Newsletter of HoloGenomics

Genomics, Epigenomics integrated into Informatics:


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

Any/all IP-related Contact is solely through

Attorney Kevin Roe, Esq. FractoGene Legal Department

155 E Campbell Ave, Campbell, CA 95008

Secured contact to Dr. Pellionisz

regarding Academic, Board, Non-Profit activities:

andras_at_pellionisz_dot_com or cell Four-Zero-Eight - 891- Seven - One - Eight - Seven

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Genome is Fractal? - "Yeah, for sure!"

(Eric Schadt, Double-degree mathematician, Ph.D. in Biomathematics, Sept 15, 2014)

listen here

Mendelspod interview with Eric Schadt, Director of the $600 M Institute of Genomics and Multiscale Biology, NYC (Sept. 15, 2014)

Q [Theral Timpson, Mendelspod]: I have read that you are a Ph.D. in bio-mathematics?

A [Eric Schadt, Ph.D. in bio-mathematics]: Yes, bio-mathematics.

Q: I have recently met a Hungarian-American scientist, András Pellionisz, and he says that we need to bring math into biology and genetics and he says that


Do you buy any of that?

A [Eric Schadt]: YEAH, FOR SURE!

[What is the significance of Eric Schadt' confirmation of FractoGene (the utility derived from fractal genome growing fractal organisms)? Credentials of Eric Schadt, with double-degree mathematician, Ph.D. in bio-mathematics, a sterling record of Merck, Pacific Biosciences and now Director of $600 M "Mount Sinai Institute for Genomics and Multi-scale Biology", plus his non-biased (straight as an arrow academic and personal integrity), would be extremely difficult to beat globally to form an independent professional judgement, based on top-command on both bio-mathematics and information theory & technology. Two times seven years after the Human Genome Project (2000-2007 Encode-I first concluding that "Junk DNA is anything but" and the Central Dogmatism proven to be one of the most harmful mistakes "of the history of molecular biology", followed by the wilderness of 2007-2014. From 2000 to 2014 genomics essentially existed "a new science without valid or even universally agreed upon definitions of theoretical axioms". Characteristically, even Eric Lander heralded globally the "nothing is true of the most important fundamental assumptions" (but put in 2009 the Hilbert-fractal of the genome, just two weeks after George Church invited to his Cold Spring Harbor Meeting Dr. Pellionisz). Detractors had to swallow their (sometimes ugly) words - with the only "alternative theory" of "mathematically solid and software-enabling FractoGene" a random sample of metaphors that "genome regulation is turning genes on and off", or that "the genome is a language" (found not to be true twenty years ago, see Flam 1994).

Eric Schadt's academic endorsement of FractoGene consistently goes back to 2010 (if the theory that fractal genotype is found to be experimentally linked to fractal phenotype, "it would be truly revolutionary"). Well, from 2011 compromised fractal globule has been linked by scores of top-notch independent experimental studies worldwide to cancer, autism, schizophrenia and a slew of auto-immune diseases.

What will the "academic endorsement" result in? First, like in case of Prof. Schadt, leading academic centers are likely to gain intellectual leadership to schools of advanced studies, where non-profit applications (see below already over a thousand) are streamlined by a thought leader of non-linear dynamics as the intrinsic mathematics of living systems. Second, (and IP augmented by trade secrets since last CIP in 2007) is likely to result in a for-profit application-monopoly (in force over the US market till mid-March of 2026)]

[Dr. Pellionisz is legally permitted to practice Compensated Professional Services (Analysis, Advisorship, Consultantship, Board Membership, etc) as long as there is no "Conflict of Interest", through Secured Contact (see above).

Communication regarding Intellectual Property of any kind, including but not limited to patents, trade secrets, know-how associated with Dr. Pellionisz must be strictly gated by "Attorney Kevin Roe, Esq. FractoGene Legal Department" (see above)]

Skip to Most Recent News (2014-2012)






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 !"

"Something like this (disruptions in the fractal structures leading to phenotypic change)" were shown to be true (starting in 2011 November, see top-ranking independent experimentalist's publications, cited below).

"Yeah, of course" - it is now "truly revolutionary".

There are only two question for everyone:

(a) "What is in it for me?"

(b) "What is the deal?"

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

(June 19) GlaxoSmithKline, Searching For Hit Drugs, Pours $95M Into DNA 'Dark Matter'
(June 09) Recurrent somatic mutations in regulatory regions of human cancer genomes (Nature Genetics, dominant author Michael Snyder)
(May 22) Big Data (Stanford): 2015 Nobelist Michael Levitt (multi-scale biology) endorses the Fractal Approach to new school of genomics
(Apr 15) Eric Schadt - Big Data is revealing about the world’s trickiest diseases
(Apr 15) IBM Announces Deals With Apple, Johnson And Johnson, And Medtronic In Bid To Transform Health Care
(Apr 09) An 'evolutionary relic' of the genome causes cancer
(Mar 31) Time Magazine Cover Issue - Closing the Cancer Gap
(Mar 31) We have run out of money - time to start thinking!
(Mar 27) The Genome (both DNA and RNA) is replete with repeats. The question is the mathematics (fractals)
(Mar 21) On the Fractal Design in Human Brain and Nervous Tissue - Losa recognizes FractoGene
(Mar 16) Cracking the code of human life: The Birth of BioInformatics & Computational Genomics
(Feb 26) Future of Genomic Medicine Depends on Sharing Information - Eric Lander to Bangalore
(Feb 25) Genetic Geometry Takes Shape (and it is fractal, see FractoGene by Pellionisz, 2002)
(Feb 19) The $2 Trillion Trilemma of Global Precision Medicine
(Feb 11) BGI Pushing for Analytics
(Feb 10) Who was next to President Obama at the perhaps critical get-together (2011)?
(Feb 03) Round II of "Government vs Private Sector" - or "Is Our Understanding of Genome Regulation Ready for the Dreaded DNA Data Tsunami?"
(Jan 31) Houston, We've Got a Problem!
(Jan 27) Small snippets of genes may have big effect in autism
(Jan 27) Autism genomes add to disorder's mystery
(Jan 27) Hundreds of Millions Sought for Personalized Medicine Initiative
(Jan 22) SAP Teams with ASCO to Fight Cancer
(Jan 15) Human longevity-genentech ink deal sequence thousands genomes
(Jan 13) UCSC Receives $1M Grant from Simons Foundation to Create Human Genetic Variation Map
(Jan 12) Silencing long noncoding RNAs with genome-editing tools with full .pdf
(Jan 08) Who Owns the Biggest Biotech Discovery of the Century?
(Jan 07) NIH grants aim to decipher the language of gene regulation
(Jan 07) End of cancer-genome project prompts rethink: Geneticists debate whether focus should shift from sequencing genomes to analysing function
(Jan 07) Variation in cancer risk among tissues can be explained by the number of stem cell divisions
(Jan 04) Finding the simple patterns in a complex world (Barnsley: "cancers are fractals")
(2015 Jan 02) A fractal geometric model of prostate carcinoma and classes of equivalence
2015 ^
(Dec 26, 2014) The human genome: a multifractal analysis
(Dec 23) 5 Crazy Habits You Might Adopt With Low-Cost Genome Sequencing
(Dec 20) The Dark Corners of Our DNA Hold Clues about Disease
(Dec 19) Roche Acquires Bina Technologies’ Powerful Genome Analysis Platform
(Dec 14) Experts expose fundamental role of chaos and complexity in biological information processing (Genome is a Fractal/Chaotic System governed by nonlinear dynamics [AJP])
(Dec 04) Craig Venter on How the Genomic Era Is Just Starting
(Nov 15) Cancer Genomics: Complexity is in the Eye of the Bewildered
(Nov 07) Exponential Medicine by Singularity University - San Diego, 2014
(Nov 01) TIME Magazine 2003 Summit versus 2014 Special Issue
(Oct 26) Ovarian cancer oncogene found in 'junk DNA'
(Oct 23) Priority Health Becomes First Health Plan to Cover Foundation Medicine's Tests
(Oct 20) ASHG: Data Science to Help Genomics Move from 'Artisanal' to 'Factory' (Google? IBM? Apple? GE Health? Microsoft? ... or Fast and Furious?)
(Oct 10) Mount Sinai Opens New Genomics Lab (in Brentwood, Connecticut) with Bank of Ion Torrent Sequencers
(Sep 15) NCI, NVIDIA Providing $2M for Omics-based Cancer Data Research
(Sep 12) Fractal Genome yields 389,000 hits - here is a list of over a thousand FRACTAL items in PubMed
(Sep 11) 23andMe aims to be Google for genetic research
(Sep 10) Mayo Clinic, IBM Collaborate to Match Patients with Clinical Trials
(Sep 06) Venter steals top scholar from Google
(Sep 06) End of Summer - Beginning of a New Era
(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

For archived HoloGenomics News articles see Archives above

GlaxoSmithKline, Searching For Hit Drugs, Pours $95M Into DNA 'Dark Matter'

GlaxoSmithKline wants to better understand biology so it can discover more medicines, like every other drugmaker. It also wants to quit wasting money on drug candidates that look promising in the lab, but flop years later when given to hundreds or thousands of real people.

Today, London-based GSK is betting that one way around the problem will come from “the living genome” or what some call the “dark matter” of the genome. These mysterious stretches in the genetic instructions don’t contain genes that provide code for making proteins, but they do appear to provide important controls over what genes do in different cells, in different states of health and disease, and in response to different environments.

Rather than invest in its own labs which have been downsized and re-organized in many ways, GSK is investing $95 million over the next five years, and potentially that amount and more over the subsequent five years, in a new nonprofit research center in Seattle called the Altius Institute for Biomedical Sciences. The institute, which stands for “higher” in Latin, is led by John Stamatoyannopoulos, a professor of genome sciences at the University of Washington. He was a leader in the international ENCODE consortium that published a batch of influential papers in the journal Nature in 2012. The findings elevated the importance of regulatory regions in the genome, and even raised some thoughtful questions about the basic definition of a “gene.”

Stam, as he is known for short, will lead a team of 40-80 molecular biologists, chemists, and computer scientists who will seek to find meaning in regions of the genome that control what they call “the cell’s operating system.” GSK is hoping that this understanding of gene control will help it find better molecular targets for drugs, and help it select the right compounds, right doses, target tissues, and all kinds of other aspects critical in drug R&D.

While the breathtaking advances in faster/cheaper DNA sequencing are making it possible to compare genomes from many people to look for differences that play a role in wellness and disease, Altius isn’t focused so much on the underlying sequences on their own. It will not set up a factory-style efficient genome sequencing center—it will contract that work out to others. The Altius group plans to use, and continuously improve technologies around imaging, chemistry, and computation to extract meaningful information from what Stamatoyannopoulos calls “the living genome.”

“The problem is that the genome only encodes some upstream potentiality, and doesn’t read out what the organism is actually doing,” Stamatoyannopoulos said. “It’s packaged in different ways in different cells…we are reading how the cell is working, and using the genome as a scaffold for all the things it does.” Looking at the downstream manifestation of the genome, in cells, he said, “is going to be much more relevant to clinical medicine.”

Lon Cardon, a senior vice president of alternative discovery and development at GlaxoSmithKline, said he and his team were fascinated by the ENCODE consortium’s series of publications starting in September 2012. “The light went on for us,” he said. Historically, pharma has looked at molecular targets as “static” entities, when the reality is much more fluid and dynamic in different cell and tissue types. Better understanding of what the targets are doing in live cells is essential to fundamental R&D challenges, Cardon said.

At the time of the ENCODE team’s public pronouncements, genomics leader Eric Lander at the Broad Institute likened it to Google GOOGLE Maps. The earlier Human Genome Project, he told The New York Times, “was like getting a picture of Earth from space. It doesn’t tell you where the roads are, it doesn’t tell you what traffic is like at what time of the day, it doesn’t tell you where the good restaurants are, or the hospitals or the cities or the rivers.” He called ENCODE a “stunning resource.”

The scientific consortium has continued to march ahead the past several years, but opinions are mixed on whether regulatory regions of the genome are ready for prime time in drug discovery.

“The maps being created from these efforts are absolutely helping lock into cell specific regulatory networks that when combined with methylation data and eQTL [expression quantitative trait loci] data can be very powerful in tuning you into causal regulators that are important for disease,” said Eric Schadt, the director of the Icahn Institute for Genomics and Multiscale Biology in New York.

David Grainger, a partner at Index Ventures in London, said, “John Stam clearly has a record of doing exciting stuff, and I’m sure he will do so again in Altius. Whether any of that will translate into value for a drug developer, only time will tell. Genomics and the control of gene expression would not necessarily have been an area I would have chosen for what is, in effect, company-funded blue skies research. But I look forward to them proving me wrong.”

GSK, like its industry peers, has been experimenting not just with different scientific approaches to discovery, but with various models for financing creative, motivated teams outside of its own walls. It has a corporate venture capital fund (SR One) that invests in biotech startups, a tight relationship with a venture firm (Avalon Ventures) that builds startups it might buy, and it tried (and closed) a number of internal centers for excellence. The idea of a big drug company putting big resources behind a semi-independent nonprofit institute isn’t exactly new—Merck & Co. did something similar in 2012 when it enlisted Peter Schultz to run the California Institute for Biomedical Research in San Diego.

In the past, pharma companies might have just written a check to sponsor research at an academic center like the University of Washington, sit back, and hope for good results to flow back to the company. But those arrangements haven’t borne much fruit. GSK could have just acquired as much of the intellectual property and technology as it could, and brought it in-house, but it was afraid that it might slow things down in a fast-moving field, Cardon said. In all likelihood, it will be easier to recruit the people it wants into a new organization with startup-like focus and urgency. Speed is of the essence in a field going through exponential advances in technology. “We want to stay ahead of that game,” Stamatoyannopoulos said.

While staying small and nimble, the institute will get some big company advantages. Altius will be able to use some of GSK’s fancy instruments, like imaging, chemistry, and robotics tools that it couldn’t possibly corral in an academic institution.

The institute and the company expect to have what sounds like an open-door relationship. Some GSK scientists will be able to go on periodic leaves from their regular job to go work at the Seattle institute, taking what they learn back to the mother ship. Scientists at the institute say they have retained their academic freedom, in the right to publish all of their discoveries without prior review of GlaxoSmithKline, with one exception–when the work applies to proprietary compounds of the parent company.

Clearly, GSK is hoping for a return on its investment. The company is getting the first shot at licensing discoveries from Altius, and the right to spin companies out of it. The knowledge from Altius, ideally, should influence decision-making with a number of its experimental drugs.

The new center is expected to get up and running later this year in offices just north of Seattle’s famed Pike Place Market. Stamatoyannopoulos said he will retain his faculty position at the UW Genome Sciences department, and continue to oversee grant work he has there, including some of the ENCODE consortium efforts. The institute will have its own board of directors, and its own scientific advisory board, but it isn’t yet naming names or even saying how many members will be in each group. The agreement between the institute and the company covers a 10-year term, with $95 million of company support for the basic science and technology exploratory phase in the first 5 years and with additional funding in the latter years for specific drug discovery/development projects. The second half of the collaboration is expected to provide funding on par with first five years, but could be even bigger, Stamatoyannopoulos said.

Incidentally, Stamatoyannopoulos said he and his team don’t use the “dark matter” analogy anymore when describing their work on the regulatory regions of the genome, mainly because they have shed light on where that regulatory DNA is. But there’s still plenty of mystery. “There of course is an enormous amount to learn–but now we have the flashlights and searchbeams,” Stamatoyannopoulos said in an e-mail. “I usually use ‘living genome’ to distinguish from research that focuses just on DNA sequence (the ‘dead genome’), which doesn’t change, while the cell’s regulatory network does back flips in response to its environment or a drug.”

Luke Timmerman is the founder and editor of Timmerman Report, a subscription publication for biotech insiders.

[Comment will be added - andras_at_pellionisz_dot_com]

Recurrent somatic mutations in regulatory regions of human cancer genomes (Nature Genetics, dominant author Michael Snyder)

[Popular journalist coverage:

Stanford Team IDs Recurrently Mutated Regulatory Sites Across Cancer Types

Jun 08, 2015 | a GenomeWeb staff reporter]

To identify the regulatory mutations, Mike Snyder's laboratory at Stanford first established an analysis workflow for whole-genome data from 436 individuals from the TCGA. They used two algorithms, MuTect and VarScan 2, to identify SNVs from eight different cancer subtypes.

Next, they annotated the mutation set with gene and regulatory information from the gene annotation project Gencode and RegulomeDB, a database of regulatory data that includes data on transcription factors, epigenetic marks, motifs, and DNA accessibility.

Overall, they found that mutations in coding exons represented between .036 percent and .056 percent of called mutations for each cancer type, while mutations in putative regulatory regions represented between 31 percent and 39 percent of called mutations for each cancer type. The large fraction of regulatory mutations, "underscores the potential for regulatory dysfunction in cancer," the authors wrote.

The team identified a number of recurrently mutated genes and regulatory regions, and they replicated a number of known findings of recurrent mutations in driver genes, including mutations in the coding regions of TP53, AKT1, PIK3CA, PTEN, EGFR, CDKN2A, and KRAS.

They also identified recurrent mutations to the known TERT promoter gene and recurrent mutations in eight new loci in proximity of, and therefore potential regulators of, known cancer genes, including GNAS, INPP4B, MAP2K2, BCL11B, NEDD4L, ANKRD11, TRPM2 and P2RY8.

In addition, they found positive selection for mutations in transcription factor binding sites. For instance, mutations in the binding sites of CEBP factors were "enriched and significant across all cancer types," the authors wrote. In addition, they found enrichment for mutations in transcription factor binding sites that were either likely to "destroy the site or increase affinity of the site for transcription factor binding," the authors wrote. Such mutations could either inactive tumor suppressor genes or activate oncogenes.

"Overall, we expect that many regulatory regions will prove to have important roles in cancer, and the approaches and information employed in this study thus represent a significant advance in the analysis of such regions," the authors wrote.


ABSTRACT OF ORIGINAL PAPER: Aberrant regulation of gene expression in cancer can promote survival and proliferation of cancer cells. Here we integrate whole-genome sequencing data from The Cancer Genome Atlas (TCGA) for 436 patients from 8 cancer subtypes with ENCODE and other regulatory annotations to identify point mutations in regulatory regions. We find evidence for positive selection of mutations in transcription factor binding sites, consistent with these sites regulating important cancer cell functions. Using a new method that adjusts for sample- and genomic locus–specific mutation rates, we identify recurrently mutated sites across individuals with cancer. Mutated regulatory sites include known sites in the TERT promoter and many new sites, including a subset in proximity to cancer-related genes. In reporter assays, two new sites display decreased enhancer activity upon mutation. These data demonstrate that many regulatory regions contain mutations under selective pressure and suggest a greater role for regulatory mutations in cancer than previously appreciated.

["Seven years of hesitation" is famous in science. So is for The Principle of Recursive Genome Function (Pellionisz 2008) and the illustration of (fractal) recursive misregulation as the basis of cancer (Pellionisz Google Tech YouTube, 2008). The double paradigm-shift (reversal of both axioms of Old School Genomics) is now validated by first class, independent experimental results. While the Principle of Recursive Genome Function is not widely quoted after 7 years, Dr. Snyder et al. (2007) was among the first pioneers to go on record abolut the need of re-definition of genes and genome function. Now, with clear evidence that intergenic and even intronic non-coding sequences, in a recursive mode are responsible for the most dreaded genome regulation disease (cancer), it seems difficult to find alternative comprehensive theoretical framework for genome (mis)regulation. Andras_at_Pellionisz_dot_com]

Big Data (Stanford) 2015: Nobelist Michael Levitt (multi-scale biology) endorses the Fractal Approach to new school of genomics

Big Data at Stanford (2015) leveled the field of post-ENCODE genomics. On one hand, the insatiable demand for dwindling resources to generate Big (and Bigger) Data clearly ran into financial and data-privacy constraints. This was rather clear from presentations by NIH (putting the $200 M nose of the camel into the $2 Trillion "Precision Medicine Initiative" by sequencing AND interpreting the full DNA of up to 2 million humans, with 1 million people by the government's effort, a questionably overlapping another 1 million by an alternative private effort). In some rather sharp contrast, NSF answered a question if it leaves paradigm-shift genomic R&D to either strategic DARPA projects or for the Private Sector, could refer to a $28 M NSF program ("INSPIRE") that seems insufficient and rather hard even to qualify for. On the other hand, several start-up companies showed up (e.g. DNA Nexus, Seven Bridges, SolveBio, YouGenix - one CEO is a new member of the International Hologenomics Society), all eager to ramp-up their genome interpretation business much quicker than the already committed Big IT (Google Genomics, Amazon Web Services, IBM-Watson, Samsung, Sony, Apple, Siemens, SAP etc). In the forefront are, therefore key algorithms (just as "search engine algorithms" determined in the Age of Internet which company will emerge as a leader). From this viewpoint, it may be remarkable that FractoGene, already on record with no opposition by Nobelist Jim Watson upon presentation in Cold Spring Harbor, 2009, and already enjoying repeated support by "multi-scale biologist" Eric Schadt, at Big Data 2015 was endorsed by Nobelist Michael Levitt (Stanford, "multi-scale biology"). Dr. Levitt provided an unsolicited public endorsement as a "very good idea".

