roche is an acknowledgment that DNA mapping is key to the future of diagnostics, particularly involving its use in cancer treatment, he said.

Illumina today adopted a so-called poison-pill takeover defense in which shareholders will receive one preferred stock purchase right as a dividend for each common share held as of the close of business on Feb. 6.

The San Diego-based company fell 4.5 percent to $52.65 in New York trading. Roche, based in Basel, Switzerland, rose less than 1 percent to 160.20 Swiss francs in Zurich.

‘Unwilling to Participate’

Roche made its hostile offer directly to Illumina shareholders after saying the testing company was “unwilling to participate in substantive discussions,” according to a statement yesterday.

The rights agreement adopted today by Illumina can block a hostile bid by making it prohibitively expensive. Should Roche or another bidder own 15 percent or more of Illumina’s stock, other shareholders will be able to exercise the rights to buy new common stock, diluting the stake of the prospective bidder.

Before initial talk of a takeover attempt surfaced in December, the shares of Illumina -- which draws a third of its revenue from researchers funded by the National Institutes of Health -- had dropped 58 percent over 12 months. Life Technologies and Affymetrix also tumbled, leaving them as vulnerable as Illumina to buyout bids, said Bill Bonello, an analyst with RBC Capital Markets in Minneapolis.

‘Intensity M&A Angle’

“This will intensify the M&A angle people will look at with these stocks,” Ross Muken, an analyst with Deutsche Bank Securities Inc. in New York, said in a telephone interview.

The human genome was first sequenced in 2003. The market for machines that map DNA has been “fast-growing” over the last five years, said Daniel O’Day, chief operating officer of Roche’s diagnostics division, in a conference call yesterday.

“We expect that to continue into the future,” O’Day said. “Today, it is over a $1 billion marketplace, and we expect that to be over a $2 billion marketplace in 2015.”

The devices sold by Illumina, Life Technologies and Affymetrix search through DNA coding that contains the instructions for making all human cells. Scientists use the technology to build an understanding of how variations or mutations found by the machines contribute to disease.

Cancer Variations

This is particularly true in cancer, where variations can contribute to uncontrolled cell growth. Doctors want to use genetic data to aim cancer treatments precisely at these variations, and stop only diseased cells from growing. Genome sequencing is also helping doctors understand, diagnose and, in some cases, treat mysterious childhood diseases that had previously taken years to identify.

The National Human Genome Research Institute has allocated funds to determine how to integrate individuals’ genetic information into day-to-day clinical care issues, such as the appropriate dosing of drugs.

Already, U.S. regulators are working with drugmakers in approving cancer drugs tied to companion genetic tests. Pfizer Inc.’s crizotinib, a treatment for a form of lung cancer caused by a genetic defect, was approved in August along with a companion diagnostic made by a unit of Abbott Laboratories that determines whether a patient has the abnormal gene.

Roche, the world’s biggest developer of cancer medicines, has particular experience with gene-targeted therapies.

Herceptin, Zelboraf

The company sells the breast-cancer drug Herceptin, one of the first cancer medicines aimed only at a subset of patients whose tumors have a particular genetic abnormality. In August, it garnered U.S. regulatory approval for Zelboraf, a melanoma drug that works on patients whose tumors have a certain gene mutation. Roche also sells a companion test with Zelboraf.

While Roche may be a pioneer in its bid for Illumina, it isn’t clear that other drugmakers will seek to acquire similar companies unless they already have a toe in the business, said Les Funtleyder, a portfolio manager with Miller Tabak & Co. in New York, whose fund owns Illumina shares.

“It seems like a bit of a leap for a pharmaceutical company to get into a whole new line of business,” Funtleyder said in a telephone interview. “You don’t need a sequencer to develop a companion diagnostic; you just need the sequence. And you can outsource that.”

Funtleyder cited General Electric Co. and Abbott as companies with existing businesses that may consider a similar acquisition.

‘Best in Class’

With Illumina, Roche is “buying best in class,” said Peter Lawson, an analyst with Mizuho Securities in New York, by telephone. “Illumina’s one of the most interesting companies in this space. They’ve been serial innovators, they’ve been great acquirers of technology and great executors.”

Illumina has been in a race to develop the first machine to be able to parse the building blocks of life in a day, rather than weeks or months. It announced Jan. 10 that it would market such a machine in the second half of this year. Life Technologies said on the same day it had reached the same goal. The current Illumina machines can sequence five human genomes in 10 days, according to the company.

Erik Gordon, a professor at the Ross School of Business at the University of Michigan in Ann Arbor, sees Roche and Illumina as a perfect fit.

“On its own, Illumina will have trouble reaching the broader clinical markets for its devices and will remain dependent on the shaky government-funded markets,” Gordon said in an e-mail. ‘As part of Roche, it quickly gets through the door at clinics worldwide.”

At the same time, he said, “Roche gets another product to run through its sales channel.”

Harvard Geneticist

George Church, a Harvard Medical School geneticist who has founded and advised numerous companies in the industry, said Roche “probably had their eye on Illumina for a long time and were waiting for the price to come down. They knew it was a valuable company; why not buy it at its lowest point?”

The sequencing technology is moving so fast the Illumina technology may become quickly outmoded, said Craig Venter, who led a private team that sequenced one of the first two human genomes a decade ago and runs the J. Craig Venter Institute in Rockville, Maryland.

“I don’t understand why Roche would do this deal when the technology is changing so rapidly,” he said. “I am puzzled.”

When Venter was racing a government team to scan the first human genome, he needed 300 expensive sequencing machines in 100,000 square feet of lab space, he said. Now researchers can build a world-class facility with just 10 smaller desktop machines, he said.

Four Years Difference

“One of these new machines replaces 100 of our old machines four years ago,” he said.

Michael Pellini, chief executive officer of Foundation Medicine in Cambridge, Massachusetts, a company that sells a test looking at 200 cancer genes, said the research market for the machines is saturated while the far bigger market of potential routine medical use is just emerging.

“This technology has not crossed over into the clinical world in earnest,” Pellini said in a telephone interview. “That is the big disconnect.” Roche can help bridge the divide with its expertise in diagnostic tests, he said.

Roche’s pursuit of Illumina reflects the growing focus of health-care companies on personalized medicine, said Susan Clark, professor of medicine at the University of New South Wales, whose lab at the Garvan Institute in Sydney uses Illumina equipment to study cancer gene expression.

The challenge is to better match their cancer therapies with the specific patient populations who will be benefit most, she said. Faster DNA scanning technologies could help, she said.

“A lot of money has been spent by pharmaceutical companies to try to find designer drugs,” Clark said in an interview. “But with designer drugs, you need to know the population that they will target because they are so expensive.”

--With assistance from Jason Gale in Singapore, Naomi Kresge in Berlin and John Lauerman in Boston. Editors: Reg Gale, Andrew Pollack

To contact the reporters on this story: Robert Langreth in New York at; Meg Tirrell in New York at; Ryan Flinn in San Francisco at

To contact the editor responsible for this story: Reg Gale at

[I predicted a "Dreaded DNA Data Deluge" in my Google Tech Talk YouTube in 2008 since Sequencing, with billions of dollars of investment became one half of "Industrialization of Genomics" - while the other half, Analytics was not attended, and therefore an oversupply of sequences produced an unsustainability. As a result, all four major "Sequencing Companies" lost much of their valuation (illustrated by stock-market graphs added to the New York Times article "DNA Sequencing Caught in a Deluge of Data", November 30th below). There should be no question that a major wave of merger/acquisition of the type of Roche/Illumina will occur - but in itself will not solve the problem. Without the two types of IT (Information Technology and Information Theory), requiring the SAMSUNG-type of genome analytics service, Industrialization of Genomics will remain unbalanced. If/when "Roche" will acquire "Illumina", look for their next step, to globalize their solution with IT, preferably in Asia]

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Genome Informatics, Globalized; - USA - China - Korea - India

Francis Collins (in Bangalore)

How much does the US spend on medical research?

Typically, the NIH invests $30 billion every year. But I should say the budget's been about there for almost eight years. We're having difficulties in fiscal deficit, so medical research may not grow much in the near future. Thoughtful decisions have to be taken on what we want to do.

What strengths do you see in Indian institutions? How are they compared to China?

India's great strength now is its IT and computational capacity. Biology is now more a computational science. To understand diseases like diabetes and cancer, we need computational strategies to sift through vast datasets. India can provide that asset.

India is on right track for biomedical research, says NIH director


Bangalore, Dec 05, 2011: Currently on a tour of India to improve collaborations between research institutes in India and the NIH, Dr Francis Collins, director, NIH, USA, spoke about the impact NIH funding has had on research in India and how it intends expand its presence in India.

National Centre for Biological Sciences (Bangalore)

Francis Collins in Bangalore


Andras Pellionisz, Board of Advisors to ELOGIC Technologies in Bangalore, tours Bangalore, Hyderabad, Trivandrum

China excels in Genome Informatics by running in BGI (Shenzhen) the World's largest capacity of Genome Sequencing Machines (all USA-made), and employing up to 4,000 computer scientists, with an every age of 27, with access to the World's fastest supercomputers (a hybrid of Intel serial chips and NVIDIA graphics parallel chips, all USA-made). Korea announced by Sept. 1, 2011 that SAMSUNG started to provide a Global Genome Analytics Service.

India's strengths, as Francis Collins pointed out in Bangalore, to deploy her massive IT and mathematics expertise towards personalized therapy against cancer, combined with clinical trials.

Andras Pellionisz, his science presentation featured above in Hyderabad, builds collaborations of Silicon Valley of California with "Silicon Valley of India"; Bangalore.

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UNESCO’s Memorial Year Honours János Szentágothai

[János Szentágothai - AJP]

As decided by the general assembly of UNESCO, the year 2012 is to be dedicated to honour the 100th birthday of János Szentágothai, a formal president of the Hungarian Academy of Sciences and a groundbreaker in his field. According to Ambassador Katalin Bogyay, the memorial year provides a unique opportunity to showcase the achievements of Hungarian science and Hungarian culture in general to a wider audience through the legacy of the great Hungarian scientist.

UNESCO has long been taking part in commemorating the anniversaries of historical events and outstanding personalities. The national committees of the organisation may make such proposals each year. Headed by member of HAS József Hámori, the Hungarian National Committee initiated a Szentágothai Memorial Year, a proposal supported by the Jury of Experts and the Executional Council and finally was accepted by UNESCO's General Assembly.

"According to my plans, an exhibition and conference are going to be organised commemorating the greatness of János Szentágothai in the centre of UNESCO in Paris. Through introducing his life to an international audience, we are to bring the achievements of Hungarian science into the forefront, while also drawing attention to the responsibility of science and to the connection between science and art", Katalin Bogyay said. "As a Christian thinker and music teacher Franz Liszt had been an ambassador of Hungarian culture in his age, so was János Szentágothai committed to both science and art, a true renaissance man of Hungarian intellectual life."

"János Szentágothai was a real founder of a school of thought. We, today's Hungarian brain researchers, are all standing on his shoulders", former student József Hámori said. Member of HAS and President of the Hungarian UNESCO Committee, professor Hámori started his career at the Department of Anatomy of Pécs University in 1955 where János Szentágothai had established a research community whose members not only improved in expertise but also had the chance to enrich the spiritual-cultural aspects of their personalities. "We worked from 9 am. until late evening every day, but were not doing science exclusively", József Hámori recalls. "The art of painting, baroque music was just as often the topic of our discussions as was poetry." However it was his findings in brain research that had earned him world fame. Among these were his results on the functions of the spinal cord, the cerebellum, and the structure of the neocortex, making him a Nobel-prize nominee several times.

Besides being an avid researcher, János Szentágothai had great affection for teaching and always encouraged his students to pass on their knowledge. He considered education as a crucial aspect of science, not only for the sake of the next generation, but also because he believed it's the perfect way for teachers to keep their knowledge up-to-date. Professor Szentágothai authored Functional Anatomy and the Atlas of Human Anatomy with Miklós Réthelyi and Ferenc Kiss respectively.

János Szentágothai was the President of the Hungarian Academy of Sciences between 1977 and 1985. Besides holding several national awards, he was also a member of many international organisations, such as the Royal Society, and the Papal Academy of the Vatican. He was an honorary doctor at several universities, among them the University of Oxford. Professor Szentágothai also played a significant role in the public life of Hungary. He was a representative of science in the Hungarian Parliament until his death in 1994.

[Why was Prof. Szentágothai passed over for Nobel Prize? - AJP]

The simple answer is that the Nobel Committee did not vote him in. At what rate and why not, is only guesswork, since the Minutes of the Committee are classified for 50 years.

As a pupil of the “Szentágothai school” since 1967, my belief is that the reason might be that the “Grand Old Man” thought and acted in terms of “Schools of Science”, not limited to that of his own. For the Nobel Committee, however, it is much easier to award the Prize to focused efforts, especially since the Science Prizes are to be awarded to living persons, divided at a maximum to three people.

Prof. Szentágothai built his school of science to a large degree on that of the schools of “vestibulo-ocular cerebellar systems” of Drs. Bárány, Hőgyes and Lenhossék – wherein Dr. Bárány was already some time ago awarded by the Nobel Prize. In itself, this could not be a major problem, as both Drs. Kornberg and his son were awarded. In Szentágothai’s school, like in all schools of excellence, there was more than a single eminent course.

There seems to be no doubt that the legacy of Hungarian schools of science, and the international schools of science that Prof. Szentágothai built a solid alliance with, made the cerebellar sensory-motor system a pre-eminent focus of his ouvre – with the cerebellum making up to 1/3 of the brain with birds top make them capable of coordinated flight.