Eric Schadt - Big Data is revealing about the world’s trickiest diseases

Technically Brooklyn

April 16, 2015

If you learned about cystic fibrosis during biology class in high school, it was probably described as an inevitable condition of those whose genes included a specific set of mutations. It was thought to be inevitable because no one had ever found anyone with those mutations that didn’t have it. On the other hand, no one was checking people’s genes to see if they had the mutations when they didn’t show symptoms.

During the 2015 Lynford Lecture at NYU Poly, Mt. Sinai Hospital’s Eric Schadt explained how a big data methodology revealed a remarkable truth: When scientists look at large sets of genomic data of broad pools of test patients, they find small numbers of people with the genetic markers that would make them genetically predisposed to various diseases, and yet they weren’t symptomatic.

The remarkable finding here is that genetics do not necessarily represent an individual’s fate and somehow these individuals’ bodies worked out ways around their genetic disadvantages.

Schadt refers to these people as “heroes” and he believes that by studying them the medical profession can find new strategies of care for patients who are symptomatic.

Schadt is the director of the Icahn Institute for Genomics and Multiscale Biology, among other appointments, at Mt. Sinai. His talk served both as an exploration of a data-driven approach to determining strategies of care, an argument for a network-oriented approach to determining multiple interventions against disease as well as an argument for encouraging non-expert investigation of biological problems.

For this latter point, we have the example of Suneris, a company whose completely novel approach to stopping bleeding was discovered by a college freshman, not a doctor.

Here are some other compelling points from Schadt’s talk:

Bias. A huge stumbling block in the healthcare system is the bias toward acute care. Acute care is treating problems. That’s what hospitals are set up to treat and that’s what they get paid the best to deal with. It is not, however, what is best for patients.

Lots of apps, lots of data. A lot of data is getting collected by something like 50,000-100,000 mobile apps that in one way or another relate to health. With all this data, it’s possible to start getting very serious about targeted, specific prevention strategies for individuals that treat them as a whole person.

Locus of power. In 5-10 years time, there will be far more data about your health outside of medical centers than inside them.

Massive new studies powered by apps. Mt. Sinai just launched an app in collaboration with Apple to study asthma sufferers and help them manage their condition as they did so. It’s in the App Store. Within six hours of announcing it with Tim Cook, Mt. Sinai had enrolled several thousand people, a number that would take traditional studies years to achieve.

Informed consent. Schadt called the informed consent process built into the app its “crowning achievement.” Subsequent testing showed that users who went through their informed consent dialogue understood what they were agreeing to better than people who went through an informed consent process with another person.

Data yields surprises. By building a complete model based on multiple networks and developing it to the point that they were able model how different genes might express themselves under different conditions and different treatments, Mt. Sinai scientists were able to find a drug that was indicated for a wildly other use relating to irritable bowel syndrome. Big data makes it possible to find treatments by just running different inputs through models, regardless of indication or researcher assumptions.

[Eric Schadt is a double-degree mathematician, with Ph.D. in Biomathematics from UCLA. Started to turn "Big Pharma" (Merck) towards Information Technology. Later became the Chief Scientist of the Silicon Valley genome sequencing company Pacific Biosciences, to interpret genome information. In 30 minute compute time identified Haiti epidemic strain. With $600 M, established the Mount Sinai Center of Genomics and Multiscale Biology in Manhattan. Moved North to suburb (454), now lectured in Brooklyn. The almost 2 hour long video could be a Ph.D. thesis on the challenges of the sick-to-health-care IT-led paradigm shift. Not only abandons obsolete "gene/junk" dogma, but now also considers obsolete the "pathways" concept. Strong supporter of the fractal approach - expected to analyze parallel self-similar recursions. There are too many highly relevant comments in Eric's lecture. Suffice to mention that in BGI (China) for every single genome analyzer there are about 50 (fifty) software developers. In the USA this number is 1-3 (about twenty times less). Another bullet-point mentions that very soon there will be a lot more health-data OUTSIDE, not within the hospitals. As an NYU Medical Center professor, I can state with some authority that such "data center" will not be in Manhattan (real estate is way too expensive). Likewise, in the article below (IBM-Apple), in Silicon Valley it is actually very easy to tell where it will be located (hint: I have worked for some years as a Senior Research Council Advisor of the National Academy to NASA Ames Research Center. "Next door" is one of the busiest Internet-hub...) andras_at_pellionisz_dot_com]

IBM Announces Deals With Apple, Johnson And Johnson, And Medtronic In Bid To Transform Health Care

IBM Almaden Research Center, Silicon Valley, California

Apple Second Campus, Silicon Valley

Forbes, April 15, 2015

Experts in health care and information technology agree on the future’s biggest opportunity: the creation of a new computational model that will link together all of the massive computers that now hold medical information. The question remains: who will build it, and how?

IBM IBM -0.61% is today staking its claim to be a major player in creating that cloud, and to use its Watson artificial intelligence – the one that won on the TV game show Jeopardy – to make sense of the flood of medical data that will result. The new effort uses new, innovative systems to keep data secure, IBM executives say, even while allowing software to use them remotely.

“We are convinced that by the size and scale of what we’re doing we can transform this industry,” says John Kelley, Senior Vice President, IBM Research. “I’m convinced that now is the time.”

Big Blue is certainly putting some muscle into medicine. Some 2,000 employees will be involved in a new Watson-in-medicine business unit. The Armonk, N.Y.-based computing giant is making two acquisitions, too, buying Cleveland’s Explorys, an analytics company that has access to 50 million medical records from U.S. patients, and Dallas’ Phytel, a healthcare services head of IBM’s Life Science company that provides feedback to doctors and patients for follow-up care. Deal prices were not disclosed.

It is also announcing some big partnerships:

• Apple AAPL -0.47% will work to integrate Watson-based apps into its HealthKit and ResearchKit tool systems for developers, which allow the collection of personal health data and the use of such data in clinical trials.

• Johnson & Johnson JNJ -0.81%, which is one of the largest makers of knee and hip implants, will use Watson to create a personal concierge service to prepare patients for knee surgery and to help them deal with its after effects.

• Medtronic MDT -1.14%, the maker of implantable heart devices and diabetes products, will use Watson to create an “internet of things” around its medical gadgets, collecting data both for patients’ personal use and, once it’s anonymized, for understanding how well the devices are working. Initially, the focus is on diabetes.

IBM’s pitch is that it will be able to create a new middle layer in the health care system – linking the old electronic records systems, some of which have components dating back to the 1970s, with a new, cloud-based architecture, because of its deep breadth of experience.

And there is no doubt that there is a need for data science that can parse the explosion of information that will soon be created by every patient. Already, there is too much information for the human brain. “If you’re an oncologist there are 170,000 clinical trials going on in the world every year,” says Steve Gold, VP, IBM Watson.

The question is how ready Watson is to take on the challenge. IBM isn’t the only one that sees opportunity here. The billionaire Patrick Soon-Shiong is aiming to create a system to do many of the same things with his NantHealth startup. Flatiron Health, a hot startup in New York, is creating analytics for cancer. The existing health IT giants, Cerner and Epic, both certainly have their eyes on trying to capture some of this new, interconnected market, lest it make them obsolete.

So far, Watson has been a black box when it comes to healthcare. IBM has announced collaborations with Anthem, the health insurer, and medical centers including M.D. Anderson, Memorial Sloan-Kettering Cancer Center, and The Cleveland Clinic. There are lots of positive anecdotal reports, but so far the major published paper from Watson is a computer science paper published by the Baylor College of Medicine that identified proteins that could be useful drug targets.

“I think that ultimately somebody’s going to figure out how to integrate all these sources of data, analyze them, sort the signal to noise, and when someone can do that, it will improve the health care system,” says Robert Wachter, the author of The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age and associate chair of medicine UCSF.

“Does this do that tomorrow? No. But do we need to create the infrastructure to do that? Yes. And are they probably the best-positioned company with the best track record to do this? I think so.”

–Sarah Hedgecock contributed reporting to this story.

[This is a global "game changer", since what I predicted over a decade ago now actually happened. It is "news" but not a "surprise". IBM has long targeted the "health care" traditional market, but with genomics, it was Google Genomics, Amazon Genomics and IBM cloud-genomics that prepared for changing, by means of Information Technology, the $2 Trillion (USA) "IT matters for your health". The IBM announcement includes Apple (informally), but all others, plus global IT companies like Samsung, Sony, Panasonic, BGI, Siemens, SAP (etc) are also in the ring. Information Technology, however, is not even the hardest challenge (see my 2008 YouTube, Information Theory is the bottleneck). As for IT1 (Information Technology), it appears that "multicore" (beyond 128) is not the way to go - "cloud computing" is the name of the game today. However, for instance IBM Research at Almaden (Silicon Valley) points out, the "techie-challenge" is far deeper; it is the "non-von-Neumann computing architecture" (with their prototype SYNAPSE-chip, with over a million neurons and gezillion connections among them, to learn e.g. pattern recognition by neural net algorithms - with power consumption an order of magnitude smaller than what a smart phone battery provides). Science-wise (minus the chip) such a neuronal network model was built a generation ago. As the above long lecture by Eric Schadt shows, however, the gap between the "medical establishment" and the "genome informatics specialists" is visibly stunning. - andras_at_pellionisz_dot_com]

An 'evolutionary relic' of the genome causes cancer

Pseudogenes, a sub-class of long non-coding RNA (lncRNA) that developed from the genome's 20,000 protein-coding genes but lost the ability to produce proteins, have long been considered nothing more than genomic "junk." Yet the retention of these 20,000 mysterious remnants during evolution has suggested that they may in fact possess biological functions and contribute to the development of disease.

Now, a team led by investigators in the Cancer Research Institute at Beth Israel Deaconess Medical Center (BIDMC) has provided some of the first evidence that one of these non-coding "evolutionary relics" actually has a role in causing cancer.

In a new study in the journal Cell, publishing online today, the scientists report that independent of any other mutations, abnormal amounts of the BRAF pseudogene led to the development of an aggressive lymphoma-like disease in a mouse model, a discovery that suggests that pseudogenes may play a primary role in a variety of diseases. Importantly, the new discovery also suggests that with the addition of this vast "dark matter" the functional genome could be tremendously larger than previously thought - triple or quadruple its current known size.

"Our mouse model of the BRAF pseudogene developed cancer as rapidly and aggressively as it would if you were to express the protein-coding BRAF oncogene," explains senior author Pier Paolo Pandolfi, MD, PhD, Director of the Cancer Center and co-founder of the Institute for RNA Medicine (iRM) at BIDMC and George C. Reisman Professor of Medicine at Harvard Medical School. "It's remarkable that this very aggressive phenotype, resembling human diffuse large B-cell lymphoma, was driven by a piece of so-called 'junk RNA.' As attention turns to precision medicine and the tremendous promise of targeted cancer therapies, all of this vast non-coding material needs to be taken into account. In the past, we have found non-coding RNA to be overexpressed, or misexpressed, but because no one knew what to do with this information it was swept under the carpet. Now we can see that it plays a vital role. We have to study this material, we have to sequence it and we have to take advantage of the tremendous opportunity that it offers for cancer therapy."

The new discovery hinges on the concept of competing endogenous RNAs (ceRNA), a functional capability for pseudogenes first described by Pandolfi almost five years ago when his laboratory discovered that pseudogenes and other noncoding RNAs could act as "decoys" to divert and sequester tiny pieces of RNA known as microRNAs away from their protein-coding counterparts to regulate gene expression.

"Our discovery of these 'decoys' revealed a novel new role for messenger RNA, demonstrating that beyond serving as a genetic intermediary in the protein-making process, messenger RNAs could actually regulate expression of one another through this sophisticated new ceRNA 'language,'" says Pandolfi. The team demonstrated in cell culture experiments that when microRNAs were hindered in fulfilling their regulatory function by these microRNA decoys there could be severe consequences, including making cancer cells more aggressive.

In this new paper, the authors wanted to determine if this same ceRNA "cross talk" took place in a living organism—and if it would result in similar consequences.

"We conducted a proof-of-principle experiment using the BRAF pseudogene," explains first author Florian Karreth, PhD, who conducted this work as a postdoctoral fellow in the Pandolfi laboratory. "We investigated whether this pseudogene exerts critical functions in the context of a whole organism and whether its disruption contributes to the development of disease." The investigators focused on the BRAF pseudogene because of its potential ability to regulate the levels of the BRAF protein, a well-known proto-oncogene linked to numerous types of cancer. In addition, says Karreth, the BRAF pseudogene is known to exist in both humans and mice.

The investigators began by testing the BRAF pseudogene in tissue culture. Their findings demonstrated that when overexpressed, the pseudogene did indeed operate as a microRNA decoy that increased the amounts of the BRAF protein. This, in turn, stimulated the MAP-kinase signaling cascade, a pathway through which the BRAF protein controls cell proliferation, differentiation and survival and which is commonly found to be hyperactive in cancer.

When the team went on to create a mouse model in which the BRAF pseudogene was overexpressed they found that the mice developed an aggressive lymphoma-like cancer. "This cancer of B-lymphocytes manifested primarily in the spleens of the animals but also infiltrated other organs including the kidneys and liver," explains Karreth. "We were particularly surprised by the development of such a dramatic phenotype in response to BRAF pseudogene overexpression alone since the development of full-blown cancer usually requires two or more mutational events."

Similar to their findings in their cell culture experiments, the investigators found that the mice overexpressing the BRAF pseudogene displayed higher levels of the BRAF protein and hyperactivation of the MAP kinase pathway, which suggests that this axis is indeed critical to cancer development. They confirmed this by inhibiting the MAP kinase pathway with a drug that dramatically reduced the ability of cancer cells to infiltrate the liver in transplantation experiments.

The Pandolfi team further validated the microRNA decoy function of the BRAF pseudogene by creating two additional transgenic mice, one overexpressing the front half of the BRAF pseudogene, the other overexpressing the back half. Both of these mouse models developed the same lymphoma phenotype as the mice overexpressing the full-length pseudogene, a result which the authors describe as "absolutely astonishing."

"We never expected that portions of the BRAF pseudogene could elicit a phenotype and when both front and back halves induced lymphomas, we were certain the BRAF pseudogene was functioning as a microRNA decoy," says Karreth.

The investigators also found that the BRAF pseudogene is overexpressed in human B-cell lymphomas and that the genomic region containing the BRAF pseudogene is commonly amplified in a variety of human cancers, indicating that the findings in the mouse are of relevance to human cancer development. Moreover, say the authors, silencing of the BRAF pseudogene in human cancer cell lines that expressed higher levels led to reduced cell proliferation, a finding that highlights the importance of the pseudogene in these cancers and suggests that a therapy that reduces BRAF pseudogene levels may be beneficial to cancer patients.

"While we have been busy focusing on the genome's 20,000 coding genes, we have neglected perhaps as many as 100,000 noncoding genetic units," says Pandolfi. "Our new findings not only tell us that we need to characterize the role of all of these non-coding pseudogenes in cancer, but, more urgently, suggest that we need to increase our understanding of the non-coding 'junk' of the genome and incorporate this information into our personalized medicine assays. The game has to start now—we have to sequence and analyze the genome and the RNA transcripts from the non-coding space."

[The game had started at least by 2002 (13 years ago), when FractoGene was submitted, but is ready now with key IP (8,280,641 in force with Trade Secrets to improve Best Methods as of the last CIP in 2007 - that is 8 years ago. andras_at_pellionisz_dot_com]

[What is the equivalent to the "Flat Earth Society" in the "Junk DNA Upholding Blogspace", grave concern about their untenable dogma is quite revealing. While unable to identify the proper DOI there, question is raised if the press release represents the views of the authors. For those behind paywall, here is a verbatim paragraph from the paper [AJP]:]

"Pseudogenes were considered genomic junk for decades, but their retention during evolution argues that they may possess important functions and that their deregulation could contribute to the development of disease. Indeed, several lines of evidence have associated pseudogenes with cellular transformation (Poliseno, 2012). Our study shows that aberrant expression of a pseudogene causes cancer, thus vastly expanding the number of genes that may be involved in this disease. Moreover, our work emphasizes the functional importance of the non-coding dimension of the transcriptome and should stimulate further studies of the role of pseudogenes in the development of disease."

Time Magazine Cover Issue - Closing the Cancer Gap

[We are beyond "the point of no return". As is widely known, potent (and expensive) cancer therapies might be next to ineffective for one person with cancer medically characterized as the same as in the other person (for whom the same therapy could be dramatically effective). The emerging "precision medicine" in cancer already reached "the point of no return". The Time Magazine Cover Story does not qualify as "good news or bad news" its box "Less than 5% of the 1.6 million Americans diagnosed with cancer each year can take advantage of genetic testing" - it clearly indicates to me that 5% is actually "a point of no return". Granted that reimbursed for genomic testing by some insurance companies is "a struggle" and the 5% percentage is unquestionably low, the wide dissemination e.g. by Time Magazine (also with its title) shows that there is no other way to go, and the question is a matter of realization by the public that "science delivers" - of course with proper time/money allocation. The news above (on non-coding "pseudogenes" - by dogmatics held way too long as "junk DNA for the purpose of doing nothing" (Ohno, 1972) - as a lid is also blown away. andras_at_pellionisz_doc_com]

We have run out of money - time to start thinking!

Dr. Harold Varmus to Step Down as NCI Director

A Letter to the NCI Community

March 4, 2015

To NCI staff, grantees, and advisors:

I am writing to let you know that I sent a letter today to President Obama, informing him that I plan to leave the Directorship of the National Cancer Institute at the end of this month.

I take this step with a mixture of regret and anticipation. Regret, because I will miss this job and my working relationships with so many dedicated and talented people. Anticipation, because I look forward to new opportunities to pursue scientific work in the city, New York, that I continue to call home.

The nearly five years in which I have served as NCI Director have not been easy ones for managing this large enterprise—one that offers so much hope for so many. We have endured losses in real as well as adjusted dollars; survived the threats and reality of government shutdowns; and have not yet recovered all the funds that sequestration has taken away. This experience has been especially vivid to those of us who have lived in better times, when NIH was the beneficiary of strong budgetary growth. As Mae West famously said, "I’ve been rich and I’ve been poor, and rich is better."

While penury is never a good thing, I have sought its silver linings. My efforts to cope with budgetary limits have been guided by Lord Rutherford’s appeal to his British laboratory group during a period of fiscal restraint a century ago: "…we’ve run out of money, it is time to start thinking." Rather than simply hold on to survive our financial crisis without significant change, I have tried with essential help from my senior colleagues to reshape some of our many parts and functions. In this way, I have tried to take advantage of some amazing new opportunities to improve the understanding, prevention, diagnosis, and treatment of cancers, despite fiscal duress.

This is not the place for a detailed account of what we have achieved over the past five years. But a brief list of some satisfying accomplishments serves as a reminder that good things can be done despite the financial shortfalls that have kept us from doing more:

The NCI has established two new Centers: one for Global Health, to organize and expand a long tradition of studying cancer in many other countries; and another, for Cancer Genomics, to realize the promise of understanding and controlling cancer as a disorder of the genome.

Our clinical trials programs (now called the National Clinical Trials Network [NCTN] and the NCI Community Oncology Research Program [NCORP]) have been reconfigured to achieve greater efficiencies, adapt to the advent of targeted drugs and immunotherapies, and enhance the contributions of community cancer centers.

Research under a large NCI contract program in Frederick, Maryland, has been redefined as the Frederick National Laboratory for Cancer Research (FNLCR), with more external advice, a large new initiative to study tumors driven by mutant RAS genes, and greater clarity about FNLCR’s role as a supporter of biomedical research.

In efforts to provide greater stability for investigators in these difficult times, we have established a new seven year Outstanding Investigator Award; are discussing new awards to accelerate graduate and post-doctoral training; and are planning to provide individual support for so-called "staff scientists" at extramural institutions.

To strengthen the NCI-designated cancer centers, we are awarding more supplements to the centers’ budgets to encourage work in high priority areas; helping centers to share resources; and working with the center directors to develop more equitable funding plans.

The NCI has attempted to improve the grant-making process in various ways at a time when success rates for applicants have reached all-time lows:

We have engaged our scientists to identify inadequately studied but important questions about cancer—so-called Provocative Questions—and have provided funds for many well-regarded applications to address them.

We have pioneered the use of a descriptive account of an applicant’s past accomplishments, moving away from mere listings of publications, to allow a fairer appraisal of past contributions to science.

Our program leaders now make more nuanced decisions about funding many individual grants, considering a wide range of highly rated applications, not simply those with scores above an arbitrary pay-line.

And we have maintained NCI’s numbers of research project grants, despite the limits on our budget, while continuing to emphasize the importance of balancing unsolicited applications to do basic cancer research against an increasing call for targeted programs to deliver practical applications.

Of course, it is still too early to judge the long-term consequences of most of these actions. But we do know that many good things have happened in cancer research over the past five years as a result of existing investments:

Our understanding of cancer biology has matured dramatically with the near-completion of The Cancer Genome Atlas and with results from other programs that depend on genomics and basic science, including work with model systems.

Many new targeted therapies have been tested in clinical trials, and several have been approved for general use.

Remarkable clinical successes against several kinds of cancers have been reported with immunological tools—natural and synthetic antibodies, checkpoint inhibitors, and chimeric T cell receptors.

More widespread use of a highly effective vaccine against human papilloma viruses (HPV) and the several cancers they cause has been encouraged by further studies and by an important report from the President’s Cancer Panel.