By 1967 János Szentágothai was about ready with the proof of their Springer book, co-authored with the leading British-Australian-American Sir John (Eccles) Nobel Laureate and Japanese Masao Ito. The title was “The Cerebellum as a Neural Machine”. This splendid accomplishment could have been the reason for János Szentágothai NOT having been awarded by a Nobel. Why? The bestseller book, according to Google Scholar under “Eccles” was cited 2,117 times – that is far more than any citation of Szentágothai’s own publications (highest is 472, often in different fields). Thus, it could be difficult to award a Nobel for the authors of the book, divided to the maximal three allotted recipients who might share the Prize. For one issue, this would have been the second Nobel to Sir John (Eccles). Not impossible, for the precedents of double Laureates. However, the electrophysiology of the cerebellum, comprised in the book, was the result of cardinal collaborative effort with Rodolfo Llinás and other colleagues, and similarly the electronmicroscopy laid out in the book was performed largely by József Hámori. Third, the contribution to the book by the Japanese Masao Ito was his flabbergasting discovery that the sole output of the cerebellum, from the Purkinje neurons, are inhibitory (as opposed to the expected excitatory action). The book on the “Neural Machine” simply could not interpret this experimental result. As a conclusion, on the very last page of the book (pp. 177.) the main three authors, altogether at least five individuals, over the limit of maximal three for any Nobel, confessed in effect that “we know everything about the neural networks of the cerebellum, except how it works as a Neural Machine”. The Nobel Committee could have wondered about the best stance towards a book that verbatim predicted by the last sentence of the book that “It is essential to be guided by the insights that can be achieved by communication theorists and cyberneticists who have devoted themselves to a detailed study of cerebellar structure and function. We are confident that the enlightened discourse between such theorists on the one hand and neurobiologists on the other will lead to the development of revolutionary hypotheses of the way in which the cerebellum functions as a neuronal machine and it can be predicted that these hypotheses will lead to revolutionary developments in experimental investigation”. Pondering over such a mesmerising conclusion, perhaps they thought that “there are too many authors now and the conclusion still awaits some time” and decided to reconsider any award for the function of the cerebellum later.

It is noteworthy that Szentágothai was ahead of his time far further than he could have ever envisioned. Springer is just proofing their handbook “The Cerebellum and Cerebellar Diseases”, in which a Chapter on Recursive Genome Function of Cerebellum: Geometric Unification of Neuroscience and Genomics” reveals that the mathematical “trick” of the cerebellum (a topic of neuroscience) is also found, in an even more profound manner, in genomics. The function of the cerebellum as a neuronal machine is to turn the independent, sensory-type motor intentions (that are mathematically covariant) into physically properly assembled motor-execution components (that are mathematically contravariant). This “invention” by mother Nature for the cerebellum is fairly recent in evolution – it only goes back to about 400 million years, when the sharks, equipped with the emerging cerebellum could outswim less coordinated competitors.

Szentágothai, who passed away in 1994, could not have known about “RNA interference” (discovered by Fire and Mello 4 years later, in 1998, to be awarded by Nobel in 2006). “The RNA system acting as a genomic cerebellum” (by both contravariant, cRNA and covariant ncRNA, by their interference comprising the metric of coordinated genome function) is a far more ancient invention about 530 million years ago by mother Nature; it resulted in the so-called “Cambrian explosion” in evolution, by enabling coordinated genome function of multi-cellular organisms.

Our beloved “Grand Old Man” (Prof. Szentágothai) would get truly excited, since he was the epitomy of scientific curiosity and its ultimate reward (understanding) - regardless of the destination of Prizes of any kind, if at all.

János Szentágothai, prof. of Semmelweis University Medical School, Budapest [at right], and András Pellionisz, prof. of New York University Medical School, New York [at left]

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Power in Numbers [math must grab genomics, beneath neuroscience – AJP]

[Eric Lander is right, again. In the video above, essentially he says: For genomics, the homework is to explain cerebellar brain function by its intrinsic math. This is exactly the strategy Tensor Network Theory (applied to Recursive Function of Cerebellar Neural Nets) and its Unification with the Fractal Approach to Genome Function followed. Lander skipped, for a number of reasons, the few decades I invested in “geometrization of neuroscience”– and Lander zoomed right into mathematization of genome (as it is “informatics”). While as a Science Adviser to the President, the US might follow his advice (“Mr. President, the Genome is Fractal!”) because of the inertia of the medical establishment countries with smaller legacy but faster growth in their GDP, plus mobilizing their mathematics-physics-engineering formerly honed to create their own nuclear industry, might even overtake the US in certain segments of “Industrialization of Genomics”. Fortunately, Dr. Lander is also schooled in economics – thus along with fellow Havard Professor economist Dr. Juan Enriquez (see his decade-old-bestseller “As the Future Catches You”) the US can maintain leadership in “Genome Based Economy”. – AJP]

“I took random classes in Harvard about the brain… To know about the brain, you have to learn about cell biology… to know about cell biology you have to learn about molecular biology… I have to know about genetics! “

“I began to appreciate that the career of mathematics is rather monastic,” Dr. Lander said. “Even though mathematics was beautiful and I loved it, I wasn’t a very good monk.” He craved a more social environment, more interactions.

“I found an old professor of mine and said, ‘What can I do that makes some use of my talents?’ ” He ended up at Harvard Business School, teaching managerial economics.

He had never studied the subject, he confesses, but taught himself as he went along. “I learned it faster than the students did,” Dr. Lander said.

Yet at 23, he was growing restless, craving something more challenging. Managerial economics, he recalled, “wasn’t deep enough.”

He spoke to his brother, Arthur, a neurobiologist, who sent him mathematical models of how the cerebellum worked."...

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Paired Ends, Lee Hood, Andras Pellionisz - 2012 a Year of Turing and Year of Turning

January 1st, 2012

[Genomeweb - AJP]

Genomeweb paired us prompted by our respective press releases, signaling the general trend of new global alliances that bridge the USA to Asia. However, as 2012 begins, the Centennary Year of Alan Turing (born in 1912), some deeper analysis may be warranted. This Centennary year closes a decade of fierce struggle. It starting by the passing of Ohno (“Junk DNA” since 1972) in 2000, and Crick in 2004 (“Central Dogma” since 1956), ENCODE’s belated admission in 2007 that “Junk DNA is anything but”, and the Principle of Recursive Genome Function (paper and YouTube in 2008, Unification of Neuroscience and Genomics in print 2012).

This year may become another turning point in mathematical theory of genome function, with great advances in deciphering cancer, see the potential of Full DNA Sequencing (and Analytics) in cancer diagnosis and personalized therapy e.g. in this YouTube by Matthew Ellis (University of Washington in St. Louis).

A Decade ago (2002) both Dr. Hood and I went on our respective records with the notion that “Biology is an Informational Science”; see Lee Hood and Andras Pellionisz.

LeRoy Hood (2002), in his Commemorative Lecture acceptance speech of the Kyoto Prize in Advanced Technologies announced that he was writing a book on “The Living Code: Biology As An Informational Science” assuming Bertalanffy’s “General Systems Theory” (1956, Dover, New York) as his intellectual foundation.

Andras Pellionisz (2002) , for better or worse, specifically pointed out the mathematics intrinsic to genomes with his FractoGene (2002). The “Fractal Approach to DNA” – after the magical 7 years of silencing – is now boosted by the group of Eric Lander (Science Advisor to the President, featuring fractal folding of DNA on Science magazine cover issue, Oct. 2009 based on decades-old pioneering by Alexander Grosberg). Further, a Boston group of four (MIT/Broad/Harvard/Dana-Farber), with Leonid Mirny in both the 2009 paper and now, found in 2011 that “fractal defect” (in their case, a Copy Number Variation, CNV) blocked the see-through transparency of 3D Hilbert-curve, becoming the root cause of cancer.

My personal FractoGene (interlaced with Tensor Network Theory) is a lineage from relativistic tensor geometry brought into a synthesis of the quantum-theory-inspired-Schroedinger school of thought; Schroedinger, “What is Life?”, 1944). I was intellectually imprinted for life by the Hungarian Edition of John von Neumann “The Computer and the Brain” (1958), where on the last page von Neumann posthumously made a visionary statement. Von Neumann was tragically short-lived 1903-1957, quite possibly exposed to nuclear radiation while participating in the Manhattan-project, died of bone cancer. His statement was that whatever the intrinsic mathematics Nature uses in biological systems (notably in brain function) is certainly not the mathematics we know and that he used to create computers.

Perhaps the most revealing article is by Alan Turing, born a Century ago, who published a seminal article well over half a Century ago (1952), before the Double Helix was ever discovered, in 1952 (in Phil. Trans. R. Soc. Lond. B.)

“The Chemical Basis of Morphogenesis”. Its Chapter 13. was entitled “Non-linear theory. Use of Digital Computers”. Aptly, he wrote: “Most of an organism, most of the time, is developing from one pattern into another, rather than from homogeneity into a pattern. One would like to be able to follow this more general process mathematically also. The difficulties are, however, that one cannot hope to have any very embracing theory of such process, beyond the statement of the equations. It might be possible, however, to treat a few particular cases in detail with the aid of a digital computer”.

Neither Ludwig von Bertalanffy (1956), nor John von Neumann (1958) had time enough to specify the math intrinsic to coordinated genome regulation, in spite of early pioneering by Schroedinger (1944) predicting in his essay “What is Life?” that covalent Hydrogen-bondings over an aperiodical crystal (later to be found as DNA Double Helix in 1953), along with other pioneering by Norbert Wiener’s Cybernetics (1949) and the departure from war-time, having deciphered cryptography, to biology by Alan Turing (1952).

In view of the above, it would be grossly unfair to take the credit of a single decade of (2002-2012), despite all turf-protecting-below-the-belt-strikes by the few mathematically unseasoned, for the now prevailing notion that the sine qua non of progress is the software enabling intrinsic algorithm of genome informatics.

I was lucky enough to be exposed at the level of a personal friend to Edward Teller in his late years. Teller was Heisenberg’s Ph.D. student, with relativistic and quantum physics in his weaponry – and I was also inspired by Benoit Mandelbrot’s fractals - Mandelbrot was a Ph.D. student of John von Neumann.

Is the fact that the lineage of concepts of genome informatics has a clear parallel to war-time efforts of Relativity (published in final form in 1916) and quantum theory that made both peaceful (Leo Szilard) and strategic applications of nuclear industry possible (Heisenberg on one side and Turing, Teller, von Neumann, Wiener on the other)?

War-time efforts drained the best minds to lay down the exact (“bullet-proof”) intellectual infrastructure, as if developing an armor capable of deflating all flak, friendly or not. Mathematicians, physicists and nuclear engineers, having served their respective countries, moved in droves from physics to biology.

In 1971, Nixon declared his “War on Cancer”. Now, those whose experise leaves no question that the disease of the genome (with Genomics=Informatics) can only be won with mathematicians, information theorists and most of all, by computers deployed the bolster the infantry of traditional medicine will make sure that the “New War on Cancer”, forty years after the first, will have the needed weaponry developed and ready to use.

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The genetic code, 8-dimensional hypercomplex numbers and dyadic shifts


Sergey V. Petoukhov

Head of Laboratory of Biomechanical System, Mechanical Engineering Research

Institute of the Russian Academy of Sciences, Moscow,,,

[Quarternion fractal from literature. Complex, hypercomplex - or just mathematically lucid? - AJP]

Abstract: Matrix forms of the representation of the multi-level system of molecular-genetic alphabets have revealed algebraic properties of this system. Families of genetic (4*4)- and (8*8)- matrices show an unexpected connections of the genetic system with functions by Rademacher and Walsh and with Hadamard matrices which are well-known in theory of noise-immunity coding and digital communication. Dyadic-shift decompositions of such genetic matrices lead to sets of sparse matrices. Each of these sets is closed in relation to multiplication and defines relevant algebra of hypercomplex numbers. It is shown that genetic Hadamard matrices are identical to matrix representations of Hamilton quaternions and its complexification in the case of unit coordinates. The diversity of known dialects of the genetic code is analyzed from the viewpoint of the genetic algebras. An algebraic analogy with Punnett squares for inherited traits is shown. Our results are discussed taking into account the important role of dyadic shifts, Hadamard matrices, fourth roots of unity, Hamilton quaternions and other hypercomplex numbers in mathematics, informatics, physics, etc. These results testify that living matter possesses a profound algebraic essence. They show new promising ways to develop algebraic biology.

1. Introduction

Science has led to a new understanding of life itself: «Life is a partnership between genes and mathematics» [Stewart, 1999]. But what kind of mathematics is a partner with the genetic code? Trying to find such mathematics, we have turned to study the multi-level system of interrelated molecular-genetic alphabets. On this way we were surprised to find connections of this genetic system with well-known formalisms of the engineering theory of noise-immunity coding: Kronecker products of matrices; orthogonal systems of functions by Rademacher and Walsh; Hadamard matrices; a group of dyadic shifts; hypercomplex number systems, etc. This article is devoted to some of our results of such studing of the phenomenologic system of interrelated genetic alphabets….

Genetic information is transferred by means of discrete elements. General theory of signal processing utilizes the encoding of discrete signals by means of special mathematical matrices and spectral representations of signals to increase reliability and efficiency of information ... A typical example of such matrices is the family of Hadamard matrices. Rows of Hadamard matrices form an orthogonal system of Walsh functions which is used for the spectral representation and transfer of discrete signals… An investigation of structural analogies between digital informatics and genetic informatics is one of the important tasks of modern science in connection with the development of DNA-computers and bioinformatics. The author investigates molecular structures of the system of genetic alphabets by means of matrix methods of discrete signal processing [Petoukhov, 2001, 2005a,b, 2008a-c; Petoukhov, He, 2010, etc.].

The article describes author’s results about relations of matrix forms of representation of the system of genetic alphabets with special systems of 8-dimensional hypercomplex numbers (they differ from the Cayley’s octonions). The discovery of these relationships is significant from some viewpoints. For example, it is interesting because systems of 8-dimensional hypercomplex numbers (first of all, Cayley’s octonions and split-octonions) are one of key objects of mathematical natural sciences today. They relate to a number of exceptional structures in mathematics, among them the exceptional Lie groups; they have applications in many fields such as string theory, special relativity, the supersymmetric quantum mechanics, quantum logic, etc. … The term “octet” is also used frequently in phenomenologic laws of science: the Eightfold way by M.Gell-Mann and Y.Ne’eman (1964) in physics; the octet rule in chemistry… In view of these facts one can think that genetic systems of 8-dimensional numbers will become one of the interesting parts of mathematical natural sciences.

In addition, hypercomplex numbers are widely used in digital signal processing… Formalisms of multi-dimensional vector spaces are one of basic formalisms in digital communication technologies, systems of artificial intelligence, pattern recognition, training of robots, detection of errors in the transmission of information, etc.