Radiographic screening for lung cancers in heavy smokers—validated by a large-scale trial just after I arrived at the NCI—has now been endorsed for wide-spread use and for reimbursement by Medicare and other insurers.

New computational methods, such as cloud computing and improved inter-operability, are advancing the dream of integrating vast amounts of molecular data on many cancers into the daily care of such cancers.

Some of these advances are now essential features of the President’s recently announced Precision Medicine initiative that will focus initially on cancer.

Such accomplishments have been possible only because the NCI has been able to recruit and retain exceptional people during my years here; I am grateful to all of you. I am also grateful to the many selfless individuals who have made our advisory groups stronger than ever and to the cancer research advocates who regularly remind me—as well as Congress and the public—about the importance of our work to human welfare.

So what is next?

In my remaining few weeks in this position, I will continue to do the NCI Director’s job with customary energy, despite my inevitable status as a "lame duck." I will also schedule a Town Hall meeting to review some of the things that have happened during my tenure here—revisiting the ambitions I announced when I accepted the job and answering questions.

As I just learned today, the White House has approved the appointment of my chief deputy and close friend, Doug Lowy, to serve as Acting Director of the NCI, beginning on April 1st. This gives me enormous pleasure, because Doug—along with Jim Doroshow, the NCI’s Deputy Director for Clinical and Translational Research—made many of NCI’s recent accomplishments possible; is a distinguished scientist, who was recently honored by the President with a National Medal for Technology and Innovation for his work on human papilloma virus vaccines; and is a remarkably congenial person to work with. The NCI will be in excellent hands.

Finally, when I return to New York City full time on April 1st, I will establish a modestly sized research laboratory in the Meyer Cancer Center at the Weill-Cornell Medical College and serve as a senior advisor to the Dean. In addition, I plan to assist the recently founded New York Genome Center as it develops its research and service functions and helps regional institutions introduce genomics into cancer care.

While I look forward to these new adventures and to leading a life concentrated in one place, I know I will miss many of the people, authorities, and ideas that make the NCI Directorship such a stimulating and rewarding position.

With deep respect and gratitude to the entire NCI community,

Harold Varmus

Posted: March 4, 2015



Genome Res. 2014 Oct; 24(10): 1559–1571.

doi: 10.1101/gr.164871.113

PMCID: PMC4199368

Systems consequences of amplicon formation in human breast cancer

Koichiro Inaki,1,2,9 Francesca Menghi,1,2,9 Xing Yi Woo,1,9 Joel P. Wagner,1,2,3 Pierre-Étienne Jacques,4,5 Yi Fang Lee,1 Phung Trang Shreckengast,2 Wendy WeiJia Soon,1 Ankit Malhotra,2 Audrey S.M. Teo,1 Axel M. Hillmer,1 Alexis Jiaying Khng,1 Xiaoan Ruan,6 Swee Hoe Ong,4 Denis Bertrand,4 Niranjan Nagarajan,4 R. Krishna Murthy Karuturi,4,7 Alfredo Hidalgo Miranda,8 and Edison T. Liucorresponding author1,2,7

1Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore;

2The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06030, USA;

3Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA;

4Computational and Systems Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore;

5Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada;

6Genome Technology and Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore;

7The Jackson Laboratory, Bar Harbor, Maine 04609, USA;

8National Institute of Genomic Medicine, Periferico Sur 4124, Mexico City 01900, Mexico

corresponding authorCorresponding author.

9These authors contributed equally to this work.

Although in earlier studies the major focus was to find specific driver oncogenes in amplicons and tumor suppressor genes in common regions of loss (primarily using loss of heterozygosity mapping), progressively there emerged an understanding that more than one driver oncogene may be present in any amplicon. Moreover, each amplicon or region of copy number loss alters the expression of many adjacent genes, some with proven conjoint cancer effects (Zhang et al. 2009; Curtis et al. 2012). Thus, any cancer is likely to be a composite of hundreds to thousands of gene changes that contribute to the cancer state. Although specific point mutations contribute to adaptive evolutionary processes, recent genomic analyses from controlled evolutionary experiments in model systems suggest that copy number changes through segmental duplications and rearrangements may play a more prominent role (Chang et al. 2013; Fares et al. 2013).


Mutations in noncoding DNA also cause cancer

New discovery could lead to novel field of study within cancer research.

October 12, 2014 - 06:2


An international group of cancer researchers have completed the first ever systematic study of noncoding DNA. They found that mutations in the noncoding DNA can, despite previous beliefs, cause cancer.

Until now, scientists have only investigated 1.5 per cent of the total humane DNA. This is the part of the DNA which consists of genes. The remaining 98.5 per cent of the DNA is called noncoding DNA and resides outside of the genes.

The study, just published in Nature Genetics, shows that the majority of cancer patients have mutations in both their genes and the areas outside the genes.

The discovery could lead to a completely new field of study within cancer research and prevention.

"In the long term this may lead to better diagnoses and treatments," says co-author postdoc Anders Jacobsen from the University of Copenhagen at the department of Computational and RNA Biology.

Over the past 10 years scientists have found more and more abnormalities in DNA which lead to cancer.

Colleague is excited

Professor and Head of the Department of Genomic Medicine at Rigshospitalet Finn Cilius Nielsen did not contribute to the study, but has read it and is very excited.

He says the study shows the importance of looking into the noncoding regions of our DNA.

“It's interesting and points to the fact that we could discover clinically relevant information from the noncoding regions," says Nielsen. "Studies like this one could come up with some vital explanations for the causes of cancer," says Nielsen.

Examined 20 different cancer types

The scientists were looking at DNA mutations in 800 cancer patients with more than 20 different types of cancer.

They compared DNA from the patients' tumours with DNA from healthy tissue from the same patients. By doing so they were able to identify the differences between healthy and sick cells and the reason why the tumour had grown.

The scientists were interested in the noncoding regions of the DNA. These regions do not translate into protein as genes do -- instead, they have a different, biochemical task. They regulate how much of a particular gene is expressed. That is, if the gene is to be “on” or “off”.

“For the first time we have been able to see mutations in the noncoding DNA and how these can be the direct cause of cancer,” says Jacobsen.

Mutation gives cancer eternal life

Several mutations connected to the development of cancer were discovered by the scientists. They found that mutations in the front area of the gene which controls the length of telomeres, can trigger cancer.

Telomeres decide how many times a cell can divide and every time a cell divides the telomeres becomes shorter.

This means that at some stage the telomeres are so short that the cells can not longer divide.

However, mutations in the region before the gene TERT makes the gene hyperactive. The length of the telomeres are then extended much more than what is considered normal and a mutation like this will make the cell keep on dividing itself -- eventually forming a tumour.

“This mutation in the noncoding part of the DNA basically gives the cancer cells eternal life," says Jacobsen. "It was exciting that our research proved to have such a concrete result."

The scientists found that this mutation was the most frequent occurrence of cancer-causing mutations outside the gene.

More studies in the future

Jacobsen is convinced there will be many more studies wlooking at the noncoding DNA in the future.

"Our study shows that there's something here which needs to be looked at. With more studies, we can get a much better insight into what happens in cells when cancer occurs,” says Jacobsen. “We can learn a lot about he different cancers and their causes from this. In the long run we hope to develope new treatments.”

Nielsen agrees that there is a need for further studies in the area.

"We need more studies of this kind. I think it'll happen naturally. Within the next 10 to 15 years we'll be able to do complete genome sequencing quickly and cheaply, and then we'll naturally look at mutations in the entire genome -- rather than just in the genes," he says.


Read the original story in Danish on

[Some of us have been thinking, moreover using high-performance computers for quite some time aiming at the "NP-hard" problem of fractal pattern recognition. The first (double) disruption was to replace the mistaken dogmas of "Junk DNA" and "Central Dogma". "Genes failed us" - the very concept of "oncogenes" seemed to exclude the obvious that not only the presently 571 "oncogenes" that have already been found may include ALL genes that can potentially become "misregulated" by fractal defects also in the vast sees in the intergenic "non-coding" (not-Junk) DNA. Any qualified informatics-specialist or physicist would be mesmerized to wittness a PERSON trying to figure out nuclear particles either in fission or fusion (once the "axiom" that the atom would not split was invalidated by its splitting). How many hundreds of millions would have to face a uniquely miserable death till a global effort is directed to the informatics- and computing challenges of "genome misregulation" (a.k.a. cancer)? - andras_at_pellionisz_dot_com]

The Genome (both DNA and RNA) is replete with repeats. These are facts. The question is the mathematics (fractals) that is best suited to interpret self-similar repetitions

Isidore Rigoutsos (Greek-American mathematician) surprised the world in 2006 that the DNA (coding or not) is replete with ";yknon"-s (repetitions). Pointing out their astounding feature of "self-similarity", Pellionisz interpeted Rigoutos' "pyknon"-s as the facts that genome function must be understood in terms of fractals. In a study first shown in Cold Spring Harbor (2009), Pellionisz demonstrated for the smallest genome of a free living organism (Mycoplasma Genitaliae), that the distribution of self-similar repetitions follows the Zipf-Mandelbrot-Parabolic-Fractal Distribution Curve. (See Figure here). In two weeks, Erez Lieberman, Eric Lander (and others) put the Hilbert-fractal globule on Science cover.

Now, about 40 co-authors, with last author Rigoutsos (including the pioneer of RNA, John Mattick) published in PNAS a paper available in full here.

Just a glance at their Fig. 7 (above) will instantly convince all that microRNA-s (that are the culprit of genome regulation with dual valence), manifest "self-similar repetitions". [You may wonder what happens next, andras_at_pellionisz_dot_com]

On the Fractal Design in Human Brain and Nervous Tissue - Losa recognizes FractoGene

... the FractoGene “cause and effect” concept conceived that “fractal genome governs fractal growth of organelles, organs and organisms” Pellionisz, A.J. (2012) The Decade of FractoGene: From Discovery to Utility-Proofs of Concept Open Genome-Based Clinical Applications. International Journal of Systemics, Cybernetics and Informatics, 17-28.. The Principle of this recursive genome function (PRGF) breaks through the double lock of central dogma and junk DNA barriers Pellionisz, A. (1989) Neural Geometry: Towards a Fractal Model of Neurons. Cambridge University Press, Cambridge.. Decades of computer modeling of neurons and neuronal networks suggested that the amount of information necessary to build just a tiny fraction of the human body, i.e. just the cerebellum of the nervous system, was a task for which the 1.3% of the information that the genome could contain [as "genes"] was just totally insufficient Pellionisz, A. (2008) The Principle of Recursive Genome Function. Cerebellum, 7, 348-359.,

... Among the main fractal peculiarities worth noticing is the process of iteration, whose powerful dynamics allows specific generators to be properly iterated at different scales (small and large) without an a priori choice, by linking efficient genetic programming in order to achieve the formation of viable biological forms and living objects Di Ieva, A., Grizzi, F., Jelinek, H., Pellionisz, A.J. and Losa, G.A. (2013) Fractals in the Neurosciences, Part I: General Principles and Basic Neurosciences. The Neuroscientist. PMID: 24362815

How to cite this paper: Losa, G.A. (2014) On the Fractal Design in Human Brain and Nervous Tissue. Applied Mathematics, 5,


[Recognition of FractoGene by Gabriele Losa (and co-publishing in 2014) is significant since Dr. Losa in Switzerland pionereed, in a Four-Volume-Meeting-Book prior and at the Human Genome Project, providing an excellent compilation of book-chapters both on the fractality of genome, and separately on the fractality of organisms. In fact, some contributions contained pointers to both fractalities. However, just about the time "to connect the dots", "The Human Genome Project", with its historically mistaken focus on "genes" (motivated by personal enthusiasm by Jim Watson, such that by mapping all human genes, the "schizophrenia gene" should also be found) the fractal pioneering by Dr. Losa was put on a back-burner. It took another decade till FractoGene (2002) "connected the dots" that the "cause and effect" of fractal genome governs fractal growth of organielles, organs and organisms could break through the double lock of central dogma and junk DNA barriers that unfortunately still prevailed through the Losa Books (1-4). Outside that double straightjacket the enormous utility is now free to roam. "Google Alert" pointed to this Losa paper with delay - Dr. Pellionisz respectfully requests .pdf reprints of publications pertinent to FractoGene be sent ASAP to andras_at_pellionisz_dot_com for proper contemporary compilation and cross-reference. Indeed, as heralded in Google Tech Talk YouTube (2008) time is ripe for a postmodern meeting (with Proceedings). Those interested should contact Dr. Pellionisz]

CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

[The March 16, 2015 issue of Pharmaceutical Intelligence, with the Introduction by Dr. Larry H. Bernstein, puts together an earlier assessment of the disruptive fractal approach to genomics with the new hope of genome editing. "Fractal defects" appear in an entirely new light with genome editing becoming a reality. Pharmaceutical Intelligence excerpts are edited by AJP; hyperlinks and the central email address corrected; andras_at_pellionisz_dot_com]

CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

[About Dr. Larry H. Bernstein] - I retired from a five year position as Chief of the Division of Clinical Pathology (Laboratory Medicine) at New York Methodist Hospital-Weill Cornell Affiliate, Park Slope, Brooklyn in 2008 folowed by an interim consultancy at Norwalk Hospital in 2010. I then became engaged with a medical informatics project called “Second Opinion” with Gil David and Ronald Coifman, Emeritus Professor and Chairman of the Department of Mathematics in the Program in Applied Mathematics at Yale. I went to Prof. Coifman with a large database of 30,000 hemograms that are the most commonly ordered test in medicine because of the elucidation of red cell, white cell and platelet populations in the blood. The problem boiled down to a level of noise that exists in such data, and developing a primary evidence-based classification that technology did not support until the first decade of the 21st century.

Part II B: Computational Genomics

1. Three-Dimensional Folding and Functional Organization Principles of The Drosophila Genome

Sexton T, Yaffe E, Kenigeberg E, Bantignies F,…Cavalli G. Institute de Genetique Humaine, Montpelliere GenomiX, and Weissman Institute, France and Israel. Cell 2012; 148(3): 458-472.

Chromosomes are the physical realization of genetic information and thus form the basis for its readout and propagation. The entire genome is linearly partitioned into well-demarcated physical domains that overlap extensively with active and repressive epigenetic marks.

Chromosomal contacts are hierarchically organized between domains. Global modeling of contact density and clustering of domains show that inactive domains are condensed and confined to their chromosomal territories, whereas active domains reach out of the territory to form remote intra- and interchromosomal contacts.

Moreover, we systematically identify specific long-range intrachromosomal contacts between Polycomb-repressed domains.

Together, these observations allow for quantitative prediction of the Drosophila chromosomal contact map, laying the foundation for detailed studies of chromosome structure and function in a genetically tractable system.

2A. Architecture Reveals Genome’s Secrets

Three-dimensional genome maps - Human chromosome

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 miss 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.

Mapping and sequencing may be completely separate processes. For example, it’s possible to determine the location of a gene - to “map” the gene - without sequencing it. Thus, a map may tell you nothing about the sequence of the genome, and a sequence may tell you nothing about the map. But the landmarks on a map are DNA sequences, and mapping is the cousin of sequencing. A map of a sequence might look like this:

On this map, GCC is one landmark; CCCC is another. Here we find, the sequence is a landmark on a map. In general, particularly for humans and other species with large genomes, creating a reasonably comprehensive genome map is quicker and cheaper than sequencing the entire genome, mapping involves less information to collect and organize than sequencing does.

Completed in 2003, the Human Genome Project (HGP) was a 13-year project. The goals were:

* identify all the approximately 20,000-25,000 genes in human DNA,

determine the sequences of the 3 billion chemical base pairs that make up human DNA,

store this information in databases,

improve tools for data analysis,

transfer related technologies to the private sector, and

address the ethical, legal, and social issues (ELSI) that may arise from the project.

Though the HGP is finished, analyses of the data will continue for many years. By licensing technologies to private companies and awarding grants for innovative research, the project catalyzed the multibillion-dollar U.S. biotechnology industry and fostered the development of new medical applications. When genes are expressed, their sequences are first converted into messenger RNA transcripts, which can be isolated in the form of complementary DNAs (cDNAs). A small portion of each cDNA sequence is all that is needed to develop unique gene markers, known as sequence tagged sites or STSs, which can be detected using the polymerase chain reaction (PCR). To construct a transcript map, cDNA sequences from a master catalog of human genes were distributed to mapping laboratories in North America, Europe, and Japan. These cDNAs were converted to STSs and their physical locations on chromosomes determined on one of two radiation hybrid (RH) panels or a yeast artificial chromosome (YAC) library containing human genomic DNA. This mapping data was integrated relative to the human genetic map and then cross-referenced to cytogenetic band maps of the chromosomes. (Further details are available in the accompanying article in the 25 October issue of SCIENCE).

Tremendous progress has been made in the mapping of human genes, a major milestone in the Human Genome Project. Apart from its utility in advancing our understanding of the genetic basis of disease, it provides a framework and focus for accelerated sequencing efforts by highlighting key landmarks (gene-rich regions) of the chromosomes. The construction of this map has been possible through the cooperative efforts of an international consortium of scientists who provide equal, full and unrestricted access to the data for the advancement of biology and human health.

There are two types of maps: genetic linkage map and physical map. The genetic linkage map shows the arrangement of genes and genetic markers along the chromosomes as calculated by the frequency with which they are inherited together. The physical map is representation of the chromosomes, providing the physical distance between landmarks on the chromosome, ideally measured in nucleotide bases. Physical maps can be divided into three general types: chromosomal or cytogenetic maps, radiation hybrid (RH) maps, and sequence maps.

2B. Genome-nuclear lamina interactions and gene regulation.

Kind J, van Steensel B. Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, The Netherlands.

The nuclear lamina, a filamentous protein network that coats the inner nuclear membrane, has long been thought to interact with specific genomic loci and regulate their expression. Molecular mapping studies have now identified large genomic domains that are in contact with the lamina.

Genes in these domains are typically repressed, and artificial tethering experiments indicate that the lamina can actively contribute to this repression.

Furthermore, the lamina indirectly controls gene expression in the nuclear interior by sequestration of certain transcription factors.

Mol Cell. 2010; 38(4):603-13. maps of the reorganization of genome-nuclear lamina interactions during differentiation/

Peric-Hupkes D, Meuleman W, Pagie L, Bruggeman SW, Solovei I, …., van Steensel B. Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, The Netherlands.

To visualize three-dimensional organization of chromosomes within the nucleus, we generated high-resolution maps of genome-nuclear lamina interactions during subsequent differentiation of mouse embryonic stem cells via lineage-committed neural precursor cells into terminally differentiated astrocytes. A basal chromosome architecture present in embryonic stem cells is cumulatively altered at hundreds of sites during lineage commitment and subsequent terminal differentiation. This remodeling involves both individual transcription units and multigene regions and affects many genes that determine cellular identity, genes that move away from the lamina are concomitantly activated; others, remain inactive yet become unlocked for activation in a next differentiation step, lamina-genome interactions are widely involved in the control of gene expression programs during lineage commitment and terminal differentiation.

Molecular Maps of the Reorganization of Genome-Nuclear Lamina Interactions during Differentiation

Molecular Cell, Volume 2010; 38 (4): 603-613.

Referred to by: The Silence of the LADs: Dynamic Genome-…

Authors: Daan Peric-Hupkes, Wouter Meuleman, Ludo Pagie, Sophia W.M. Bruggeman, et al.

Various cell types share a core architecture of genome-nuclear lamina interactions. During differentiation, hundreds of genes change their lamina interactions. Changes in lamina interactions reflect cell identity. Release from the lamina may unlock some genes for activation

Fractal “globule”

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 Hi-C, 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, Jobe 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. 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. The researchers report two striking findings.

First, the human genome is organized into two separate compartments, keeping

* active genes separate and accessible

* while sequestering unused DNA in a denser storage compartment.

* Chromosomes snake in and out of the two compartments repeatedly

* as their DNA alternates between active, gene-rich and inactive, gene-poor stretches.

Second, at a finer scale, the genome adopts an unusual organization known in mathematics as a “fractal.” The specific architecture the scientists found, called

* a “fractal globule,” enables the cell to pack DNA incredibly tightly – the information density in the nucleus is trillions of times higher than on a computer chip — while avoiding the knots and tangles that might interfere with the cell’s ability to read its own genome. Moreover, the DNA can easily Unfold and Refold during

* gene activation,

* gene repression, and

* cell replication.

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. Dekker thinks the discovery of [folding] domains will be one of the most fundamental [genetics] discoveries of the last 10 years. The big questions now are

* how these domains are formed, and

* what determines which elements are looped into proximity.

“By breaking the genome into millions of pieces, we created a spatial map showing how close different parts are to one another,” says co-first author Nynke van Berkum, a postdoctoral researcher at UMass Medical School in Dekker‘s laboratory. “We made a fantastic three-dimensional jigsaw puzzle and then, with a computer, solved the puzzle.”

Lieberman-Aiden, van Berkum, Lander, and Dekker’s co-authors are Bryan R. Lajoie of UMMS; Louise Williams, Ido Amit, and Andreas Gnirke of the Broad Institute; Maxim Imakaev and Leonid A. Mirny of MIT; Tobias Ragoczy, Agnes Telling, and Mark Groudine of the Fred Hutchison, Cancer Research Center and the University of Washington; Peter J. Sabo, Michael O. Dorschner, Richard Sandstrom, M.A. Bender, and John Stamatoyannopoulos of the University of Washington; and Bradley Bernstein of the Broad Institute and Harvard Medical School.