Revealed genetic types of hypercomplex numbers can be useful to answer many questions of bioinformatics and to develop new kinds of genetic algorithms. Hadamard matrices and orthogonal systems of Walsh functions are among the most used tools for error-correcting coding information, and for many other applications in digital signal processing …. As noted in the article [Seberry, et al., 2005], many tens of thousands of works are devoted to diverse applications of Hadamard matrices for signal processing. Our discovery of relations of the system of genetic alphabets with the special systems of 4-dimensional and 8-dimensional hypercomplex numbers and with special Hadamard matrices helps to establish the kind of mathematics which is a partner of the molecular-genetic system. Hypercomplex numbers, first of all, Hamilton quaternions and their complexification (biquaternions) are widely applied in theoretical physics. The author shows that matrix genetics reveals a special connection of the system of genetic alphabets with Hamilton quaternions and their complexification. These results give new promising ways to build a bridge between theoretical physics and mathematical biology. They can be considered as a new step to knowledge of a mathematical unity of the nature….

As Hamilton quaternions describe the properties of three-dimensional physical space, the discovery of the connection of the genetic system with Hamilton quaternions attracts our attention to some fundamental questions. It is, for example, the question about innate spatial representations in humans and animals [Russell, 1956; Petoukhov, 1981]. Or the question about a development of physical theories, in which the concept of space is not primary, but derived from more fundamental concepts of special mathematical systems [Kulakov, 2004; Vladimirov, 1998]. The described effectiveness of the algorithm of hidden parameters allows thinking about the systems of hidden parameters as about a possible base for additional development of these theories.

Molecular biology and bioinformatics possess their own problems where Hamilton quaternions and their complexification can be used. For example some approaches are known about algorithmic constructions of fractal patterns in biological structures including fractals in genetic molecules (see [Pellionisz et al, 2011; web]). A development of geometric algorithms for such approaches needs those geometrical operations inside physical 3D-space which are connected with the molecular-genetic system and which can be used as a basis of these geometric algorithms. Hamilton quaternions and their complexifications, which are connected with the system of genetic alphabets and which correspond to geometric properties of our physical space, seem to be promising candidates for this purpose.

Our article shows that now Hamilton quaternions and their complexifications are connected not only with theoretical physics but also with molecular genetics and bioinformatics. The discovery of the relation between the system of molecular-genetic alphabets and Hamilton quaternions together with their complexification provides a bridge between theoretical physics and biology for their mutual enrichment. It can be considered as a next step to discover the mathematical unity of nature.

[Physicists pick up from where Schroedinger left Genome Informatics in 1943 in his essay "What is Life?" - AJP]

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Biophysicists Discover Four New [Fractal - AJP] Rules of DNA 'Grammar'

MIT Technology, December 10, 2010

... Today, Michel Yamagishi at the Applied Bioinformatics Laboratory in Brazil and Roberto Herai at Unicamp in Sao Paulo, say they've discovered several new patterns that significantly broaden the grammar of DNA.

Their approach is straightforward. These guys use set theory to show that Chargaff's existing rules imply the existence of other, higher order patterns.

Here's how. One way to think about the patterns in DNA is to divide up a DNA sequence into words of specific length, k. Chargaff's rules apply to words where k=1, in other words, to single nucleotides.

But what of words with k=2 (eg AA, AC, AG, AT and so on) or k=3 (AAA, AAG, AAC, AAT and so on)? Biochemists call these words oligonucleotides. Set theory implies that the entire sets of these k-words must also obey certain fractal-like patterns.

Yamagishi and Herai distil them into four equations.

Of course, it's only possible to see these patterns in huge DNA datasets. Sure enough, Yamagishi and Herai have number-crunched the DNA sequences of 32 species looking for these new fractal patterns. And they've found them.

They say the patterns show up with great precision in 30 of these species, including humans, e coli and the plant arabidopsis. Only human immunodeficiency virus (HIV) and Xylella fastidiosa 9a5c, a bug that attacks peaches, do not conform.

"These new rules show for the first time that oligonucleotide frequencies do have invariant properties across a large set of genomes," they say.

That could turn out to be extremely useful for assessing the performance of new technologies for sequencing entire genomes at high speed.

One problem with these techniques is knowing how accurately they work. Yamagishi and Herai suggest that a simple test would be to check whether the newly sequenced genomes contain these invariant patterns. If not, then that's a sign the technology may be introducing some kind of bias.

This is a bit like a checksum test for spotting accidental errors in blocks of data and a neat piece of science to boot.

Ref: Chargaff's "Grammar of Biology": New Fractal-like Rules

Chargaff's "Grammar of Biology": New Fractal-like Rules

Michel Eduardo Beleza Yamagishi, Roberto H. Herai

(Submitted on 7 Dec 2011)

Chargaff once said that "I saw before me in dark contours the beginning of a grammar of Biology". In linguistics, "grammar" is the set of natural language rules, but we do not know for sure what Chargaff meant by "grammar" of Biology. Nevertheless, assuming the metaphor, Chargaff himself started a "grammar of Biology" discovering the so called Chargaff's rules. In this work, we further develop his grammar. Using new concepts, we were able to discovery new genomic rules that seem to be invariant across a large set of organisms, and show a fractal-like property, since no matter the scale, the same pattern is observed (self-similarity). We hope that these new invariant genomic rules may be used in different contexts since short read data bias detection to genome assembly quality assessment.


Chargaff once said that “I saw before me in dark contours the beginning of a grammar of

Biology”. In linguistics, “grammar” is the set of natural language rules, but we do not know for

sure what Chargaff meant by "grammar” of Biology. Nevertheless, assuming the metaphor,

Chargaff himself started a “grammar of Biology” discovering the so called Chargaff’s rules. In

this work, we further develop his grammar. Using new concepts, we were able to discovery new

genomic rules that seem to be invariant across a large set of organisms, and show a fractal-like

property, since no matter the scale, the same pattern is observed (self-similarity). We hope that

these new invariant genomic rules may be used in different contexts since short read data bias

detection to genome assembly quality assessment.

[We are soon approaching the phase when everyone will say "Of course, the Genome is Fractal! Why should it be an exception to everything else in Nature?" The invited Springer Handbook Chapter "Recursive Genome Function of the Cerebellum: Unification of Neuroscience and Genomics" (In Press) reviews that looking at the genome as a kind of a "language" (with grammar) goes back to a couple of decades - but could not break through in part because full DNA sequences were not available, and also since the double barrier of the "Central Dogma" and "Junk DNA" misnomer blocked progress for over half a Century. With The Principle of Recursive Genome Function recursive fractal iteration was established as the fundamental algorithm of genome function, and in the "Unification" publication not only the Genomic-Epigenomic (HoloGenomic) system was put in a coherent mathematical framework, but also the "RNA System Serves as the Genomic Cerebellum" concept was put forward. The genome is not only fractal, but the "Coordinated Genome Function" uses the dual (covariant and contravariant) representations of protein production. This entry can be discussed in the FaceBook page of Andras Pellionisz]

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Francis Collins [Head of NIH of the USA in Bangalore, India -AJP].

This US scientist is the director of the National Institute of Health, the country's leading health research establishment. He's in Bangalore to meet top Indian scientists on Saturday and Sunday and shares his outlook on life in this exclusive interview.

What strengths do you see in Indian institutions? How are they compared to China?

India's great strength now is its IT and computational capacity. Biology is now more a computational science. To understand diseases like diabetes and cancer, we need computational strategies to sift through vast datasets. India can provide that asset.