2C. three-dimensional structure of the human genome

Lieberman-Aiden et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 2009; DOI: 10.1126/science.1181369.

Harvard University (2009, October 11). 3-D Structure Of Human Genome: Fractal Globule Architecture Packs Two Meters Of DNA Into Each Cell. ScienceDaily. Retrieved February 2, 2013, from

Using a new technology called Hi-C and applying it to answer the thorny question of how each of our cells stows some three billion base pairs of DNA while maintaining access to functionally crucial segments. The paper comes from a team led by scientists at Harvard University, the Broad Institute of Harvard and MIT, University of Massachusetts Medical School, and the Massachusetts Institute of Technology. “We’ve long known that on a small scale, DNA is a double helix,” says co-first author Erez Lieberman-Aiden, a graduate student in the Harvard-MIT Division of Health Science and Technology and a researcher at Harvard’s School of Engineering and Applied Sciences and in the laboratory of Eric Lander at the Broad Institute. “But if the double helix didn’t fold further, the genome in each cell would be two meters long. Scientists have not really understood how the double helix folds to fit into the nucleus of a human cell, which is only about a hundredth of a millimeter in diameter. This new approach enabled us to probe exactly that question.”

The mapping technique that Aiden and his colleagues have come up with bridges a crucial gap in knowledge—between what goes on at the smallest levels of genetics (the double helix of DNA and the base pairs) and the largest levels (the way DNA is gathered up into the 23 chromosomes that contain much of the human genome). The intermediate level, on the order of thousands or millions of base pairs, has remained murky. As the genome is so closely wound, base pairs in one end can be close to others at another end in ways that are not obvious merely by knowing the sequence of base pairs. Borrowing from work that was started in the 1990s, Aiden and others have been able to figure out which base pairs have wound up next to one another. From there, they can begin to reconstruct the genome—in three dimensions.

Even as the multi-dimensional mapping techniques remain in their early stages, their importance in basic biological research is becoming ever more apparent. “The three-dimensional genome is a powerful thing to know,” Aiden says. “A central mystery of biology is the question of how different cells perform different functions—despite the fact that they share the same genome.” How does a liver cell, for example, “know” to perform its liver duties when it contains the same genome as a cell in the eye? As Aiden and others reconstruct the trail of letters into a three-dimensional entity, they have begun to see that “the way the genome is folded determines which genes were

2D. “Mr. President; The Genome is Fractal !”

Eric Lander (Science Adviser to the President and Director of Broad Institute) et al. delivered the message on Science Magazine cover (Oct. 9, 2009) and generated interest in this by the International HoloGenomics Society at a Sept meeting [Pellionisz, Sept. 16, 2009 in Cold Springs Harbor]

First, it may seem to be trivial to rectify the statement in “About cover” of Science Magazine by AAAS.

The statement “the Hilbert curve is a one-dimensional fractal trajectory” needs mathematical clarification.

The mathematical concept of a Hilbert space, named after David Hilbert, generalizes the notion of Euclidean space. It extends the methods of vector algebra and calculus from the two-dimensional Euclidean plane and three-dimensional space to spaces with any finite or infinite number of dimensions. A Hilbert space is an abstract vector space possessing the structure of an inner product that allows length and angle to be measured. Furthermore, Hilbert spaces must be complete, a property that stipulates the existence of enough limits in the space to allow the techniques of calculus to be used. A Hilbert curve (also known as a Hilbert space-filling curve) is a continuous fractal space-filling curve first described by the German mathematician David Hilbert in 1891,[1] as a variant of the space-filling curves discovered by Giuseppe Peano in 1890.[2] For multidimensional databases, Hilbert order has been proposed to be used instead of Z order because it has better locality-preserving behavior.

Representation as Lindenmayer system

The Hilbert Curve can be expressed by a rewrite system (L-system).

While the paper itself does not make this statement, the new Editorship of the AAAS Magazine might be even more advanced if the previous Editorship did not reject (without review) a Manuscript by 20+ Founders of (formerly) International PostGenetics Society in December, 2006 - [only an Abstract by Pellionisz could be published at his Symposium in native Budapest, 2006, AJP].

Second, it may not be sufficiently clear for the reader that the reasonable requirement for the DNA polymerase to crawl along a “knot-free” (or “low knot”) structure does not need fractals. A “knot-free” structure could be spooled by an ordinary “knitting globule” (such that the DNA polymerase does not bump into a “knot” when duplicating the strand; just like someone knitting can go through the entire thread without encountering an annoying knot): Just to be “knot-free” you don’t need fractals. Note, however, that

* the “strand” can be accessed only at its beginning – it is impossible to e.g. to pluck a segment from deep inside the “globulus”.

This is where certain fractals provide a major advantage – that could be the “Eureka” moment for many readers. [Below, citing a heavily spammed email address instead of the secured andras_at_pellionisz_dot_com, the "Heureka explanation" borrows from here - AJP] For instance,

* the mentioned Hilbert-curve is not only “knot free” -

* but provides an easy access to “linearly remote” segments of the strand.

* If the Hilbert curve starts from the lower right corner and ends at the lower left corner, for instance

* the path shows the very easy access of what would be the mid-point

* if the Hilbert-curve is measured by the Euclidean distance along the zig-zagged path.

Likewise, even the path from the beginning of the Hilbert-curve is about equally easy to access – easier than to reach from the origin a point that is about 2/3 down the path. The Hilbert-curve provides an easy access between two points within the “spooled thread”; from a point that is about 1/5 of the overall length to about 3/5 is also in a “close neighborhood”.

This may be the “Eureka-moment” for some readers, to realize that

* the strand of “the Double Helix” requires quite a finess to fold into the densest possible globuli (the chromosomes) in a clever way

* that various segments can be easily accessed. Moreover, in a way that distances between various segments are minimized.

This marvellous fractal structure is illustrated by the 3D rendering of the Hilbert-curve. Once you observe such fractal structure, you’ll never again think of a chromosome as a “brillo mess”, would you? It will dawn on you that the genome is orders of magnitudes more finessed than we ever thought so.

Those embarking at a somewhat complex review of some historical aspects of the power of fractals may wish to consult the ouvre of Mandelbrot (also, to celebrate his 85th birthday). For the more sophisticated readers, even the fairly simple Hilbert-curve (a representative of the Peano-class) becomes even more stunningly brilliant than just some “see through density”. Those who are familiar with the classic “Traveling Salesman Problem” know that “the shortest path along which every given n locations can be visited once, and only once” requires fairly sophisticated algorithms (and tremendous amount of computation if n>10 (or much more). Some readers will be amazed, therefore, that for n=9 the underlying Hilbert-curve helps to provide an empirical solution.

refer to [Andras J. Pellionisz, andras_at_pellionisz_dot_com]

Briefly, the significance of the above realization, that the (recursive) Fractal Hilbert Curve is intimately connected to the (recursive) solution of TravelingSalesman Problem, a core-concept of Artificial Neural Networks can be summarized as below.

Accomplished physicist John Hopfield (already a member of the National Academy of Science) aroused great excitement in 1982 with his (recursive) design of artificial neural networks and learning algorithms which were able to find reasonable solutions to combinatorial problems such as the Traveling SalesmanProblem. (Book review Clark Jeffries, 1991, see also 2. J. Anderson, R. Rosenfeld, and A. Pellionisz (eds.), Neurocomputing 2: Directions for research, MIT Press, Cambridge, MA, 1990):

“Perceptions were modeled chiefly with neural connections in a “forward” direction: A -> B -* C — D. The analysis of networks with strong backward coupling proved intractable. All our interesting results arise as consequences of the strong back-coupling” (Hopfield, 1982).

The Principle of Recursive Genome Function [Pellionisz, 2008 in peer reviewed science article, also disseminated as Google Tech Talk YouTube "Is IT Ready for the Dreaded DNA Data Deluge"] surpassed obsolete axioms that blocked, for half a Century, entry of recursive algorithms to interpretation of the structure-and function of (Holo)Genome. This breakthrough, by uniting the two largely separate fields of Neural Networks and Genome Informatics, is particularly important for

* those who focused on Biological (actually occurring) Neural Networks (rather than abstract algorithms that may not, or because of their core-axioms, simply could not

* represent neural networks under the governance of DNA information).

3A. The FractoGene Decade

from Inception in 2002 to Proofs of Concept and Impending Clinical Applications by 2012

[Below, Pharmaceutical Intelligence lists the yearly milestones of FractoGene. The document that also contains all hyperlinks is here ]

Junk DNA Revisited (SF Gate, 2002)

The Future of Life, 50th Anniversary of DNA (Monterey, 2003)

Mandelbrot and Pellionisz (Stanford, 2004)

Morphogenesis, Physiology and Biophysics (Simons, Pellionisz 2005)

PostGenetics; Genetics beyond Genes (Budapest, 2006)

ENCODE-conclusion (Collins, 2007)

The Principle of Recursive Genome Function (paper, YouTube, 2008)

Cold Spring Harbor presentation of FractoGene (Cold Spring Harbor, 2009)

Mr. President, the Genome is Fractal! (2009)

HolGenTech, Inc. Founded (2010)

Pellionisz on the Board of Advisers in the USA and India (2011)

ENCODE – final admission (2012)

Recursive Genome Function is Clogged by Fractal Defects in Hilbert-Curve (2012)

Geometric Unification of Neuroscience and Genomics (2012)

US Patent Office issues FractoGene 8,280,641 to Pellionisz (2012)

[Below, Pharmaceutical Intelligence provides some excerpts from a 2002 article in SF-Gate (the electronic version of San Francisco Chronicle). This is a very lucid overview of the beginnings at 2002 - AJP]

When the human genome was first sequenced in June 2000, there were two pretty big surprises. The first was thathumans 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.

If biophysicist Andras Pellionisz is correct, genetic science may be on the verge of yielding its third — and by far biggest — surprise.

With a doctorate in physics, Pellionisz is the holder of Ph.D.’s in computer sciences and experimental biology from the prestigious Budapest Technical University and the Hungarian National Academy of Sciences. A biophysicist by training, the 59-year-old is a former research associate professor of physiology and biophysics at New York University, author of numerous papers in respected scientific journals and textbooks, a past winner of the prestigious Humboldt Prize for scientific research, a former consultant to NASA and holder of a patent on the world’s first artificial cerebellum, a technology that has already been integrated into research on advanced avionics systems. Because of his background, the Hungarian-born brain researcher might also become one of the first people to successfully launch a new company by using the Internet to gather momentum for a novel scientific 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. The notion that at least certain parts of junk DNA might have a purpose for example, many researchers now refer to with a far less derogatory term: introns.

In a provisional patent application filed July 31, Pellionisz claims to have unlocked a key to the hidden role junk DNA plays in growth — and in life itself. His patent application covers all attempts to count, measure and compare the fractal properties of introns for diagnostic and therapeutic purposes.

[The patent with priority date of 2002 is now a USPTO issued patent 8,280,641 in force till 2026 late March. The utility of "diagnostic and therapeutic purposes" has just gained a tremendous new market with "genome editing" unfolding. "Fractal Defects" in the genome producing "Fractal Defects" of the organism (perhaps most importantly, cancer) can not only be matched to the therapeutic agents (chemos) with the highest probability to be effective (80% of chemos are NOT effective for the genome of any particular individual). Beyond this vast market, editing out fractal defects that initiate the derailment of fractal genome regulation hold a key to the ultimate "inner sanctum" of providing genomic cures based on mathematical understanding - AJP]

3B. The Hidden Fractal Language of Intron DNA

[Excerpts from San Francisco Chronicle, 2002 continued] -To fully understand Pellionisz’ idea, one must first know what a fractal is.

Fractals are a way that nature organizes matter. Fractal patterns can be found in anything that has a nonsmooth surface (unlike a billiard ball), such as coastal seashores, the branches of a tree or the contours of a neuron (a nerve cell in the brain). Some, but not all, fractals are self-similar and stop repeating their patterns at some stage; the branches of a tree, for example, can get only so small. Because they are geometric, meaning they have a shape, fractals can be described in mathematical terms. It’s similar to the way a circle can be described by using a number to represent its radius (the distance from its center to its outer edge). When that number is known, it’s possible to draw the circle it represents without ever having seen it before.

Although the math is much more complicated, the same is true of fractals. If one has the formula for a given fractal, it’s possible to use that formula to construct, or reconstruct, an image of whatever structure it represents, no matter how complicated.

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.

In a move sure to alienate some scientists, Pellionisz has chosen the unorthodox route of making his initial disclosures online on his own Web site. He picked that strategy, he says, because it is the fastest way he can document his claims and find scientific collaborators and investors. Most mainstream scientists usually blanch at such approaches, preferring more traditionally credible methods, such as publishing articles in peer-reviewed journals.

[San Francisco Chronicle could not possess the domain expertise to know that the double-disruption (overturning both of the underlying axioms of Genomics, the JunkDNA and Central Dogmas) not only in 2002 made it impossible to publish with the prevailing bias of "peer review", but even in 2006, along with 20+ leading scientists, worldwide, Science Magazine rejected (without review, a violation of their bylaws...) publication. The enormous utility in the scientific breakthrough compelled the scientist-inventor, now seeking the proper class of entrepreneurs, to swiftly file to USPTO, spend well over a million dollars of his own money (to become the sole inventor and "clean as a whistle" owner), in the struggle to see through the patent, approved over ten years of wrangling, finally USPTO throwing in the towel a week after ENCODE-II killed the Old School Dogmas. Meanwhile, both the mathematical theory, software enabling algorithms had to go beyond the "best methods" of the time of last CIP to patent (2007 - now available as "trade secrets"), and once the priority was secured peer reviewed publications could resume. Noteworthy that the scientist-inventor has published well over 100 peer-reviewed papers before his double-disruptive FractoGene. A previous issued patent of Pellionisz took NASA 10 years to improve the avionics of F15 fighter jets. - AJP]

Basically, Pellionisz’ idea is that a fractal set of building instructions in the DNA plays a similar role in organizing life itself. Decode the way that language works, he says, and in theory it could be reverse engineered. Just as knowing the radius of a circle lets one create that circle, the more complicated fractal-based formula would allow us to understand how nature creates a heart or simpler structures, such as disease-fighting antibodies. At a minimum, we’d get a far better understanding of how nature gets that job done.

The complicated quality of the idea is helping encourage new collaborations across the boundaries that sometimes separate the increasingly intertwined disciplines of biology, mathematics and computer sciences.

Hal Plotkin, Special to SF Gate. Thursday, November 21, 2002. to SF Gate/plotkin.htm (1 of 10)2012.12.13. 12:11:58/

3C. multifractal analysis

The human genome: a multifractal analysis. Moreno PA, Vélez PE, Martínez E, et al.

BMC Genomics 2011, 12:506.

Background: Several studies have shown that genomes can be studied via a multifractal formalism. Recently, we used a multifractal approach to study the genetic information content of the Caenorhabditis elegans genome. Here we investigate the possibility that the human genome shows a similar behavior to that observed in the nematode.

Results: We report here multifractality in the human genome sequence. This behavior correlates strongly on the presence of Alu elements and to a lesser extent on CpG islands and (G+C) content.

In contrast, no or low relationship was found for LINE, MIR, MER, LTRs elements and DNA regions poor in genetic information.

Gene function, cluster of orthologous genes, metabolic pathways, and exons tended to increase their frequencies with ranges of multifractality and large gene families were located in genomic regions with varied multifractality.

Additionally, a multifractal map and classification for human chromosomes are proposed.


we propose a descriptive non-linear model for the structure of the human genome,

This model reveals

a multifractal regionalization where many regions coexist that are far from equilibrium and this non-linear organization has significant molecular and medical genetic implications for understanding the role of Alu elements in genome stability and structure of the human genome.

Given the role of Alu sequences in gene regulation, genetic diseases, human genetic diversity, adaptation and phylogenetic analyses, these quantifications are especially useful.

Future of genomic medicine depends on sharing information: Eric Lander

Feb 26, 2015 01:34 AM , By Special Correspondent | 0 comments

[Eric Lander goes to Bangalore (Tata Auditorium) early March]

Eric S. Lander, one of the principal leaders of the Human Genome Project that mapped the entire human genetic code in 2003, said on Wednesday that the “real genome project” is about studying huge samples of genomic data to identify disease genes.

While phenomenal technological advances had helped reduce the cost of genome sequencing by a million-fold over the last decade, allowing researchers to map thousands of human genomes, the future of genomic medicine depended on “sharing information” between organisations and countries — including India — Professor Lander said.

In order for therapy to emerge from genetic research, “health systems around the world need to turn into learning systems” that share information, said Prof Lander, delivering a lecture on “The Human Genome and Beyond: A 35 year Journey of Genomic Medicine” as part of the three-city Cell Press-TNQ Distinguished Lectureship Series.

Prof. Lander envisaged a “DNA library” where genes can be cross-referenced to detect “spelling differences” and disease genes. The goal before the scientific community now was to find targets for therapeutic intervention, he said, to a packed auditorium comprising a large number of medical students. There was much to be learnt in the course of clinical care, said Prof. Lander, founding director of the Broad Institute of MIT and Harvard University.

While the “breathless hype” created around the Human Genome Project suggested that it would cure all disease in a couple of years, he said much progress had indeed been made over the last decade with the discovery of several genes responsible for diabetes, schizophrenia and heart attacks.

Prof. Lander will be speaking next on Friday at the JN Tata Auditorium in Bengaluru as part of the lectureship series.

[For Pellionisz, in his 2012 Bangalore-Hyderabad-Trivandrum lectureship series the "Fractal Approach" was an "easy sale in India" - where culture is replete of self-similar repetitions:

[Pellionisz' lectureship series in India, selling fractals, 2012]

Pellionisz initiated FractoGene in 2002 as a US patent application not because he is a scientist driven by money (see about a hundred academic publications to geometrize neuroscience). "Fractal Genome Grows Fractal Organism" was in 2002 a "double lucid heresy" (reversing both mistaken dogmas of old-schoool genomics; the "Junk DNA" misnomer and "Central Dogma"). Not only no peer-review would accept it (even in 2006, prior to releasing ENCODE-I Science rejected without review a manuscript submitted with dozens of world-class co-authors). In fact, after publishing the seminal concept in 1989 of fractal recursion to the genome in a Cambridge University Press book (a Proceedings of a Neural Networks meeting in which Pellionisz was on the Program Committee), his ongoing NIH grant was discontinued and the application to a new NIH program, promoting informatics was not accepted (see "acknowledgement" in the 1989 paper). Now the utility is a US patent in force, 8,280,641), academically followed by Lander putting the Hilbert-fractal on the cover of Science magazine (2009). In the "Global $2 Trillion Trilemma" (see essay below) India can contribute with huge numbers of human genomes (both control and cancerous), along with the much less regulated personal data, and much more economical genome-based chemo-matching. Pellionisz put forward this plan as his Proceedings of award-winning lecture-tour in India. Francis Collins toured Bangalore at about the same time, and now Eric Lander has a chance to bring the international collaboration to success with Ratan Tata. The video of Eric' pitch (taped in New Delhi) answers the reporter's question "what is the single biggest thing (towards breakthrough of understanding genomic underpinning of e.g. cancer)?" in an interesting manner: "The diagram of a cell".

With due respect, a fractal diagram of a (Purkinje) cell, generated by the fractal recursive genome function, is already available, and India is keenly aware of the powerful architecture of self-similar repetitions (fractals) both by a presentation and Proceedings.

[Samples from presentation in lecture-tour of Pellionisz in India, 2012]

Eric Lander also visited Bangalore and Chennai, and concluded with the prediction that 'India Will Lead the Genetic Revolution':

The New Indian Express

By Papiya Bhattacharya

BENGALURU:India will lead the genetic revolution, said Broad Institute of MIT and Harvard’s core member Prof Eric Lander, while delivering the last of his lectures in the Cell Press-TNQ India Distinguished Lectureship Series 2015 here on Friday.

“India is a country of a billion people. It has a special role to play because of its huge diversity of environment, people, their exposure to these environments and a large percentage of consanguinity. All these factors can be put to good use to study the existence and function of human genes for India,“ he said.

Lander is one of the leaders of the Human Genome Project. He and his colleagues are known for sequencing the human genome in 2000 and they have standing interest in applying genomics to understand the molecular basis of human physiology and disease.

Lander has a PhD in Mathematics from Oxford University as a Rhodes scholar. He later turned a biologist and a geneticist.

His mathematical talent came in handy when he turned to interpret the human genome and its sequence.

On Friday, he spoke on the history of genetics, its birth in 1911 to 1980 when he and his collaborators spent $3 billion to sequence the human genome.

“Now the job is to find the genes responsible for diseases so that drugs can target those genes and the proteins they make and help in treating diseases,” he said.

The future belongs to precision medicine where all medical decisions, medicines and products will be tailored to suit the patients individual needs of the body and genome, he added.

Genetic Geometry Takes Shape

By: Ivan Amato

February 25, 2015

nuclei from a half-million human cells could all fit inside a single poppy seed. Yet within each and every nucleus resides genomic machinery that is incredibly vast, at least from a molecular point of view. It has billions of parts, many used to activate and silence genes — an arrangement that allows individual cells to specialize as brain cells, heart cells and some 200 other different cell types. What’s more, each cell’s genome is atwitter with millions of mobile pieces that swarm throughout the nucleus and latch on here and there to tweak the genetic program. Every so often, the genomic machine replicates itself.

At the heart of the human genome’s Lilliputian machinery is the two meters’ worth of DNA that it takes to embody a person’s 3 billion genetic letters, or nucleotides. Stretch out all of the genomes in all of your body’s trillions of cells, says Tom Misteli, the head of the cell biology of genomes group at the National Cancer Institute in Bethesda, Md., and it would make 50 round trips to the sun. Since 1953, when James Watson and Francis Crick revealed the structure of DNA, researchers have made spectacular progress in spelling out these genetic letters. But this information-storage view reveals almost nothing about what makes specific genes turn on or off at different times, in different tissue types, at different moments in a person’s day or life.

To figure out these processes, we must understand how those genetic letters collectively spiral about, coil, pinch off into loops, aggregate into domains and globules, and otherwise assume a nucleus-wide architecture. “The beauty of DNA made people forget about the genome’s larger-scale structure,” said Job Dekker, a molecular biologist at the University of Massachusetts Medical School in Worcester who has built some of the most consequential tools for unveiling genomic geometry. “Now we are going back to studying the structure of the genome because we realize that the three-dimensional architecture of DNA will tell us how cells actually use the information. Everything in the genome only makes sense in 3-D.”

Genome archaeologists like Dekker have invented and deployed molecular excavation techniques for uncovering the genome’s architecture with the hope of finally discerning how all of that structure helps to orchestrate life on Earth. For the past decade or so, they have been exposing a nested hierarchy of structural motifs in genomes that are every bit as elemental to the identity and activity of each cell as the double helix.

A Better Genetic Microscope

A close investigation of the genomic machine has been a long time in coming. The early British microscopist Robert Hooke coined the word cell as a result of his mid-17th-century observations of a thin section of cork. The small compartments he saw reminded him of monks’ living quarters — their cells. By 1710, Antonie van Leeuwenhoek had spied tiny compartments within cells, though it was Robert Brown, of Brownian motion fame, who coined the word nucleus to describe these compartments in the early 1830s. A half-century later, in 1888, the German anatomist Heinrich Wilhelm Gottfried von Waldeyer-Hartz peered through his microscope and decided to use the word chromosome — meaning “color body” — for the tiny, dye-absorbing threads that he and others could see inside nuclei with the best microscopes of their day.

During the 20th century, biologists found that the DNA in chromosomes, rather than their protein components, is the molecular incarnation of genetic information. The sum total of the DNA contained in the 23 pairs of chromosomes is the genome. But how these chromosomes fit together largely remained a mystery.

Then in the early 1990s, Katherine Cullen and a team at Vanderbilt University developed a method to artificially fuse pieces of DNA that are nearby in the nucleus — a seminal feat that made it possible to analyze the ultrafolded structure of DNA merely by reading the DNA sequence. This approach has been improved over the years. One of its latest iterations, called Hi-C, makes it possible to map the folding of entire genomes.

The first step in a Hi-C experiment is to treat a sample of millions of cells with formaldehyde, which has the chemical effect of cross-linking strands of DNA wherever two strands happen to be close together. Those two nearby bits might be some distance away along the same chromosome that has bent back onto itself, or they may be on separate but adjacent chromosomes.

Next, researchers mince the genomes, harvest the millions of cross-linked snippets, and sequence the DNA of each snippet. The sequenced snippets are like close-up photos of the DNA-DNA contacts in the 3-D genome. Researchers map these snippets onto existing genome-wide sequence data to create a listing of the genome’s contact points. The results of this matching exercise are astoundingly data-rich maps — they look like quilts of nested, color-coded squares of different sizes — that specify the likelihood of any two segments of a chromosome (or even two segments of an entire genome) to be physically close to one another in the nucleus.

So far, most Hi-C data depict an average contact map using contact hits pooled from all of the cells in the sample. But researchers have begun to push the technique so that they can harvest the data from single cells. The emerging capability could lead to the most accurate 3-D renderings yet of chromosomes and genomes inside nuclei.

In addition, Erez Lieberman Aiden, the director of the Baylor College of Medicine Center for Genome Architecture, and his colleagues have recently cataloged DNA-DNA contacts in intact nuclei, rather than in DNA that previously had to be extracted from nuclei, a step that adds uncertainty to the data. The higher-resolution contact maps enable the researchers to discern genomic structural features on the scale of 1,000 genetic letters — a resolution about 1,000 times finer than before. It is like looking right under the hood of a car instead of squinting at the engine from a few blocks away. The researchers published their views of nine cell types, including cancer cells in both humans and mice, in the December 18, 2014, issue of Cell.

The Power of Loops

Using sophisticated algorithms to analyze the hundreds of millions — in some cases, billions — of contact points in these cells, Aiden and his colleagues could see that these genomes pinch off into some 10,000 loops. Cell biologists have known about genomic loops for decades, but were not previously able to examine them with the level of molecular resolution and detail that is possible now. These loops, whose fluid shapes Dekker likens to “snakes all curled up,” reveal previously unseen ways that the genome’s large-scale architecture might influence how specific genes turn on and off, said Miriam Huntley, a doctoral student at Harvard University and a co-author of the Cell article.

In the different cell types, the loops begin and end at different specific chromosomal locations, so each cell line’s genome appears to have a unique population of loops. And that differentiation could provide a structural basis to help explain how cells with the same overall genome nonetheless can differentiate into hundreds of different cell types. “The 3-D architecture is associated with which program the cell runs,” Aiden said.

What do these loops do? Misteli imagines them “swaying in the breeze” inside the fluid interior of the nucleus. As they approach and recede from one another, other proteins might swoop in and stabilize the transient loop structure. At that point, a particular type of protein called a transcription activator can kick-start the molecular process by which a gene gets turned on.

Misteli muses that each cell type — a liver cell or a brain cell, for example — could have a signature network of these transient loop-loop interactions. Loop structures could determine which genes get activated and which get silenced.

Yet the researchers are careful to note that they’ve only found associations between structure and function — it’s still too early to know for sure if one causes the other, and the direction in which the causal arrow points.

As they mined their data on inter-loop interactions, Aiden, Huntley and their colleagues were also able to discern a half-dozen larger structural features in the genome called subcompartments. Aiden refers to them as “spatial neighborhoods in the nucleus” — the nucleic equivalent of New York City’s midtown or Greenwich Village. And just as people gravitate toward one neighborhood or another, different stretches of chromosomes carry a kind of molecular zip code for certain subcompartments and tend to slither toward them.

These molecular zip codes are written in chromatin, the mix of DNA and protein that makes up chromosomes. Chromatin is built when DNA winds around millions of spool-like protein structures called nucleosomes. (This winding is why two meters of DNA can cram inside nuclei with diameters just one-three-hundred-thousandth as wide.)

A large cast of biomolecular players finesses different swaths of this contorted chromatin into more closed or open shapes. Roving parts of the genomic machine can better access the open sections, and so have a better chance of turning on the genes located there.

The increasingly detailed hierarchical picture of the genome that researchers like Dekker, Misteli, Aiden and their colleagues have been building goes something like this: Nucleotides assemble into the famous DNA double helix. The helix winds onto nucleosomes to form chromatin, which winds and winds in its turn into formations similar to what you get when you keep twisting the two ends of a string. Amid all of this, the chromatin pinches off here and there into thousands of loops. These loops, both on the same chromosome and on different ones, engage one another in subcompartments.

As researchers gradually gain more insight into the genome’s hierarchy of structures, they will get closer to figuring out how this macromolecular wonder works in all of its vastness and mechanistic detail. The National Institutes of Health has launched a five-year, $120 million program called 4D Nucleome that is sure to build momentum in the nuclear-architecture research community, and a similar initiative is being launched in Europe. The goal of the NIH program, as described on its website, is “to understand the principles behind the three-dimensional organization of the nucleus in space and time (the fourth dimension), the role nuclear organization plays in gene expression and cellular function, and how changes in the nuclear organization affect normal development as well as various diseases.”

Or, as Dekker says, “It will finally allow us to see the living genome in action, and that would ultimately tell us how it actually works.

[By the completion of the Human Genome Project in 2001, and especially after the shock of finding next year (2002) that the mouse has essentially the same tiny set of "genes", thinkers had to seek principles of the genome function. This was not easy, since the celebrated principle of genome STRUCTURE (the Double Helix, 1953) biased thinking towards a linear (though twisted) "thread". Nothing can take away the significance of the discovery of double-stranded structure, since it is the basis how the genome propagates itself. Nonetheless, the structure (and its propagation) essentially says nothing about how the genome functions; how the genome governs the growth of living organisms. (Transcription is serial, but different kinds of proteins are produced in parallel even within a single cell, moreover the regulation of production of proteins is obviously interactive in a parallel manner). The above journalistic reminder takes us back to 2002 when Job Dekker (and co-workers)”discovered and developed an experimental method (3C) to measure the frequency of interaction between any two genomic loci. The parallel function of the genome was, therefore, experimentally established. Along a separate line of thinking, since 1989 Pellionisz showed that the single cell of a Purkinje neuron develops branchlets in a parallel fashion (just like any tree grows branchlets and leaves in a parallel fashion, certainly not serially one after the other). Moreover, the growth of the cell has proven to be fractal, requiring the Principle of Recursive Genome Function (Pellionisz, 2008). It was the brilliance of Eric Lander, handed over a copy of the manuscript of "The Principle of Recursive Genome Function" dedicated to him in 2007, that connected the two lines of thoughts by means of the spectacular improvement of Dekker's 3C experimental technique to "Hi-C" by Erez Lieberman. The importance of the principle of "structural closeness" in a massively parallel function is elaborated here. The resulting Science cover article (Lieberman, Mirny, Lander, Dekker et al, 2009) experimentally clinched the "fractal globule" of DNA (theoretically predicted by Grosberg et al, 1988, 1993). Already (at 2002, Pellionisz), "FractoGene" utility IP was secured that "genomic fractals are in a cause-effect relationship with fractal growth of organisms" (8,280,641) - a finding corroborated in case of cancer by Mirny et al (2011, see assorted further independent experimental evidence linking fractal defects of the genome to cancer, autism, schizophrenia and autoimmune diseases in Pellionisz 2012). The correlation of genomic variants with cancer therapies is now an exploding area of activities (see Foundation Medicine, with Founding Adviser Eric Lander, and Roche having invested $1Bn into FMI). Nobody claims (any more) any objection against "The Principle of Recursive Genome Function", and "the fractal approach" is now almost taken for granted in the "New School Genomics" (based on fractal/chaotic nonlinear dynamics, with FractoGene just in "patent trolling mode" estimated at $500 M) with an exclusive license value heralded back in 2002 far surpassing this conservative valuation. Andras_at_Pellionisz_dot_com]

The $2 Trillion Trilemma of Global Precision Medicine

As shown below, BGI of China just bought the San Diego-based Irys System, to try to cope with some analytics of the "Dreaded DNA Data Tsunami". Also, Switzerland-based Roche, that acquired Silicon Valley's Genentech for $44 Bn years ago, now bought into Boston-based Foundation Medicine for a $Bn. All this infiltration of the $2 Trillion US Health Care ("Sick Care", rather), is at the time (see news items below) when the USA officially launched their "Precision Medicine" programs. Similar to the Government/Private Sector duel of Human Genome Project (led by Francis Collins/Craig Venter), now Venter's initiative to sequence 1 million humans towards "precision medicine" was announced (see news below), to be closely followed by the competitive US Government Initiative at $215 M in the 2016 budget.

The point is made here that the $2 Trillion traditional Sick Care service of the USA simply can not be transformed into the newfangled "Genome-based Precision Medicine") - unless it is done globally. The trilemma of either the USA, Asia or Europe doing it alone is just not economically feasible.

As the Battelle Report elaborated (see coverage in this column), the $3Bn Human Genome Project (concluding in 2001) generated about $1 Trillion business in the USA alone.

Motivated by earlier and present numbers (and the identical leaders), let's ponder the expected figures of a most likely several decade-long "Global Precision Medicine Program" (with cancer in the focus).

First, in genomics one of the most often cited guestimate for a single human genome is that the present numbers are based on the "one thousand dollar sequencing and a million dollar analysis". Based on this, the two competitive US initiatives will run well over $2 Trillion (just the DNA sequencing might run up a $Bn bill, as 1 M x $1,000= $1 Bn in EACH US-based initiatives). "Precision Medicine" thus appears to be a very noble goal - but not very good mathematics with a US Government budget-proposal of $220 M next year - even if that budget-item would be approved by Congress.

The $2 Trillion ticket appears more interesting in a global sense. China has announced lately "to shop around in the USA for about $2 Trillion worth". Sony has expressed interest in San Diego-based Illumina. Tata Consultants Services are exploring ways of cooperation with the USA for the needed (colossal amount) of software, needed for e.g. fractal genome analytics. Also, investments from Europe (Roche in pharmaceutics, Siemens in medical instrumentation) round up the global picture. Any reform towards "Precision Medicine" of the present USA "Sick care", a vastly lucrative yearly $2 Trillion dollar for-profit business simply represents way too much inertia to adequately respond to small scale initiatives (in the range of couple of hundred milliion dollars). The US faces the trilemma of either going for it alone (extremely unlikely to succeed in a reasonable time-frame), let either Asia or Europe forge ahead and the US just following the trend - or figure out the best ways of global cooperation, also in terms of economy.

Obviously the best resolution for the trilemma is a choreographed cooperation. Especially, since for instance in the disruption from land-line phone systems to smart mobile phone systems such a transition already took place. Some lessons can be directly used. China and India simply skipped development of their land-line phone system and went directly to the supreme technology (with one billion cell phones used in India). Also in China, hospitals are often too far apart - necessitating a "Precision Therapy technology" that is largely IT-based.

Like with the earlier disruption (in phone service), some key innovations will make a crucial difference - for instance the innovation to locate the exact coordinates of the cell phone user. This enables to serve him/her with "precision service" (whenever location is crucial).

Likewise, Information Theory and Technology of Genome Interpretation is presently the most advanced in the USA. Already, this is the most desired essential component of "Precision therapy". By far the most important challenge is (similar to DNA sequencing), to lower the "one million dollar interpretation" price-tag, Moore-Law style.

Clouds, awesome personal computers (disguished as "smart phones") will not listen to anything but (software-enabling) algorithms.

This is what the FractoGene genome interpretation, a double-disruption of overturning the two most fundamental (but wrong) axioms of Genomics accomplished. "Fractal genome governs growth of fractal organisms".

Implementing the "FractoGene Operator" is a new industry, in the footsteps of advanced geometry of nonlinear dynamics.

Is it something that is entire novel? Not at all. Those who figured out how "fractal laws govern the fractal fluctuation of stock-prices" used the software-enabling algorithms and made fortunes.


BGI Pushing for Analytics - Research Documents Rapid Detection of Structural Variation in a Human Genome Using BioNano's Irys System

SAN DIEGO and SHENZHEN, China, Feb. 9, 2015 /PRNewswire/ -- BioNano Genomics, Inc., the leader in genome mapping, and BGI, the world's largest genomics organization, highlight the publication of a peer-reviewed research article and its accompanying data* in GigaScience. This article describes the rapid detection of structural variation in a human genome using the high-throughput, cost-effective genome mapping technology of the Irys® System. Structural variations are known to play an important role in human genetic diversity and disease susceptibility. However, comprehensive, efficient and unbiased discovery of structural variations has previously not been possible through next generation sequencing (NGS) and DNA arrays with their inherent technology limitations.

This study showed that the Irys System was able to detect more than 600 structural variations larger than 1kb in a single human genome. Approximately 30 percent of detected structural variations affected coding regions, responsible for making proteins. Proteins participate in virtually every process within cells, suggesting that these structural variations may have a deep impact on human health. The Irys System also accurately mapped the sequence of a virus that had integrated into the genome. The ability to provide this type of information may help inform how virus sequence integration can lead to diseases such as cancer.

"We found that BioNano's Irys System helps overcome the technological issues that have severely limited our understanding of the human genome," said Xun Xu, deputy director at BGI. "In a matter of days and with fewer than three IrysChip®, we were able to collect enough data for de novo assembly of a human genome and perform comprehensive structural variation detection without additional technologies or multiple library preparations. BioNano has since improved throughput of the Irys System enabling enough data for human genome de novo assembly to be collected in one day on a single IrysChip."

Genome maps built using the Irys System reveal biologically and clinically significant order and orientation of functionally relevant components in complex genomes. This includes genes, promoters, regulatory elements, the length and location of long areas of repeats, as well as viral integration sites.

"The Irys System provides a single, cost-effective technology platform solution to assemble a comprehensive view of a genome and discover and investigate structural variations," said Han Cao, Ph.D., founder and chief scientific officer of BioNano Genomics. "The Irys System enables de novo assembly of genomes containing complex, highly variable regions and accurate detection of all types of structural variation, both balanced and imbalanced, within complex heterogeneous samples."

The Irys System has previously been used to map the 4.7-Mb highly variable human major histocompatibility complex (MHC) region and to enable a de novo assembly of a 2.1-Mb region in the highly complex genome of Aegilops tauschii, one of three progenitor genomes that make up today's wheat.

BGI acquired the Irys System in 2014 to enable comprehensive exploration of structural variation in the human genome and to provide vastly improved assemblies for various organisms that have very complex genomic structure, including those organisms where no reference exists. Together with other available platforms, BGI aims to provide researchers with the most comprehensive information and comprehensive interpretation.

The article is one of the first articles that are part of GigaScience's series Optical Mapping: New Applications, Advances, and Challenges (, and is available through this link:

*The data for this study, as part of the journal's mission of making published research reproducible and data reusable, are available in the Journal's linked database, GigaDB, at

[Francis Collins-based US Government versus Craig Venter-based US Private sector are not in a duel for their sequencing and analysis of 1 million people. BGI, especially when the wholly purchased sequencing technology is fully absorbed (made cheaper, faster, better) than Complete Genomics, quite conceiveably China's BGI with its centralized system combining the advantages of both government-subsidy and global entrepreneurship, could actually beat the two leading US efforts. Don't forget that the Switzerland-based Roche, having acquired Genentech and now Foundation Medicine makes the horse-race at least a foursome. The Shenzhen/San Diego setup of BGI/BioNano Genomics is rather interesting at the outset, not only because of making the sprint truly global, but also because if the found structural variants (no longer SNP-s, but larger than 1kb stretches) are only 30 percent in the coding regions, it means that 70 percent of detected "structural variants" are in the non-coding (in the Old School "Junk") parts of the fractal genome. The "Chinese Solution" to penetrate the vastly lucrative US (cancer) hospital market is also interesting. "They just buy it" - earlier BGI bought the Silicon Valley jewel Complete Genomics to save it from bankruptcy caused by a glut of "dreaded DNA data deluge". In 2014 BGI "just bought the Irys System" (why bother with licensing or infringement?). Incidentally, as calculated below, the true cost of Tsunami (after the 2008 Data Deluge) is estimated at $2 Trillion. This is exactly the Chinese budget to shop around for US technologies and businesses, for about $2 Trillion. andras_at_pellionisz_dot_com]

Round II of "Government vs Private Sector" - or "Is Our Understanding of Genome Regulation Ready for the Dreaded DNA Data Tsunami?"

[News items over the last two weeks, Venter's Private Sector Initiative and the US Government's promise of the same goal (to sequence genomes of 1 million people) inevitably trigger strong memories or earlier markedly similar parallel events. In addition, I warned in my 2008 Google Tech Talk YouTube "Is IT Ready for the Dreaded DNA Data Deluge" that data gathering, in itself, not only falls short of "science" (it is an industry), but if supply of data is not matched with demand might result in unsustainable business model (of DNA sequencing companies). The last seven years have proven that billions of dollars of valuation of "sequencing companies" was lost due to the glut (oversupply) of DNA data without matching analysis. Complete Genomics (a USA-investment, crown jewel of Silicon Valley had to be sold to China for a mere $117M). Data gathering is a necessary, but in itself not a satisfactory ingredient of science. Perhaps the bottom line is best expressed: "Altshuler says. “No amount of genome sequencing would ever lead to a new medicine directly.” The bottleneck is our understanding of genome regulation; Andras_at_Pellionisz_dot_com.]


Who was next to President Obama at the perhaps critical get-together (2011)?

[Almost three years prior to President Obama at shoulder-to-shoulder with a cancer patient (see above, Ms. Elana Simon), Obama had the chance to have next to him another cancer patient (see below, Steve Jobs). The iconic leader of the world's most valuable company (Apple) claimed in his memoirs that perhaps he will be the first cancer patient to be cured by (repeated) genome sequencing & rough preliminary analysis. Or, the last one to die, since sequencing of his genome came too late for him, and too early for science. The Silicon Valley IT-Giants (labeled by "Financetwitter") could have decided in February 2011 in the home of John Doerr at the dinner to launch Calico, Google Genomics and the sequencing (and analysis?) of one million humans. It is unclear if at that dinner this decision was debated, or mentioned at all. (Please let me know, andras_at_pellionisz_dot_com). We all wish that Ms. Elana Simon will not necessarily be the "first" whom genome sequencing and precision medicine will help, but certainly will be among the hundreds of millions who will benefit from this effort. Since just sequencing the genome costs at present $1,000, it is clear that the "sequencing part" of the project (both at the government, and at the private sector) is going to be many billions of dollars. (It is very common these days to quote "one thousand dollar sequencing and one million dollar analytics"; with such rates each of the two competing projects should be planned at the Grand Total well over Two Trillion Dollars. Unless a theoretical (software enabling algorithmic) understanding of fractal recursive genome function will crush the perhaps untenable further two trillion dollar debt to a sustainable expenditure. Earlier, see 2008 YouTube a similar projection was made that unless the dreaded DNA data deluge is matched by appropriate analytics, billions of dollars invested into sequencing technologies would provide an oversupply of data - and billions of dollars of investment will be lost - or sold to China (for $117 M).]