China has strengths too - a long history of genomics research and was into the human genome project earlier than India. India is catching up. But we need the collaboration of all countries on health because everyone everywhere in the world has health problems. Like Louis Pasteur said, science belongs to no one country.

Tell us more about your Bangalore visit...

It's been very exciting. I've been to the National Centre for Biological Sciences, St John's Medical Research College and IISc. At St Johns, I visited the hospital and clinical facilities to get a grasp of research there.

At NCBS, I spoke to students and faculty. The experience was wonderful. The students are bright and inquisitive and we discussed issues ranging from neuroscience to genomics. Clearly, Bangalore is a city that has a thoughtful generation of youngsters out to prove themselves in science. I see a spark in the young people here.

What collaborations are you looking at with institutions here?

We have a collaboration on cancer with India. India is concentrating on mouth cancer as that occurs at a higher frequency here. Then, there's diabetes - a worldwide concern. At St John's, we talked about diabetes and cardiovascular research and the implications for heart disease arising out of diabetes. We're also looking at vaccines, HIV, vision and brain research and technologies we need to develop to tackle these and other chronic diseases.

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Paired Ends: Lee Hood, Andras Pellionisz

Genomeweb, In Sequence

December 06, 2011

a "leader in the field of genome informatics." Pellionisz holds PhD degrees in computer engineering...

People In The News‎

GenomeWeb Daily News - Dec 2, 2011

Elogic Technologies has named Andras Pellionisz to serve on its advisory board. An expert in genome informatics who established the International ...

People In The News‎

GenomeWeb Daily News - 1 day ago

PrimeraDx this week announced that it has appointed Leroy Hood to its scientific advisory board. Hood has helped found several research and commercial ...

[Genomeweb elected to disclose full contents only to subscribers or registered readers. This entry can be discussed on the FaceBook page of Andras Pellionisz]

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ELOGIC Technologies (Bangalore) to launch Genome Analytics Service (See Binet - Genome)

ELOGIC Technologies is proud to present, for the very first time in India, IT Infrastructure Services in Next Generation Sequence (NGS) Analysis and Management on the Cloud Environment, through its BINET (Biological Internet) Division.

ET partners with leading IT MNC’s as a preferred alliance partner in India, to cater to the needs of Genome Informatics for a gradually burgeoning global clientele. ET’s partnership with these MNC’s goes back a decade for providing a range of services and products.

ET is foraying into Life Sciences sector as a whole and will pursue its interests at present in Genome Informatics as a focus area.

Being a forerunner in the arena of Genome Informatics and Data Analysis for NGS on the Cloud, ET is building a team comprising Board of Advisors, experienced Genomics experts, Biology Scientists, Mathematicians and IT Professionals, to provide an array of services in this field as a one-stop-shop for its customers. ET is aiming at providing services in the entire Life-Sciences sector per se, which implies developing software products and algorithms for NGS Analysis.

TD Prakash, Managing Director, ET says – “ET understands the Genome Informatics Landscape in all its entirety and interdisciplinary nature of Biological Sciences, which has occupied the foreground now, with the emergence of new areas in Bio research, such as Genomics, Proteomics and System Biology.

We envision value in building Life Science services with cutting edge technologies and will forge collaboration with global players in NGS area, with the objective of serving the global Life Science industry and related Academia.

In order to ensure that we provide services with complete knowledge and understanding of the field, extra proficiency and authority, ET has engaged with Dr. Andras Pellionisz, a global leader in Genome Informatics from USA, to be a part of our Board of Advisors and we welcome him with much delight on board our advisory team”.

Dr. Pellionisz is the President of HolGenTech, Inc. in Silicon Valley, California, USA and is a thought leader in Fractal Genomics and Hologenomics and will be undertaking the role of the guiding force for ET in this field. He has convinced himself of ET’s domain knowledge, capabilities, business model and growth plans prior to being a part of our Board of Advisors. For more information on our collaboration, please read here a Press Release held in California USA on the 30th November, 2011.

Equipped with the very best of high-end IT know-how and technical expertise, Bangalore is emerging as the epicentre of Biotech - a hub for Genomics and Genome Informatics and is therefore in a unique position to deliver to a world-wide audience, quality services and products in the field of Genome Informatics.

ET is poised to deliver its services to the market by the first quarter of 2012 and will, as a first step, start with executing pilot projects with the Academia. ET will offer services in IT infrastructure to begin with, in Compute Power and Storage followed by NGS Data Analysis Services.

Headquartered in Bangalore, ET has its office in Mumbai and operations in Dubai United Arab Emirates and UK too. Its immediate expansion plans include establishing offices in Chennai and Delhi in India, followed by an office in the Silicon Valley of USA.

With its knowledge of Genomics and its strategic location, ET has at its disposal the means and wherewithal to achieving Data Analysis of Next Generation Sequencing on Cloud.

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DNA Sequencing Caught in Deluge of Data


Published: November 30, 2011

[Added by Pellionisz: In 2008 I warned against this problem in my YouTube. Today, 3 years and 12,744 views later, the NYT describes precisely what was predicted and warned against. The lessons are not analyzed by general media - see my proof of the presently unsustainable path of Genome Sequencing Industry - without the rapid matching of Genome Analytics Industry (stock charts appended). This will emerge (in the USA or elsewhere) once Genome Analytics will be able to tap the vast market of Global Consumers and Global Health Care - this entry can be discussed in the FaceBook of Andras Pellionisz]

BGI, based in China, is the world’s largest genomics research institute, with 167 DNA sequencers producing the equivalent of 2,000 human genomes a day.

BGI churns out so much data that it often cannot transmit its results to clients or collaborators over the Internet or other communications lines because that would take weeks. Instead, it sends computer disks containing the data, via FedEx....

The field of genomics is caught in a data deluge. DNA sequencing is becoming faster and cheaper at a pace far outstripping Moore’s law, which describes the rate at which computing gets faster and cheaper.

The result is that the ability to determine DNA sequences is starting to outrun the ability of researchers to store, transmit and especially to analyze the data.

“Data handling is now the bottleneck,” said David Haussler, director of the center for biomolecular science and engineering at the University of California, Santa Cruz. “It costs more to analyze a genome than to sequence a genome.”

That could delay the day when DNA sequencing is routinely used in medicine. In only a year or two, the cost of determining a person’s complete DNA blueprint is expected to fall below $1,000. But that long-awaited threshold excludes the cost of making sense of that data, which is becoming a bigger part of the total cost as sequencing costs themselves decline.

But the data challenges are also creating opportunities. There is demand for people trained in bioinformatics, the convergence of biology and computing. Numerous bioinformatics companies, like SoftGenetics, DNAStar, DNAnexus and NextBio, have sprung up to offer software and services to help analyze the data. EMC, a maker of data storage equipment, has found life sciences a fertile market for products that handle large amounts of information. BGI is starting a journal, GigaScience, to publish data-heavy life science papers.

“We believe the field of bioinformatics for genetic analysis will be one of the biggest areas of disruptive innovation in life science tools over the next few years,” Isaac Ro, an analyst at Goldman Sachs, wrote in a recent report.

There will probably be 30,000 human genomes sequenced by the end of this year, up from a handful a few years ago, according to the journal Nature. And that number will rise to millions in a few years.