Latest NewsU.S. proposes effort to analyze DNA from 1 million people



WASHINGTON Fri Jan 30, 2015 12:22pm EST(Reuters) - The United States has proposed analyzing genetic information from more than 1 million American volunteers as part of a new initiative to understand human disease and develop medicines targeted to an individual's genetic make-up.

At the heart of the "precision medicine" initiative, announced on Friday by President Barack Obama, is the creation of a pool of people - healthy and ill, men and women, old and young - who would be studied to learn how genetic variants affect health and disease.

Officials hope genetic data from several hundred thousand participants in ongoing genetic studies would be used and other volunteers recruited to reach the 1 million total.

"Precision medicine gives us one of the greatest opportunities for new medical breakthroughs we've ever seen," Obama said, promising that it would "lay a foundation for a new era of life-saving discoveries."

The near-term goal is to create more and better treatments for cancer, Dr. Francis Collins, director of the National Institutes of Health (NIH), told reporters on a conference call on Thursday. Longer term, he said, the project would provide information on how to individualize treatment for a range of diseases.

The initial focus on cancer, he said, reflects the lethality of the disease and the significant advances against cancer that precision medicine has already made, though more work is needed.

The president proposed $215 million in his 2016 budget for the initiative. Of that, $130 million would go to the NIH to fund the research cohort and $70 million to NIH's National Cancer Institute to intensify efforts to identify molecular drivers of cancer and apply that knowledge to drug development.

A further $10 million would go to the Food and Drug Administration to develop databases on which to build an appropriate regulatory structure; $5 million would go to the Office of the National Coordinator for Health Information Technology to develop privacy standards and ensure the secure exchange of data.

The effort may raise alarm bells for privacy rights advocates who have questioned the government's ability to guarantee that DNA information is kept anonymous.

Obama promised that "privacy will be built in from day one."


The funding is not nearly enough to sequence 1 million genomes from scratch. Whole-genome sequencing, though plummeting in price, still costs about $1,000 per genome, Collins said, meaning this component alone would cost $1 billion.

Instead, he said, the national cohort would be assembled both from new volunteers interested in "an opportunity to take part in something historic," and existing cohorts that are already linking genomic data to medical outcomes.

The most ambitious of these is the Million Veteran Program, launched in 2011 by the Department of Veterans Affairs. Aimed at making genomic discoveries and bringing personalized medicine to veterans, it has enrolled more than 300,000 veterans and determined DNA sequences of about 200,000.

The VA was a pioneer in electronic health records, which it will use to link the genotypes to vets' medical histories.

Academic centers have, with NIH funding, also amassed thousands of genomes and linked them to the risk of disease and other health outcomes. The Electronic Medical Records and Genomics Network, announced by NIH in 2007, aims to combine DNA information on more than 300,000 people and look for connections to diseases as varied as autism, appendicitis, cataracts, diabetes and dementia.

In 2014, Regeneron Pharmaceuticals Inc launched a collaboration with Pennsylvania-based Geisinger Health System to sequence the DNA of 100,000 Geisinger patients and, using their anonymous medical records, look for correlations between genes and disease. The company is sequencing 50,000 samples per year, spokeswoman Hala Mirza said.


Perhaps the most audacious effort is by the non-profit Human Longevity Inc, headed by Craig Venter. In 2013 it launched a project to sequence 1 million genomes by 2020. Privately funded, it will be made available to pharmaceutical companies such as Roche Holding AG.

"We're happy to work with them to help move the science," Venter said in an interview, referring to the administration's initiative.

But because of regulations surrounding medical privacy, he said, "we can't just mingle databases. It sounds like a naive assumption" if the White House expects existing cohorts to merge into its 1 million-genomes project.

Venter raced the government-funded Human Genome Project to a draw in 2000, sequencing the entire human genome using private funding in less time than it took the public effort.

Collins conceded that mingling the databases would be a challenge but insisted it is doable.

"It is something that can be achieved but obviously there is a lot that needs to be done," he said.

Collating, analyzing and applying the data to develop drugs will require changes to how products are reviewed and approved by health regulators.

Dr. Margaret Hamburg, the FDA's commissioner, said precision medicine "presents a set of new issues for us at FDA." The agency is discussing new ways to approach the review process for personalized medicines and tests, she added.

(Reporting by Toni Clarke in Washington; Editing by Cynthia Osterman and Leslie Adler)


J. Craig Venter, Ph.D., Co-Founder and CEO, Human Longevity, Inc. (HLI) Participates in White House Precision Medicine Event

Prepared Statement by J. Craig Venter, Ph.D.

LA JOLLA, Calif., Jan. 30, 2015 /PRNewswire/ -- It is gratifying to see that the Obama Administration realizes the great power and potential for genomic science as a means to better understand human biology, and to aid in disease prevention and treatment. I was honored to participate in today's White House event outlining a potential new, government-funded precision medicine program.

Since the 1980s my teams have been focused on advancing the science of genomics—from the first sequenced genome of a free living organism, the first complete human genome, microbiome and synthetic cell— to better all our lives.

We founded HLI in 2013 with the goal of revolutionizing healthcare and medicine by systematically harnessing genomics data to address disease. Our comprehensive database is already in place with thousands of complete human genomes, microbiomes and phenotypic information together with accompanying clinical records, and is enabling the pharmaceutical industry, academics, physicians and patients to use these data to advance understanding about disease and wellness, and to apply them for personalized care.

We envisioned a new era in medicine when we founded HLI in which millions of lives will be improved through genomics and comprehensive phenotype data.

Now, through sequencing and analyzing thousands of genomes with private funds – with the goal of reaching 1 million genomes by 2020 – we believe that we can get a holistic understanding of human biology and the individual.

It is encouraging that the US government is discussing taking a role in a genomic-enabled future, especially funding the Food and Drug Administration (FDA) to develop high-quality, curated databases and develop additional genomic expertise. We agree, though, that there are still significant issues that must be addressed in any government-funded and led precision medicine program. Issues surrounding who will have access to the data, privacy and patient medical/genomic records are some of the most pressing.

We look forward to continuing the dialogue with the Administration, FDA and other stakeholders as this is an important initiative in which government must work hand in hand with the commercial sector and academia.

Additional Background on Human Longevity, Inc.

HLI, a privately held company headquartered in San Diego, CA was founded in 2013 by pioneers in the fields of genomics and stem cell therapy. Using advances in genomic sequencing, the human microbiome, proteomics, informatics, computing, and cell therapy technologies, HLI is building the world's largest and most comprehensive database of human genomic and phenotype data.

The company is also building advanced health centers – called HLI Health Hubs – which will be the embodiment of our philosophies of genomic science-based longevity care – where we will apply this learning and deliver it to the general public for the greatest benefit. Individuals and families will be seen in welcoming environments for one-stop, advanced evaluations (advanced genotype and phenotype analysis including whole body MRI, wireless digital monitoring, etc.). Our first prototype center is slated to open in July 2015 in San Diego, California.


Obama gives East Room rollout to Precision Medicine Initiative

By Jocelyn Kaiser 30 January 2015 4:15 pm 2 Comments

President Barack Obama this morning unveiled the Precision Medicine Initiative he’ll include in his 2016 budget request to a White House East Room audience packed with federal science leaders, academic researchers, patient and research advocacy groups, congressional guests, and drug industry executives. By and large, they seemed to cheer his plan to find ways to use genomics and other molecular information to tailor patient care.

After poking fun at his own knowledge of science—a model of chromosomes made from pink swim noodles “was helpful to me,” he said—Obama explained what precision medicine is: “delivering the right treatments, at the right time, every time to the right person.” Such an approach “gives us one of the greatest opportunities for new medical breakthroughs that we have ever seen,” he added. He went on to describe the $215 million initiative, which includes new support for cancer genomics and molecularly targeted drug trials at the National Cancer Institute (NCI), and a plan to study links among genes, health, and environment in 1 million Americans by pooling participants in existing cohort studies.

“So if we have a big data set—a big pool of people that’s varied—then that allows us to really map out not only the genome of one person, but now we can start seeing connections and patterns and correlations that helps us refine exactly what it is that we’re trying to do with respect to treatment,” the president explained in his 20-minute speech, flanked by a red-and-blue model of the DNA double helix.

In the room were various patients, from Elana Simon, a young survivor of a rare liver cancer who has helped sequence her cancer type, who introduced the president; to towering former basketball great Kareem Abdul-Jabbar, who apparently takes targeted therapy for his leukemia; and cystic fibrosis patient William Elder, a 27-year-old medical student and guest at the State of the Union address who takes a new drug aimed at the genetic flaw underlying his form of the disease.

Representative Diana DeGette (D–CO), who has been working on 21st Century Cures, a plan to speed drug development, and Senator Lamar Alexander (R–TN), who has similar aims, were also present.

Sitting in the front row were the two lieutenants who will carry out the bulk of the precision medicine plan: National Institutes of Health (NIH) Director Francis Collins and NCI Director Harold Varmus. Another attendee was Craig Venter, who led a private effort to sequence the human genome in the late 1990s that competed with a public effort led by Collins. (Fifteen years ago, Venter sat in the same room with Collins when President Bill Clinton announced the first rough draft of the human genome.) Venter is now CEO of a company called Human Longevity Inc. that aims to sequence 1 million participants’ genomes by 2020—a new private competitor to Collins’s federal cohort study, perhaps.

Many other genome-medical biobank projects at academic health centers and companies are clamoring to be part of the 1 million–person cohort study. NIH will begin to explore which studies to include at an 11 to 12 February meeting (agenda here) that will also examine issues ranging from data privacy to using electronic medical records.

Amid all the hoopla, one prominent human geneticist in the audience offered a cautionary note. David Altshuler, who recently left the Broad Institute for Vertex Pharmaceuticals in Boston, which makes Elder’s cystic fibrosis drug, warns that although the new 1 million American cohort study may uncover new possible drug targets, it will be 10 to 15 years before any such discoveries lead to a successful drug.

“This is the first step,” Altshuler says. “No amount of genome sequencing would ever lead to a new medicine directly.”


Pellionisz' 2008 Google Tech YouTube

Forget the genome, Australian scientists crack the 'methylome' for an aggressive type of breast cancer

Sidney Morning Herald

February 3rd, 2015

Decoding the letters of the human genome revolutionised scientists' understanding of the role of genetic mutations in many diseases, including about one in every five cancers.

Now a team of Australian scientists have gone a step further, inventing a way to decipher another layer of information that garnishes genes, called methyl groups, which may explain the cause of many more cancers.

Methyl groups hang off sections of DNA like Christmas lights and act like a switch, affecting how genes are expressed in different cell types. Collectively called the methylome, they can also switch off tumour suppressor genes and switch on cancer promoting genes.

Susan Clark from the Garvan Institute of Medical Research and her team have for first the first time translated the methylome of breast cancer, finding distinct patterns associated with different types of breast cancer.

They have also found a way to classify women with the worst type of breast cancer, triple-negative, into two groups; those with a highly aggressive form and those with a lower-risk variety with a longer survival time. At present there is no reliable way to divide triple-negative cancers, which do not respond to targeted treatment, into these sub-groups.

With further testing, methylation signatures may be used as predictive biomarkers that doctors use to prescribe more appropriate treatments for women diagnosed with breast cancer in the future.

Professor Clark's team are the first in the world to sequence large chunks of the methylome from samples of cancer tissue that had been archived for up to two decades.

Using historical samples meant they could trace which methylation patterns were linked to patient survival times.

Cancer specialist Paul Mainwaring, who was not involved in the research, said Professor Clark's new technique to decode the entire methylome will have significant implications for cancer research in general.

"The power of this technology is that it's allowing us to get a much sharper view on how cancer starts, progresses, metastasizes, behaves and a new avenue of treatment," said Dr Mainwaring from ICON Cancer Care in Brisbane.

"We'll still be talking about this paper in 20 years," he said.

While specific faults in a person's DNA sequence have been shown to increase their risk of certain cancers – the BRCA 2 mutation which significantly increases a woman's chance of developing breast tumours – in about two-thirds of cancers there are no changes to the DNA code.

In many of these cases scientists are finding changes to the genome that do not affect the underlying code, principally through DNA methylation.

"Every cancer has some sort of mutational profile, but there are multiple layers of where those abnormalities can occur. This is a giving us the ability to read one of those layers," he said.

Dr Mainwaring said the exciting part about identifying methylation patterns was that they are potentially reversible.

"It's the bit of the genome we may be able to influence most, certain regions can be changed either by diet, exercise or drugs," he said.

Professor Clark and team's research was funded by the National Breast Cancer Foundation and has been published in the leading scientific journal Nature Communications.

Houston, We've Got a Problem!

[FractoGene, 2002 yielded fractal defect mining, consistent with repeats algorithmically described as pyknon-s by Rigoutsos, 2006 disseminated in Google Tech Talk Youtube 2008, a year before the Hilbert-fractal of genome folding appeared on Science Cover in 2009]

Paraphrasing the infamous alarm so well pictured in "Apollo 13" of the US Space Program, one would be urged to cry out now: "USA Genome Project, "We've Got a Problem!"

One thing is amiss, that there is no "Command Center" to call with the increasingly obvious alarm that even Craig Venter articulated years ago about our that "our concepts of genome regulation are frighteningly unsophisticated". The Old School of genomics with the fairy tale of 1.3% Genes and 98.7% of Junk, with the bad joke by Crick's Central Dogma falsely arbitrating that "protein to DNA recursion can never happen" has now totally unraveled. Yet, the "New School of Hologenomics", based on advanced mathematics of non-linear dynamics is only budding after hardly more than its first decade (hear double-degree biomathematician Eric Schadt).

Whom to alert? Though even very small Countries (see Estonian Genome Project, Latvian Genome Project, etc, etc) have their "National Genome Project", the USA-led international project, that led to the $3Bn sequencing of a single genome, the project expired one-and-a-half Decade ago. Some consider the NIH-led "ENCODE" its continuation (2003-2007, prompted e.g. by my personal debate with Dr. Francis Collins at the 50th Anniversary of the Double Helix, arguing the importance of settlling the very disturbing result that only about 20 thousand genes were found, and according to my 2002 FractoGene 98.7% of the human genome was NOT JUNK). ENCODE-II (2007-2012) was even less of a "continuation". ENCODE-II essentially reinforced the surprise that "the human genome is pervasively transcribed", and attached a suspiciously arbitrary-looking number (80%) for the "functional" parts of the genome (the exons and introns of genes plus vast sees of intergenic non-directly-coding DNA). However, neither the original US-led Human Genome Project, nor ENCODE I-II addressed the basic question of algorithmic interpretation of (recursive) genome function.

In the absence of any overarching "USA Genome Project" (NIHGR, DoE, NSF, DARPA etc. compete for taxpayer dollars, thus by definition their activities are scattered), whom to alert, for instance, that "microexons" (see two articles below) await not only a definition, but are often self-contradictory? For instance, a paper lists "microexons" of 1nt "long". Since "exon" is defined as protein-coding sequence (of triplets of A,C,T,G in an open reading frame), nothing shorter than 3nt can be called "microexon". Since a single base can not code for protein (amino-acid, rather), the referred single nucleotide could well be part of an "intron". The mathematically dual valence of exons, introns and intergenic non-coding DNA was exposed in a Springer Textbook, but the advanced mathematics of e.g. the significance of dual valence (and fractal eigenstates) are not easily digestible for non-mathematically-minded workers. This is most unfortunate, since after the "genome disease" a.k.a cancers now autism established the case that these major diseases are so complex, involving myriads of coding and non-coding DNA structural variants that the recent Newsweek cover applies "You can not cure a disease that you do not understand". By now it is totally clear that neither cancer nor autism could even be cured, and not even understood, without an algorithmic (mathematical) approach to genome regulation. It is commandable, therefore, that one of the leading "agencies" is not at all an "agency" in the government-sector - but the charitable Simons Foundation (headed by the most accomplished mathematician, Jim Simons, who made $Billions with his stock-market algorithms). Mathematics is also not much of a problem for world-leader Information Technology companies (e.g. my Google Youtube points out near to its end that even the Internet is fractal). Thus, Google Genomics, Amazon Web Services, IBM in the USA, and SAP or Siemens in Germany, Samsung, Sony or even TATA in Asia are the entities that are likely to heed (and lucratively profit from) this "alert". One challenge is, that cross-domain expertise (genomics AND informatics) is required, that is presently a still somewhat unusual combination - but advisership is available. Andras_at_Pellionisz_dot_com

Small snippets of genes may have big effects in autism

Print Kate Yandell

22 January 2015

Small pieces of DNA within genes, dubbed ‘microexons,’ are abnormally regulated in people with autism, suggests a study of postmortem brains published 18 December in Cell1. These sequences, some as short as three nucleotides, moderate interactions between key proteins during development.

“The fact that we see frequent misregulation in autism is telling us that these microexons likely play an important role in the development of the disorder,” says lead researcher Benjamin Blencowe, professor of molecular genetics at the University of Toronto.

Genes are made up of DNA sequences called exons, separated by swaths of noncoding DNA. These exons are mixed and matched to form different versions of a protein. This process, called alternative splicing, is thought to be abnormal in autism.

Many sequencing studies tend to skip over microexons because they are not recorded in reference sequences. Although researchers have known about microexons for decades, they were unsure whether the small segments had any widespread purpose.

The new study confirms microexons’ importance, suggesting that these tiny sequences can have big effects on brain development.

“It’s really a new landscape of regulation that’s associated with a disorder,” says Blencowe. “We have a big challenge ahead of us to start dissecting the function of these microexons in more detail.”

Blencowe and his team developed a tool that flags short segments of RNA flanked by sequences that signal splice sites. They used the tool to identify microexons in RNA sequences from various cell types and species throughout development.

In the brain, microexons are highly conserved across people, mice, frogs, zebrafish and other vertebrates. Alternatively spliced microexons are more likely to be present in neurons than in other cell types, suggesting that they have an important, evolutionarily conserved role in neurons.

Irregular splicing:

The researchers analyzed patterns of microexon splicing in the postmortem brains of 12 people with autism and 12 controls between 15 and 60 years of age.

Nearly one-third of alternatively spliced microexons are present at abnormal levels in autism brains compared with control brains, they found. By contrast, only 5 percent of exons longer than 27 nucleotides are differentially spliced in autism brains.

Genes with microexons that are misregulated in autism tend to be involved in the formation of neurons and the function of synapses — the junctions between neurons. Both of these processes are implicated in autism.

Microexons are particularly likely to be misregulated in autism-linked genes, such as SHANK2 and ANK2. What’s more, the expression of a gene called nSR100, which regulates splicing of microexons, is lower in the brains of people with autism than in those of controls.

One future goal is to determine the biology underlying these differences, says Daniel Geschwind, director of the University of California, Los Angeles Center for Autism Research and Treatment. nSR100 belongs to a module of genes that includes transcription factors — which regulate the expression of other genes — and those that modify chromatin, which helps package DNA into the nucleus. Many of these genes have known links to autism.

To look at microexon splicing throughout development, Blencowe and his team sequenced RNA from mouse embryonic stem cells as they differentiated into neurons. Microexon levels tend to spike after the cells finish dividing, hinting at a role in the late stages of neuronal maturation.

Studying microexon regulation at various stages of normal development in people is another logical next step, says Lilia Iakoucheva, assistant professor of psychiatry at the University of California, San Diego, who was not involved in the study. “Then, of course, we can study gene expression in autism brains and then talk about what’s regulated correctly and what’s misregulated.”

As a complement to the postmortem data, the researchers could also look at how microexons are regulated in developing neurons derived from people with autism, says Chaolin Zhang, assistant professor of systems biology at Columbia University in New York, who was not involved in the study.

“We should not underestimate the potential of more detailed characterization of these splicing variants,” he says. “They really expand the genome and [its] complexity in an exponential way.”

Yang Li, a postdoctoral fellow at Stanford University in California also applauds the attention to the microexons. “There’s still not enough recognition that different [forms of proteins] can have very different functions,” he says. “This is especially true in the brain.”

In an independent study published in December in Genome Research, Li and his colleagues reported that microexons in the brain tend to encode amino acids in locations that are likely to affect protein-protein interactions2. They also found that the autism-linked RBFOX gene family regulates microexon splicing in the brain.

“I definitely think that microexons are important because of how conserved they are in terms of brain function,” says Li. “But I don’t know if they cause autism.”

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


1. Irimia M. et al. Cell 159, 1511-1523 (2014) PubMed

2. Li Y.I. et al. Genome Res. 25, 1-13 (2015) PubMed

Autism genomes add to disorder's mystery


Los Angeles Times,

January 26, 2015

Less than a third of siblings with autism shared the same DNA mutations in genes associated with the disorder, according to a new study that is the largest whole-genome sequencing for autism to date.

Canadian researchers sequenced whole genomes from 170 siblings with autism spectrum disorder and both their parents. They found that these sibling pairs shared the same autism-relevant gene variations only about 31% of the time, according to the study published online Monday in the journal Nature Medicine.

More than a third of the mutations believed to be relevant to autism arose in a seemingly random way, the study also found.

“It isn’t really autism; it’s autisms,” said the study’s lead investigator, Dr. Stephen W. Scherer, head of the Center for Applied Genomics, Genetics and Genome Biology at the Hospital for Sick Children in Toronto. In some cases, he added, “it’s like lightning striking twice in the same family.”

The results are part of 1,000 whole genomes that are being made available to researchers via a massive Google database that autism advocates hope will grow to 10 times that size by next year.

The effort, spearheaded by the research and advocacy group Autism Speaks, has been somewhat controversial from the start, with some questioning whether results from the relatively costly and time-consuming process will be too complicated or obscure to yield significant breakthroughs.

Indeed, researchers associated with the effort acknowledged that much of their data remain a mysterious ocean of jumbled, deleted or inserted DNA code, much of which is not located on areas of the genome that program the proteins that directly affect biological functions.

“You might expect that you’d see some commonalities in the mutations between kids in the same family, but that’s actually not the case here,” said Rob Ring, chief science officer of Autism Speaks. “We’re not really sure what might explain that at this time.”

Said Scherer: “We’ve really just scratched the surface of this data.”

That’s where Google’s cloud-based data capabilities will come in, according to Ring and Scherer. Making these whole genomes – potentially 10,000 of them – available to any researcher could yield unexpected connections and order in data that are the equivalent of more than 13 years of streaming high-definition television programming.

Even the more limited data from several hundred genomes sequenced in the study proved difficult to handle. “We couldn’t transfer it over the Internet,” said Scherer. “We had to buy hard drives and Fed-Ex them.”

Autism Speaks hopes the database will attract researchers from varied fields, including those outside of genetics.

“It may be a genetic code as it rolls off of sequencers, but it’s just data and numbers,” Ring said.

Other sequencing studies have examined more children diagnosed with autism, but involved single siblings with the diagnosis and have focused on a narrower part of the genome – a little more than 1% of the genome that codes the proteins that carry out biological processes.

The Canadian study is the largest of so-called "multiplex" families with more than one child diagnosed with the disorder.

The researchers had examined a smaller batch of 32 family genomes in 2013, uncovering damaging variations of four genes not previously correlated to autism spectrum disorder. That study also identified mutations in 17 other known or suspected autism genes. The small variations in DNA coding it found accounted for about 19% of the autism cases, the study found.The current study found autism-relevant mutations in 36 of the 85 families studied. Those mutations were shared by siblings in only 11 of those 36 families, and 10 of those were inherited.

Advocates for whole-genome sequencing argue that their approach picks up all kinds and sizes of mutations, including much smaller additions and deletions of code, than are detected in other forms of sequencing. The study noted that more than 95% of one particular category of coding variation would have been missed by narrower approaches.

The cost and time involved in whole genome sequencing are rapidly declining, while cloud-based computing opens up massive computational power that could potentially make sense of the vast database, advocates say.

Critics have argued that turning up more small oddities may not necessarily be helpful, given that many are so rare that it will be hard to make any statistical sense of them. Even some of the strongest “autism gene” candidates are associated with only a small fraction of autism cases, they note.

Still, genomics is increasingly examining the potential roles of vast stretches of DNA that do not directly code proteins, or that lie outside of genes. Those areas can affect how genes are expressed and how they interact with the environment.

Autism Speaks has committed $50 million to the whole-genome sequencing effort so far, Ring said. The portal to the 1,000 genomes should be in place by the second quarter this year, he said.

Hundreds of Millions Sought for Personalized Medicine Initiative

Jan 26, 2015

US President Barack Obama will seek hundreds of millions of dollars to fund the new personalized medicine initiative he announced in his State of the Union address last week, the New York Times reports.

Such a program would bring about "a new era of medicine  —  one that delivers the right treatment at the right time," Obama said in his speech.

According to the Times, this initiative may have broad, bipartisan support. "This is an incredible area of promise," says Senator Bill Cassidy (R-La.), who is also a gastroenterologist.

The funds would go to both the National Institutes of Health to support biomedical research and to the Food and Drug Administration to regulate diagnostic tests.

Ralph Snyderman, the former chancellor for health affairs at Duke University, tells the Times that he is excited by the prospect of the initiative. "Personalized medicine has the potential to transform our health care system, which consumes almost $3 trillion a year, 80 percent of it for preventable diseases," Snyderman says.

Though new treatments are expensive, Snyderman says personalized therapies will save money, as they will only be given to people for whom they'll work.

[The purpose of "State of the Union Address" by US Presidents is to seek maximally broad-based political support. Thus, most everybody gets a little of the thinly spread promises. However, any "Initiative" would have to be 1) worked out by experts, 2) pushed through (often requiring years) the legislative system of Congress. While according to the above it is questionable how much effect and when such "initiative" might have e.g. on the NIH (with already a thirthy thousand millions of dollars, yearly, thus "hundreds of millions" might barely make a dent with NIH). The Statement might be very useful to stimulate task # 1) (to work out by domain experts the most cost-effective plan). In this regard, in the multiple quality of a) someone whose NIH grant-continuation was cut in 1989 when the colossal disruption by Genomics became a "perceived threat on the establishment" (see acknowledgement in Pellionisz, 1989), b) someone who already contributed to governement-blueprints, see "Decade of the Brain Initiative", c) someone who worked out the mathematical (geometrical) algorithmic approach to unification of neuroscience and genomics (Pellionisz et al, 2013) this worker would add two further improvements that the US government could plan for - if influencing by "hundreds of millions of dollars" the "$3 trillion dollar health care system" is meant as a real catalyzer. First, with the new involvement of the government in health care insurance system, some "catalyzer monies" could be well spent to shape the US health insurance system into the direction of Germany (see news below), France, UK, Canada (where instead of a for-profit "sick care system" health-care is a non-profit government service). Second, (as the news below also clearly indicates), "personalized medicine" will happen by massive involvement of Information Technology giants (SAP in Germany, Google Genomics, Amazon Web Services, IBM etc. in the USA). These monstrous companies, however, typically have a rather hard time embracing "paradigm-shifts" (see the classic best-seller of Christensen "The Innovator's Dilemma"). Indeed, there is a new crop of "personalized medicine start-ups" in the USA (most notably Foundation Medicine in Boston, that is already a post-IPO $Bn business). Government incentives on the scale of "hundreds of millions of dollars" could boost the (existing) "SBIR programs" seeking innovative IT-based solutions for personalized medicine. This is all the more important, since judging from the past history, informatics falls much more into the forte of NSF, DOE, DARPA (etc), rather than the mostly still "old schooler"-dominated NIH. This opinion could be based on the Memoirs of Mandelbrot, that recalls the opportunity "to mathematize biology". The now late Mandelbrot deliberately declined the offer (though it came along with ample funding) since his opinion "biologists were not ready for advanced mathematics" (an opinion he upheld till his passing away; The Fractalist, 2012). This worker would like to note here, that there is also a third, much superior opportunity as well, to be elaborated elsewhere. Andras_at_Pellionisz_dot_com.]

SAP Teams with ASCO to Fight Cancer

[SAP of Germany uses Big Data to fight cancer together with USA - Video]

SAP is teaming with the American Society of Clinical Oncology (ASCO) to develop CancerLinQ, a big data solution that will transform care for cancer patients.The collaboration brings data and expertise from ASCO, a non-profit physician group with over 35,000 members worldwide, onto SAP HANA. CancerLinQ will give doctors new insights in seconds when they are deciding on personalized treatment plans with patients.

[In the USA Health Care ("Sick Care", rather) is well known to be a for-profit business. Thus, it is in the best interest to both hospital systems as well as Pharma to try as many chemo-s on a single patient, as possible. Since 80% of chemos do NOT work for any particular individual, there is a lot of "repeat customer mode" for "sick care" to experiment on humans. This is fortunately not true for countries like Germany, France, UK, Canada (even China...) where Health Care is NOT a for-profit business, but a government-paid public service. For the government budget, it is extremely important for such countries to minimize the ineffective expenditure - and e.g. in Germany that is rich enough to afford expensive cancer-medication but smart and motivated enough to use "Big Data" (genome-matching) to personalize cancer medicine both SAP and Siemens are already engaged in "genome-matched chemo-personalization". In the USA, at least 3 major IT companies (Google Genomics, Amazon/Illumina, IBM/New York Genome Center) already engaged in genome analytics - and e.g. Boston-based Foundation Medicine is already a post-IPO business beyond $Bn valuation). Now the USA is facing an increasingly more potent, and much more motivated competition from Germany, Japan (Riken/Sony), Korea (Samsung) and even China (BGI). While an earlier trend used to be to travel to the USA for the best medical care, these days some cancer patients leave the USA for Germany for more personalized medicine. A key to the best matching is THE ALGORITHM - andras_at_pellionisz_dot_com]

Human Longevity, Genentech Ink Deal to Sequence Thousands of Genomes

Jan 14, 2015 | a GenomeWeb staff reporter

NEW YORK (GenomeWeb) – Human Longevity today announced it has signed a multi-year agreement with Genentech to conduct whole genome sequencing and analysis on tens of thousands of patient samples provided by the drug developer.

Human Longevity will sequence the genomes at 30x coverage with the Illumina HiSeq X Ten machines in its genomic sequencing center, the firm said in a statement.

"We are excited to be working with Genentech so that patient samples can be analyzed according to more precise genetic categories," Human Longevity CEO Craig Venter said in a statement. "The application of our capabilities to discover new diagnostics and targeted therapies is one of the most relevant today."

Genentech Senior VP James Sabry also said that the partnership would advance the firm's drug discovery program.

All sample and patient data elements will be de-identified to protect privacy, the firms added.

Financial details of the agreement were not disclosed.

Human Longevity continues to sign deals giving it more genomes to sequence as it builds its human genotype and phenotype database. Earlier this week, the firm announced it had signed a deal to sequence genomes for the oncology testing firm Personal Genome Diagnostics. In November 2014, the firm signed a deal to gain access to the Twins UK registry and sequence samples from it.

Last week, Genentech signed a deal with 23andMe to sequence the genomes of 3,000 people in the Parkinson's disease community.

[Craig Venter churns it up, again! The announcement is somewhat uncharacteristically understated. The title does not mention that there is no "Genentech" (it is a subsidiary of Roche), and glosses over the brilliance how Craig's latest move towards the private sector put not just Roche, but also Illumina, Amazon and Google into a fiercely competitive mode - serving the interest of science (Craig Venter's style...). Venter rather recently appeared to compete against Google (by snatching Franz Och). As we know, Craig answered the rhetorical question "what's the difference between Celera and God?" by answering "we had computers". IBM wanted to do it for him for free - but he built the largest computer system, instead. Now Illumina could either remain "the King" by providing sequencers - or by a monopoly on algorithms can in addition either catapult Amazon Web Services, or the competitors (Google and/or IBM).The world will never be the same - andras_at_pellionisz_dot_com]

UCSC Receives $1M Grant from Simons Foundation to Create Human Genetic Variation Map

Jan 13, 2015


a GenomeWeb staff reporter

NEW YORK (GenomeWeb) – Researchers at the University of California Santa Cruz's Genomics Institute have received a grant for up to $1 million from the Simons Foundation that will support a one-year pilot project to create a comprehensive map of human genetic variation for biomedical research.

Co-leading the project is David Haussler, a professor of biomolecular engineering and director of the Genomics Institute at UC Santa Cruz, and Benedict Paten, a research scientist at the Genomics Institute.

They'll work with scientists at the Broad Institute, Memorial Sloan Kettering Cancer Center, UC San Francisco, Oxford University, the Wellcome Trust Sanger Institute, and the European Bioinformatics Institute to develop algorithms and formulate the best mathematical approaches for constructing a new graph-based human reference genome structure that will better account for and reflect the different kinds of variation that occur across populations. They'll test algorithms developed as part of the project on tricky parts of the genome within the first six months of the pilot, Paten said in a statement.

The researchers will use a dataset of more than 300 complete and ethnically diverse human genomes sequenced by researchers at the Broad Institute to construct the reference structure and they'll also leverage work done to create a standard data model for the structure by members of the reference variation task team, a subgroup of the data working arm of the Global Alliance for Genomics and Health that Paten co-leads.

The project aims to overcome the limitations of the current model for analyzing human genomic data, which relies on mapping newly sequenced data to a single set of arbitrarily chosen reference sequences resulting in biases and mapping ambiguities. "One exemplary human genome cannot represent humanity as a whole, and the scientific community has not been able to agree on a single precise method to refer to and represent human genome variants," Haussler said in a statement. "There is a great deal we still don't know about human genetic variation because of these problems."

Paten added that the proliferation of different genomic databases within the biomedical research community has resulted in hundreds of specialized coordinate systems and nomenclatures for describing human genetic variation. This poses problems for tools such as the widely used UCSC Genome Browser which was developed and is maintained by UCSC researchers. "For now, all our browser staff can do is to serve the data from these disparate sources in their native, mutually incompatible formats," Paten said in a statement. "This lack of comprehensive integration, coupled with the over-simplicity of the reference model, seriously impedes progress in the science of genomics and its use in medicine."

The diversity of genomes in the Broad's dataset, Paten continued, offers a rich data resource that will be used "to define a comprehensive reference genome structure that can be truly representative of human variation." The plan is eventually to expand the graph-structure to include many more genomes, he said.

The researchers expect to have a draft variation map available by the end of the year. Paten and Haussler have also outlined the follow-up activities needed to extend the pilot project and fully realize their vision for the new map.

The new map will make it easier to detect and analyze both simple and complex variants that contribute to conditions with a genetic component such as autism and diabetes. It will also be a valuable tool for understanding recent human evolution, according to the researchers.

[The news talks about "algorithms" and "maps" (of genomic variations). Given that Jim Simons is a most brilliant mathematician (with autism in the family), it is more likely that he invested this sum, relatively minor on his scale, towards having more "algorithms", rather than just"maps" around. "Pathways" and "maps" already abound - both mathematicians and computers are yearning for software-enabling ALGORITHMS to call genomic variants responsible for human diversity from pathological genomic variants. It is almost self-evident that some variants are "self-similar" - thus one of the many (?) algorithmic approaches might be a measure of self-similarity (fractality). andras_at_pellionisz_dot_com]

Silencing long noncoding RNAs with genome-editing tools with full .pdf.

Methods Mol Biol. 2015;1239:241-50. doi: 10.1007/978-1-4939-1862-1_13.

Gutschner T.


Long noncoding RNAs (lncRNAs) are a functional and structural diverse class of cellular transcripts that comprise the largest fraction of the human transcriptome. However, detailed functional analysis lags behind their rapid discovery. This might be partially due to the lack of loss-of-function approaches that efficiently reduce the expression of these transcripts. Here, I describe a method that allows a specific and efficient targeting of the highly abundant lncRNA MALAT1 in human (lung) cancer cells. The method relies on the site-specific integration of RNA-destabilizing elements mediated by Zinc Finger Nucleases (ZFNs).

See full .pdf of Chapter 13 here

[Genome Editing, an effort that has long been brewing and broke through with full force by 2015 calls for a crucially important "heads up". In earlier times, efforts towards an effective modification of the genome used to be labelled as "Gene Surgery". Thus, some readers may be under the impression that the classic misunderstanding (that the "genome is your destiny and there is no way to change it") needs perhaps only a slight cosmetics; changes of gene(s) (the protein-coding, though not contiguous, but fractally scattered parts of the genome) could, in theory, be altered. This recent paper should totally dispell any such misunderstanding. First, the paper is not even about "genes" and "non-coding DNA" of the genome - but provides an experimentally verifiable method to alter the function of the (mistakenly believed as "function-less" RNA, more particularly of "Long noncoding RNAs (lncRNAs). The effort would be totally misspent if lncRNAs were without important function in genome regulation - critical to cancer(s), in this case lung cancer, one of the most dreadful and rampant diseases. The first words of the abstract, however, clinch that lncRNAs are "a functional and structural diverse class of cellular transcripts that comprise the largest fraction of the human transcriptome". The Fractal Approach (FractoGene), since its inception (concept in 1989 and utility in 2002) has long been kept at bay (in order to delay a humanly and materially very expensive total paradigm-shift as long as possible) by the rationale that "what is the importance of a mathematical (algorithmic) theory of fractal recursive genome function"? For some time the answer was "to find fractal defects in the genome that are in a cause-and-effect relationship with e.g. cancer devepment by misregulation". While in itself the reason has been totally justified (as a recent cover issue in Newsweek on cancer very properly stated "You can not cure a disease that you do not understand" - and scribbling some equations underneath the graphics), with Genome Editing that (also) matured over the "wilderness of genomics" (1953 of Double Helix to end of Encode-2 in 2012), the enormous importance of "fractal defect mining" resulting in "genome editing" can be trivialized even for those in elementary schools. Before "spelling checkers" and "word processors" anybody could write (as this columnist, for whom English is the sixth language...) maybe important sets of letters, but occasionally laden with typos. In natural languages such errors are not nearly as important as e.g. in "computer languages" (codes, rather). Anybody who ever wrote a line of code knows all too well, that a freshly written code (even if it is "interpreted", not "compiled") for best results should undergo the dove-tailing process of "syntax checking" and subsequently the "debugging". (A recursive computer code may produce an infinitely repeating "uncontrolled cycle" is the "stop" symbol is missing or is at an error. While it is common sense that "wash, rinse, repeat" is "meaningful enough", coders itch to add "after repeating the cycle n times, do not cycle it for the n+1 occasion. This trivialization may not be superfluous since it also brings up the question that came back to fashion after 20 years "how similar, or profoundly different are natural languages from the code of recursive genome function". Withouth a serious probe into this question (for which the NIH newly allocated $28 million), perhaps one might want to read & cite (beyond the 28 citation) the full pdf of 2008 peer-reviewed paper on "The Principle of Recursive Genome Function" - andras_at_pellionisz_dot_com]

Long noncoding RNAs (lncRNAs) are a functional and structural diverse class of cellular transcripts that comprise the largest fraction of the human transcriptome. However, detailed functional analysis lags behind their rapid discovery. This might be partially due to the lack of loss-of-function approaches that efficiently reduce the expression of these transcripts. Here, I describe a method that allows a spe- cific and efficient targeting of the highly abundant lncRNA MALAT1 in human (lung) cancer cells. The method relies on the site-specific integration of RNA-destabilizing elements mediated by Zinc Finger Nucleases (ZFNs).

Key words Cancer, CRISPR, Genome engineering, Homologous recombination, MALAT1, LncRNA, Single cell analysis, TALEN, Zinc finger nuclease

1 Introduction

LncRNAs represent a novel and exciting class of transcripts usually defined by their size (>200 nucleotides) and the lack of an open reading frame of significant length (<100 amino acids). Several studies link the expression of these transcripts to human diseases, e.g., cancer [1]. Functional analysis using RNA interference- mediated knockdown approaches are a common strategy to infer a gene’s cellular role. However, these widely used approaches have multiple limitations [2] and might have limited efficiency for lncRNA research due to the intracellular localization (nuclear) and secondary structure of a large fraction of lncRNA molecules.

To overcome these limitations, a novel gene targeting method was developed to reduce the expression of the lncRNA MALAT1 in human A549 lung cancer cells [3]. MALAT1 is a ~8 kb long, highly abundant, nuclear transcript which was originally discov- ered in a screen for lung cancer metastasis associated genes [4, 5]. The targeting method relies on the site-specific integration of a selection marker (here: GFP) and RNA-destabilizing elements or

Shondra M. Pruett-Miller (ed.), Chromosomal Mutagenesis, Methods in Molecular Biology, vol. 1239, DOI 10.1007/978-1-4939-1862-1_13, © Springer Science+Business Media New York 2015


Chapter 13

transcriptional stop signals, e.g., poly(A) signals, into the pro- moter region of the MALAT1 gene. The integration is mediated by ZFNs that specifically introduce a DNA double-strand break (DSB) [6]. The induced DNA damage activates the cellular repair pathways, namely, Nonhomologous end joining (NHEJ) or Homologous Recombination (HR). By providing an appropriate template (donor plasmid) the HR pathway can be used to repair the DSB and to integrate exogenous DNA sequences (Fig. 1). Application of this method to human lung cancer cells yielded a stable, specific and more than 1,000-fold reduction of MALAT1 expression and functional analysis established MALAT1 as an active regulator of lung cancer metastasis [7]. Importantly, the methods’ concept is of broad applicability and allows targeting of protein-coding genes as well as other lncRNAs using any kind of recently developed genome targeting tools, e.g., ZFNs, TALENs, or the CRISPR/Cas9 system.

Store all components according to manufacturer’s recommenda- tions. Use ultrapure water for nucleic acid analysis. ZFNs are com- mercially available from Sigma-Aldrich. Alternative methods were described that allow homemade generation of ZFNs [8, 9] or fast assembly of TALENs [10]. CRISPR/Cas9 plasmids are available from Addgene.