In a few cases, human genomes are being sequenced to help diagnose mysterious rare diseases and treat patients. But most are being sequenced as part of studies. The federally financed Cancer Genome Atlas, for instance, is sequencing the genomes of thousands of tumors and of healthy tissue from the same people, looking for genetic causes of cancer.

One near victim of the data explosion has been a federal online archive of raw sequencing data. The amount stored has more than tripled just since the beginning of the year, reaching 300 trillion DNA bases and taking up nearly 700 trillion bytes of computer memory.

Straining under the load and facing budget constraints, federal officials talked earlier this year about shutting the archive, to the dismay of researchers. It will remain open, but certain big sequencing projects will now have to pay to store their data there.....

“In the life sciences, anyone can produce so much data, and it’s happening in thousands of different labs throughout the world,” he said.

Moreover, DNA is just part of the story. To truly understand biology, researchers are gathering data on the RNA, proteins and chemicals in cells. That data can be even more voluminous than data on genes. And those different types of data have to be integrated. [See an entirely new approach to the "RNA System Acting as a Genomic Cerebellum" In Press - AJP]


Researchers are increasingly turning to cloud computing so they do not have to buy so many of their own computers and disk drives.

Google might help as well.

“Google has enough capacity to do all of genomics in a day,” said Dr. Schatz of Cold Spring Harbor, who is trying to apply Google’s techniques to genomics data. Prodded by Senator Charles E. Schumer, Democrat of New York, Google is exploring cooperation with Cold Spring Harbor.

Google’s venture capital arm recently invested in DNAnexus, a bioinformatics company. DNAnexus and Google plan to host their own copy of the federal sequence archive that had once looked as if it might be closed.


[Stock charts of the dramatic drop of valuation over the last six monts of the four leading DNA Sequencing companies. (Illumina and Life dropped less, since they are NOT "pure play sequencers"). This evidence of the presently unsustainable path of Genome Sequencing - without the rapid ramp-up in the USA or by SAMSUNG (announced Sept. 1. 2011) and/or other global players - has long been directly communicated, and non-standard solutions are emerging - these additions to the NYT description of the mesmerizing symptoms can be discussed on FaceBook of Andras Pellionisz]

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The FDA’s confusing stance on companies that interpret genetic tests is terrible for consumers.

Tell Me What’s in My Genome!

SLATE - By Christopher Mims|Posted Friday, Nov. 25, 2011, at 12:20 AM ET

Right now, for about the same price as a conventional medical test that reveals just a handful of genes, you could learn the entire contents of your genome. Sure, it’s a "research" scan, which means it will contain mistakes, and your insurance won’t cover the $4,000-$5,000 bill. But it won't be more than a few years before a complete and virtually error-free version of your genome will be within financial reach. Wouldn’t you like to unlock your complete instruction set, with all the medical and ancestry data it contains?

Enticing as that may be, it won’t be easy get those keys if the FDA has its way. Last summer, the agency indicated that it wants to classify the work of any company that helps you decipher your genome as a medical test that must be regulated accordingly. But over the last year, the agency’s lack of continued communication has left companies that would interpret genetic information—which are simply offering information—confused as to where they stand. This lack of clarity and direction could ultimately mean ceding leadership in this field to overseas competitors who are not similarly constrained.

The FDA has indicated through its public statements that it will put regulatory barriers in the path of companies that want to help us interpret genomes. In June 2010 the agency sent a series of letters to providers like 23andMe, warning them that they were selling what amounted to medical tests that were not vetted by the FDA, and so were in violation of the law. The FDA’s letter to consumer genetics testing company 23andMe is a good example of the tack the agency is now taking. “23andMe has never submitted information on the analytical or clinical validity of its tests to FDA for clearance or approval. ... Consumers may make medical decisions in reliance on this [genetic] information [provided by 23andMe].”

Since then, the FDA has continued to send out letters of a similar tone—23 in total, all to different companies—but has offered no other guidance to providers of direct-to-consumer genetic tests, leaving these companies, and their investors, in the dark about the ultimate direction of regulation in this area. Frustrated by the delay, in recent months many of these companies have made their responses to the FDA public on their websites, in part to protest the climate of ongoing regulatory uncertainty that the agency’s actions have created. Others have pre-emptively eliminated medically significant interpretations from their tests, even if the genes they return still contain that information.

Rather than protect consumers, the FDA’s move has left the genetic information industry in limbo—and it seems a matter of time before it moves overseas. Can’t get your full genome scan interpreted by software hosted on servers in the United States, owned by a U.S. company? Within a decade, a company in a country not subject to our laws will almost certainly be happy to accommodate you. That’s if you don’t take the do-it-yourself route first, plumbing your genome with free and open-source software linked to Wikipedia-style databases maintained by volunteers (which, because they aren’t sold, aren’t subject to FDA regulation).

It’s difficult, if not impossible, to find legal or medical scholars in the United States who are against patient access to full genome sequences. So where does the FDA’s reticence come from? In part, it’s the long shadow of “genetic exceptionalism”—the idea that “genetic information is inherently unique and should be treated differently in law than other forms of personal or medical information,” as Alan Dow, vice president and legal counsel at Complete Genomics, put it.

Other Western governments, too, have fallen into the genetic exceptionalism trap. In 1997, the European Union’s member states even signed a treaty, the Convention on Human Rights and Biomedicine, which mandates that all signatories apply the precautionary principle when handling biomedical advances like genetic sequencing. This means it’s incumbent upon the advocates of these technologies to prove they won’t do any harm. So, for example, Germany has instituted a law so broad that it basically prevents anyone from getting her own genes sequenced without a doctor’s permission. If the genome-interpreting industry is forced by regulatory limbo to seek shelter outside the United States, we may see developing countries like India compete to fill the market gap.

Based on how we've (mis)used other medical technologies, it’s understandable that governmental bodies are at least a little concerned about the advent of whole-genome sequencing. For example, full-body MRI scans have fed into hypochondria-type fears by flagging benign abnormalities that then have to be further examined. Wouldn't a full-genome scan, with the many disease-contributing genes it turns up, do the same? And won't patients who discover, for example, an elevated chance of an incurable disease have their quality of life adversely affected? We'll get to the details later, but the short answer is no.

Genetic data have to be interpreted in a way that the public might not be accustomed to. But it is elitism of the highest order to imagine that most of us are simpletons who can’t grasp the concept that a gene might contribute to a disease condition, but in no way guarantees it. The fear is that every new study associating a gene with a particular disorder will send patients running to their doctors to ask whether they should be worried. But that seems to be a short-term concern: Most patients will understand the reality after their first (or maybe second) panicked trip to the doctor. The physician will tell them that these studies are always preliminary and that even if they’re borne out by subsequent research, the vast majority of these genes have only a marginal effect on our health.

Studies suggest that even patients who find out they have an elevated risk for a disease with a strong genetic component but no cure—like Alzheimer’s—handle the news quite well. In light of this, it seems like the worst-case scenario for a full genome scan is that a patient might be inspired to actually talk to their doctor about their health. If having genes that suggest an elevated chance of heart disease inspire someone to at least be conscientious about their other risk factors for the disease, great! Preliminary research suggests that results of genetic tests change consumers’ intention to do something about their health, if not their actual behavior. (Consumers’ options about what to do with this information often come down to common lifestyle changes like diet and exercise, which are difficult to get patients to implement under any circumstances.)

The only thing worse than the paternalism keeping genetic data and its implications from consumers is the failure of imagination this represents, in terms of the potential upside of the coming genomic revolution. The more full-genome scans we have, and the cheaper they become, the more useful information patients will have. Widespread genotyping will help us understand our own ancestry, but perhaps more importantly will lead to a new kind of engagement with our health and biology. For this new technology to transform American health—and to cultivate a new, high-tech, high-promise industry within the United States—the FDA needs to provide clarity and guidance. The alternative is that the FDA becomes something like the recording industry at the dawn of the MP3 age: a body trying to lock down immaterial assets that consumers are going to get their hands on, one way or another.

[No Comment - Andras Pellionisz]

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ELOGIC Technologies Private Limited Bangalore, India [Pellionisz unites Silicon Valley-s of USA/India - AJP]

PRWeb, November 30, 2011

Bangalore, India - Genome informatics leader Dr. Andras Pellionisz joins the BoA of the global IT Company to break into Industrialization of Genomics

ELOGIC Technologies Private Limited is a Company Certified for ISO 9001:2008 by BVQI and ISO 27001:2005 for Security by BSI for years now and is in the process of obtaining an ISO: 50001 Certification for Energy Management System. In the business of Secure Information Management and IT Infrastructure Services Delivery, the Company aims at maintaining an uncompromising level of integrity and character to serve its customers, partners, employees and community, building a network of trust along the way. The company is now foraying into Genome Informatics and Next Gen Seq Data Analysis on the public and private clouds.

ELOGIC Technologies announces that Dr. Andras Pellionisz has accepted invitation to join the Advisory Board of ELOGIC Technologies. Dr. Pellionisz is an internationally renowned leader in the field of genome informatics specializing in the geometric unification of neuroscience and genomics. Founder and President of Silicon Valley-based HolGenTech, Inc. in California, he exemplifies the model Andy Grove, senior adviser to Intel, by putting innovation within goal-oriented corporation structure. In his major paper in Springer Handbook (in Press, accepted Nov. 1st 2011) he pairs breakthrough algorithmic development with a blueprint for industrial deployment at a crucial time when the Human Genome Project already impacted the economy by $796 Bn.

“We are delighted to welcome Dr. Andras Pellionisz into our Advisory Board. He brings a wealth of leading edge understanding and global contacts in genome informatics that will be invaluable to ELOGIC Technologies as we edge into this major emerging market,” says TD Prakash, Managing Director and Chairman of the Board of ELOGIC Technologies. "This is the formative decision in the long-term co-operation between USA-Silicon valley HolGenTech, Inc. and ELOGIC Technologies from Bangalore, Silicon valley of India, in the emerging field of genome analytics”, both Dr Pellionisz and Mr. TD Prakash concurred.

“Dr. Pellionisz will be our guiding force for foraying into Data Analysis of Next Gen Sequencing and Management, which we are offering to global clientele by early 2012”, added MV Ramanujam, VP of BINET Division, ELOGIC Technologies.

As a domain expert in Genome Informatics, Dr. Pellionisz is a cross-disciplinary scientist and technologist. With Ph.D.-s in Computer Engineering, Biology and Physics, he has 45 years of experience in Informatics of Neural and Genomic Systems spanning Academia, Government and Silicon Valley Industry. He played a leading role in the shift from artificial intelligence to neural nets, including the establishment of the International Neural Network Society. In 2005, he combined interdisciplinary communities of Genomics and Information Technology when he established the International HoloGenomics Society (IHGS).

Based on sound genome informatics, his work sets forth new mathematical principles for proceeding with full exploration of the whole genome. Dr. Pellionisz’ fractal approach to genome analysis is corroborated by recently published findings about fractal folding of DNA structure by Presidential Science Adviser Eric Lander.

“I am very pleased to join the ELOGIC Technologies Advisory Board. I am convinced that they have the foundation essential for edging into genome informatics. As one who served the “Internet Boom” as Chief Software architect of several Silicon Valley companies, I see and publicly expressed already in 2008 two major differences in the coming much larger boom of Industrialization of Genomics. First, while Internet companies could charge ahead without scientific innovation as packet-switching technology is both man-made and is utterly simple, industrialization of genomics (like nuclear industry) would not only be naive but utterly dangerous without science leadership. Second, while the Internet Boom was essentially centered on Silicon Valley of California, the Genome Boom is already global. I not only realize the cardinal importance of an alliance of Silicon Valley of California with Bangalore, the Silicon Valley of India, but will enjoy building a spectacular success based on global alliance,” says Dr. Pellionisz.

In 1973 Dr. Pellionisz was awarded a Stanford Post Doctoral Fellowship, subsequently he served as Research Professor of Biophysics at New York University Medical Center. Later at NASA Ames Research Center, as a Senior Research Associate of the National Academy. From 1994, he served as Chief Software Architect to several Silicon Valley companies.

About ELOGIC Technologies

ELOGIC Technologies is an IT Enabled Services Company serving a clientele of major multi- national and Government organisations seeking collaboration in the areas of Genome Informatics & Life Sciences, E-Security Services, Productivity Enhancement Solutions, Banking Solutions, Engineering Services and Professional Services Consultancy.

Established in the year 2002, they aim at providing high quality, products and services to achieve customer satisfaction and to be an innovating Company in leading edge technologies.


ELOGIC Technologies Pvt Ltd
Phone : 0091 80 41210 892
Email : mvramanujam(at)elogic(dot)

[Dr. Pellionisz, as Founder and President of his HolGenTech, Inc. in Silicon Valley, California, with his new Board of Adviser role to Elogic Technologies of India's Silicon Valley in Bangalore, builds a global alliance. Dr. Pellionisz also serves as Board of Adviser to DRCcomputer - a hybrid serial/parallel processing hardware integrator of California's Silicon Valley. While the terms of an emerging global alliance are not disclosed, in view of the Boston team just having provided "proof of concept" (see full preview and Nature article two items below in this column, and popular coverage here) to the long-held thesis of Dr. Pellionisz that "fractal defects are root causes of a slew of hereditary syndromes, most notably of cancer" (see at min. 30 of his Google Tech Talk YouTube, 2008), Dr. Pellionisz' major peer-reviewed paper In Press provides hints of a global agenda) - This entry can be discussed on the FaceBook page of Andras Pellionisz]

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The Search for RNAs

November 2011

By Christie Rizk

The creation of new drugs is a vital part of the health-care system. Researchers in academia and in industry are always searching for new ways to combat disease — more efficiently, with fewer toxicities, and less chance of rejection. Until recently, most medicines have been limited to the classic formulation of a small molecule targeting a protein to disrupt its function. But there are many targets and formulations that have yet to be fully exploited, particularly those involving RNAs.

Small interfering RNAs and microRNAs can be used both as targets for drugs and as compounds in drug formulations to disrupt the function of certain genes. By taking advantage of RNA interference, miRNAs and siRNAs can bind to specific messenger RNAs and either increase or decrease their expression to affect how much or how little a given target gene functions. "There are really quite a lot of different methods and cellular pathways that are exploited. In some of them the field is quite old, so you might consider antisense technology a form of RNA therapeutics," says the University of Massachusetts Medical School's Philli