Fok I

ZF ZF2.1 Cloning

1. Plasmid containing a selection marker of choice, e.g., Green fluorescent protein (GFP) followed by a poly(A) signal, e.g., bovine growth hormone (bGH) poly(A) signal.

2. Genomic DNA from cell line(s) subjected to modifications.

3. Genomic DNA isolation kit.

4. Proofreading DNA Polymerase.

5. Cloning primer for homology arms with appropriate restric- tion sites.

6. Agarose and agarose gel chamber. 7. Gel purification kit. 8. Restriction enzymes needed for cloning of homology arms. 9. PCR purification kit.

10. T4 DNA Ligase.

11. Competent bacteria.

12. LB-Medium: 5 g/L yeast extract, 10 g/L Tryptone, 10 g/L NaCl.

13. LB-Agar plates: LB-Medium with 15 g/L Agar. 14. Antibiotics, e.g., Ampicillin, Kanamycin. 15. Plasmid DNA preparation kits.

1. Cell line of choice.

2. Appropriate complete cell culture medium for cell line of inter- est containing supplements, serum, and antibiotics where appropriate.

3. Transfection reagent of choice. 4. Cell culture plates (96-well, 24-well, 6-well, 10 and 15 cm). 5. 0.05 or 0.25 % Trypsin-EDTA. 6. Phosphate-buffered saline (PBS). 7. 12×75 mm tube with cell strainer cap. 8. Conical centrifuge tubes.

1. Cell sorter.

2. Power SYBR Green Cells-to-CT Kit (Life Technologies, Carlsbad, CA, USA).

3. qPCR primer for reference and target gene.

4. DirectPCR lysis reagent (Peqlab, Wilmington, DE, USA) or mammalian genomic DNA MiniPrep Kit.

5. Integration-PCR primer spanning the nuclease cleavage site. 6. DNA-Polymerase of choice suitable for genotyping PCR. 7. PCR strip tubes or 96-well PCR plates and adhesive films. 8. Thermocycler.

2.2 and Transfection

2.3 Analysis

Cell Culture

Single Cell

LncRNA Silencing with ZFNs 243

244 Tony Gutschner

3 Methods

3.1 Cloning of a Donor Plasmid

The targeting approach requires cloning of a donor plasmid (Subheading 3.1), its transfection into cells together with ZFNs (or any other gene editing tool) (Subheading 3.2). After cell expan- sion, cells need to be enriched using Fluorescence Activated Cell Sorting (FACS) (Subheading 3.3). FACS is also used to distribute single cells into 96-wells for clonal growth. Finally, cell clones are analyzed for site-specific integration events and target gene expres- sion levels (Subheading 3.4). See Fig. 2 for a protocol workflow. Design and cloning of gene-specific ZFNs or other gene-editing tools is highly user-specific and will not be covered here.

1. Use proofreading DNA polymerases and genomic DNA to PCR amplify about 800 nt long left and right homology arms (see Note 1).

2. Run PCR program for 30 cycles and with an elongation time of 1 min per 1 kb.

3. Load PCR products on an agarose gel (1 % w/v) and let run at 5–8 V/cm.

4. Purify PCR products using a Gel Extraction kit according to manufacturer’s recommendations. Elute in 30 μL pre-warmed water (50–60°C). Measure concentration of PCR products.

5. Use about 400 ng of PCR product and incubate for 1 h at 37 °C with appropriate restriction enzymes.

6. Purify PCR products using a PCR purification kit according to manufacturer’s recommendations. Elute in 20 μL pre-warmed water (50–60 °C) and determine concentrations.

7. In parallel, prepare the donor plasmid accordingly by digesting and purifying the plasmid with the same reagents and protocols.

8. Clone the first homology arm into the donor plasmid by ligat- ing the PCR product and the prepared plasmid using T4 DNA ligase. Use a 3:1 M ratio (PCR–Plasmid) for optimal ligation efficiency.

9. Transform competent E.coli, e.g., by heat shock (42 °C for 30–45 s, on ice for 2 min)

10. Streak E. coli on LB plates containing appropriate antibiotics.

11. Incubate plates for 12–16 h at 37 °C.

12. Pick single colonies and inoculate 2.5–5 mL LB-Medium con- taining antibiotics.

13. Grow colonies for 8–12 h and isolate plasmid DNA using a Mini-Prep kit.

14. Sequence-verify your clone harboring the first homology arm.





LncRNA Silencing with ZFNs 245 Cloning of ZFNs and donor plasmid

Transfection: ZFN and donor plasmid

Expansion of cells

1st FACS: enrich for GFP+ cells

Expansion of cells

2nd FACS: Single cell sort of GFP+ cells

Expansion of single cells clones

Transfer of clones to 24-well plates

Expansion of single cells clones

Transfer to 96-well and 6-well plates

1-2d 5-10d Genotyping or expression analysis Expansion and storage of clones

Identification of KO clones

Functional analysis of KO clones

Fig. 2 Workflow for lncRNA knockout. Single, homozygous clones can be obtained within 6–8 weeks after ZFN and donor plasmid transfection

15. Continue cloning the second homology arm into the plasmid obtained above.

Repeat steps 7–14 accordingly.

246 Tony Gutschner

3.2 Transfection of ZFNs and Donor Plasmid

3.3 Cell Sorting

16. Use 20–40 μL of starting culture used for Mini-Prep and inoculate 25–35 mL LB-Medium containing antibiotics.

17. Perform Plasmid DNA isolation using a Midi-Prep kit.

The optimal transfection protocol highly depends on the cell line that is subjected to manipulations. Transfection conditions should thus be optimized in advance. The protocol introduced here was successfully applied to human A549 lung cancer cells.

1. 2.


4. 5.

6. 7.


1 . 2. 3.


5. 6.



9. 10.

Seed cells (2–3×105 per 6-well) in 2 mL cell culture medium (+10 % FBS, no antibiotics) (see Note 2).

The next day, prepare plasmid mix by combining 3 μg donor plasmid and 0.5 μg of ZFN plasmid each (1 μg ZFN plasmids in total) (see Note 3).

Combine plasmid mix (4 μg) with 8 μL Turbofect transfection reagent (Thermo Scientific) in serum-/antibiotics-free cell cul- ture medium (final volume = 200 μL). Mix briefly.

Incubate for 15 min at room temperature.

Add transfection mix dropwise to cells and shake plate back and forth for equal distribution.

Incubate cells for 4–6 h with transfection mix.

Remove medium and add fresh, complete growth medium to cells.

Cells might be evaluated for GFP expression prior to further processing.

Expand cells for 10 days after donor and ZFN plasmid transfection.

Remove medium, wash cells once with PBS and add Tr ypsin–EDTA.

Incubate cells at 37 °C and allow for detach (5–15 min).

Resuspend cells in complete cell culture medium and transfer into conical centrifuge tube.

Spin down cells at 500×g for 5 min.

Completely remove cell culture medium and resuspend cell pellet in 2–4 mL PBS/FBS (1 % v/v) by pipetting up and down (see Note 4).

Pipet cells into BD Falcon 12×75 mm Tubes using the cell strainer cap to filter the cell suspension.

Perform steps 2–7 with GFP-negative wild-type cells. Put cells on ice and continue with cell sorting.

Use GFP-negative cells to adjust instrument settings and set threshold for GFP-selection.

3.4 Analysis

11. Perform cell sorting to enrich for GFP-positive cells. Sort cells into 1.5 mL reaction tubes containing 50–100 μL complete cell culture medium (see Note 5).

12. Spin down cells in a tabletop centrifuge (800×g, 5 min) and remove supernatant.

13. Resuspend cells in complete growth medium and seed into appropriate cell culture plates (see Note 6).

14. Expand cells for about 10 days to obtain at least one confluent 10 cm plate for further processing.

15. Add 200 μL complete growth medium per well into 96-well plate. Prepare 5–10 plates per cell line/construct/ZFN (see Note 7).

16. Prepare cells and adjust instrument settings as described in steps 2–10.

17. Sort GFP-positive cells into 96-well plates. GFP-negative wild- type cells might be sorted as well to obtain appropriate nega- tive control clones for subsequent biological experiments.

18. Incubate cells at 37 °C. Add 100 μL complete medium after 5–7 days (see Note 8).

1. About 7–10 days after sorting inspect 96-well plates and mark wells that contain cells.

2. Replace cell culture medium in respective wells by carefully removing the old medium using a 200 μL—pipet and sterile tips.

3. Continuously inspect 96-wells and mark wells that contain cells.

4. About 14–21 days after cell sorting first single cell clones might be ready for transfer into 24-well plates: Remove medium, wash once with PBS and add about 40 μL Trypsin–EDTA per 96-well. After incubation at 37 °C inspect cells for complete detachment. Resuspend cell clones in about 150 μL complete medium and transfer into 24-wells containing additional 500 μL complete growth medium.

5. After another 5–10 days, cells in 24-well plates might be con- fluent and are assigned an identification number. Then, cell clones are simultaneously transferred to 96-well and 6-well plates: Remove medium, wash once with PBS and add about 100 μL Trypsin–EDTA per 24-well. After incubation at 37 °C inspect cells for complete detachment. Resuspend cell clones in about 400 μL complete medium and transfer 100 μL into 96-well and 400 μL into a 6-well containing additional 2 mL complete growth medium.

Cell Clone

LncRNA Silencing with ZFNs 247

248 Tony Gutschner



No Integration

Fig. 3 Genotyping of cell clones by Integration-PCR. Primers cover the ZFN cleavage site. Monoallelic and bial- lelic integration events can be detected due to the different product sizes. In this example, 1 out of 12 clones harbored a biallelic integration of the selection marker after the selection process and thus showed a strong reduction in lncRNA expression (not shown)

4 Notes

6. The next day, cells in 96-wells are subjected to gene expression or genotyping analysis using the Power SYBR Green Cells- to-Ct kit (Life Technologies) or the DirectPCR lysis reagent (Peqlab) or GenElute mammalian genomic DNA MiniPrep Kit (Sigma-Aldrich) according to manufacturer’s recommen- dations respectively.

7. For genotyping analysis an Integration-PCR is performed using primer pairs that span the ZFN cleavage site (see Note 9). A site-directed integration will lead to a longer PCR product (Fig. 3) (see Note 10).

8. Corresponding positive, homozygous clones in the 6-well plates are further expanded and transferred to 10 cm plates (see Note 11).

9. Single cell clones might be frozen and stored in liquid nitrogen.

1. Homology arms should be cloned from the same cell line that will be used for genome editing due to potential single nucleo- tide polymorphisms (SNPs). Homologous recombination strongly depends on perfect homology and can be impaired by SNPs.

2. The cell line(s) used for ZFN-mediated integration of exoge- nous DNA must possess a certain homologous recombination rate. Several cell lines might be tested, if no integration events are detected.

3. Although not absolutely required, linearization of the donor plasmid might increase integration rates. Please note that lin- earized plasmids are less stable and thus a modified transfection

1 kb DNA ladder



LncRNA Silencing with ZFNs 249

protocol might be used. In this case, ZFN plasmids might be transfected prior to the donor plasmid to allow ZFN protein expression.

4. Careful pipetting should be performed to prevent disruption of cells while obtaining a single cell suspension, which is critical for subsequent single cell sorting. Addition of EDTA (1 mM final conc.) to the PBS/1 % FBS solution might be beneficial to prevent cell aggregation.

5. A total of 1–3 % of GFP-positive cells can be anticipated, but this rate might vary and depends on multiple parameters. Depending on the instrument and exact settings up to 4×105 cells can be sorted into one 1.5 mL reaction tube.

6. Antibiotics should be added to the cell culture medium after cell sorting to avoid contaminations.

7. The cell lines’ capability to grow as a single cell colony should be tested beforehand. If a cell sorter (e.g., BD Bioscience FACS Aria II) is used, optimal sorting conditions should be determined in advance. Roughly, 10–40 single cell colonies can be expected per 96-well plate.

8. Some cell lines might show an improved single cell growth, if conditioned medium or medium with higher serum concen- tration is used (max. 20 % v/v). If conditioned medium is used, sterile filter before applying to single cells to avoid contaminations.

9. Alternatively, a Junction-PCR can be performed for genotyp- ing. Here, one primer anneals to a sequence region outside the homology arms and the second primer specifically binds to the newly integrated (exogenous) sequence, e.g., the selection marker (here: GFP).

10. Different amounts of donor plasmid should be tested, if high rates of random, nonspecific donor plasmid integrations are observed, i.e., GFP-positive cells that lack a site-specific inte- gration of the donor plasmid. Also, an efficient counter selec- tion strategy could be applied, e.g., cloning the herpes simplex virus thymidine kinase gene outside the homology arms. Nonspecific integration and expression of this suicide gene confers sensitivity towards ganciclovir [11].

11. In theory, targeted integration on both chromosomes is neces- sary to obtain an efficient gene knockdown. However, cancer cells might show diverse degrees of gene amplifications and deletions. Also, epigenetically silenced or imprinted genes as well as genes localized on the X or Y-chromosomes represent exceptions of the rule. Thus, a single, site-specific integration might already lead to an efficient silencing. On the other hand, multiple integration events must occur simultaneously

250 Tony Gutschner

in human polyploid cells (e.g., hepatocytes, heart muscle cells, megakaryocytes) or in amplified chromosome regions to significantly impair target gene expression.

The author wishes to acknowledge the support of his colleagues at the German Cancer Research Center (DKFZ) Heidelberg who helped to establish this method and to set up the protocol. A spe- cial thanks goes to Matthias Groß and Dr. Monika Hämmerle for critical reading of the manuscript. T.G. is supported by an Odyssey Postdoctoral Fellowship sponsored by the Odyssey Program and the CFP Foundation at The University of Texas MD Anderson Cancer Center.



1. Gutschner T, Diederichs S (2012) The hall- 7. marks of cancer: a long non-coding RNA point of view. RNA Biol 9(6):703–719. doi:10. 4161/rna.20481

2. Jackson AL, Linsley PS (2010) Recognizing and avoiding siRNA off-target effects for tar- get identification and therapeutic application. Nat Rev Drug Discov 9(1):57–67. doi:10.1038/nrd3010 8.

3. Gutschner T, Baas M, Diederichs S (2011) Noncoding RNA gene silencing through genomic integration of RNA destabilizing ele- ments using zinc finger nucleases. Genome Res 21(11):1944–1954. doi:10.1101/gr. 9. 122358.111

4. GutschnerT,HammerleM,DiederichsS(2013) MALAT1—a paradigm for long noncoding RNA function in cancer. J Mol Med 91(7):791– 801. doi:10.1007/s00109-013-1028-y

5. Ji P, Diederichs S, Wang W, Boing S, Metzger R, Schneider PM, Tidow N, Brandt B, Buerger H, Bulk E, Thomas M, Berdel WE, Serve H, Muller-Tidow C (2003) MALAT-1, a novel noncoding RNA, and thymosin beta4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene 22(39):8031– 8041. doi:10.1038/sj.onc.1206928

6. Miller JC, Holmes MC, Wang J, Guschin DY, Lee YL, Rupniewski I, Beausejour CM, Waite AJ, Wang NS, Kim KA, Gregory PD, Pabo CO, Rebar EJ (2007) An improved zinc-finger nuclease architecture for highly specific genome editing. Nat Biotechnol 25(7):778– 785. doi:10.1038/nbt1319

Gutschner T, Hammerle M, Eissmann M, Hsu J, Kim Y, Hung G, Revenko A, Arun G, Stentrup M, Gross M, Zornig M, MacLeod AR, Spector DL, Diederichs S (2013) The non- coding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. Cancer Res 73(3):1180–1189. doi:10.1158/ 0008-5472.CAN-12-2850

Fu F, Voytas DF (2013) Zinc Finger Database (ZiFDB) v2.0: a comprehensive database of C(2)H(2) zinc fingers and engineered zinc finger arrays. Nucleic Acids Res 41(Database issue):D452–D455. doi:10.1093/nar/gks1167

Sander JD, Dahlborg EJ, Goodwin MJ, Cade L, Zhang F, Cifuentes D, Curtin SJ, Blackburn JS, Thibodeau-Beganny S, Qi Y, Pierick CJ, Hoffman E, Maeder ML, Khayter C, Reyon D, Dobbs D, Langenau DM, Stupar RM, Giraldez AJ, Voytas DF, Peterson RT, Yeh JR, Joung JK (2011) Selection-free zinc-finger- nuclease engineering by context-dependent assembly (CoDA). Nat Methods 8(1):67–69. doi:10.1038/nmeth.1542

10. Cermak T, Doyle EL, Christian M, Wang L, Zhang Y, Schmidt C, Baller JA, Somia NV, Bogdanove AJ, Voytas DF (2011) Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting. Nucleic Acids Res 39(12):e82. doi:10.1093/nar/gkr218

11. Moolten FL, Wells JM (1990) Curability of tumors bearing herpes thymidine kinase genes transferred by retroviral vectors. J Natl Cancer Inst 82(4):297–300

Who Owns the Biggest Biotech Discovery of the Century?There’s a bitter fight over the patents for CRISPR, a breakthrough new form of DNA editing.

Control over genome editing could be worth billions. [Yes, there is already ample independent experimental evidence that "fractal defects" of the genome are linked to cancers, schizophrenia, autism, auto-immune diseases (etc). Of course, one needs first to find such "fractal defects"; see US patent in force 8,280,641 - such that one would know what to edit out. FractoGene is a result of "geometrization of genomics". Since mathematization of biology is rarely well received by non-mathematical-minded biologists, result of understanding the sensorimotor coordination function of cerebellar neural nets really broke through not in biology (AJP actually was denied continuation of his grant support since actual mathematics contradicted "Central Dogma" - though Francis Crick confessed later that he did not know either mathematics or what the word "Dogma" actually meant, it just "sounded good"). Since one of the most successful fighter jets in history, the F15 (Israel shot down all enemy aircraft without losing a single F15) could in fact be landed "on one wing" by a superb Israeli pilot, the patent-version of Pellionisz' "Tensor Network Theory" led to automation by NASA, such that landing could be done by any lesser pilot, purely by automation. Geometrization of the function of cerebellar neural net immediately yielded the Alexander von Humboldt Prize from Germany (such that on a 6-months lecture tour in Germany the concepts were widely disseminated, and the inventor faced the trilemma of either switching his professorship at New York University to one in Germany, or his native Hungary - or return to Silicon Valley - today's decisions also include BRICS countries, as the USA is without a streamlined "Genome Program" - genomics is scattered from NIH to NSF and DARPA, DoE and even Homeland Defense). For NASA, it took a decade from the blueprint to actually perform successful implementation. Indeed, intellectual property, especially when university and/or government parties are involved in invention and/or assignment can be mind-boggling, at the time Dr. Pellionisz turned to develop the advanced geometry of recursive genome function, he steered clear of any such cumbersome involvement. This, of course, meant that since the inventor financed the entire development "out of pocket", could not pay for "accelerated issuance" of his patent. It took more than a full decade for the USPTO to understand and to issue the patent 8,280,641 (though, in retrospect, may appear "yeah, sure" to some now - but the patent is in force till late March of 2026). There is a single inventor, and the patent is personal property (assigned to none other than the inventor). Now, some agencies need all the help they can get hard times explaining the $100 million project of "cataloging cancer mutations" (the number is not infinite, given the finite amount of information compressed into the genome, but certainly astronomical, and it makes no sense either scientifically or economically to waste taxpayer's money to "big data" projects that result mostly in prolonged suffering). At least three leading "cloud computing companies" are already set-up for hunting "fractal defects" - with myriads of "wet labs" to hone "genome editing" to clean up genomic glitches. Help is available, given appropriate arrangements - andras_at_pellionisz_dot_com]

By Antonio Regalado on December 4, 2014

Last month in Silicon Valley, biologists Jennifer Doudna and Emmanuelle Charpentier showed up in black gowns to receive the $3 million Breakthrough Prize, a glitzy award put on by Internet billionaires including Mark Zuckerberg. They’d won for developing CRISPR-Cas9, a “powerful and general technology” for editing genomes that’s been hailed as a biotechnology breakthrough.

Not dressing up that night was Feng Zhang (see 35 Innovators Under 35, 2013), a researcher in Cambridge at the MIT-Harvard Broad Institute. But earlier this year Zhang claimed his own reward. In April, he won a broad U.S. patent on CRISPR-Cas9 that could give him and his research center control over just about every important commercial use of the technology.

How did the high-profile prize for CRISPR and the patent on it end up in different hands? That’s a question now at the center of a seething debate over who invented what, and when, that involves three heavily financed startup companies, a half-dozen universities, and thousands of pages of legal documents.

“The intellectual property in this space is pretty complex, to put it nicely,” says Rodger Novak, a former pharmaceutical industry executive who is now CEO of CRISPR Therapeutics, a startup in Basel, Switzerland, that was cofounded by Charpentier. “Everyone knows there are conflicting claims.”

At stake are rights to an invention that may be the most important new genetic engineering technique since the beginning of the biotechnology age in the 1970s. The CRISPR system, dubbed a “search and replace function” for DNA, lets scientists easily disable genes or change their function by replacing DNA letters. During the last few months, scientists have shown that it’s possible to use CRISPR to rid mice of muscular dystrophy, cure them of a rare liver disease, make human cells immune to HIV, and genetically modify monkeys (see “Genome Surgery” and “10 Breakthrough Technologies 2014: Genome Editing”).

No CRISPR drug yet exists. But if CRISPR turns out to be as important as scientists hope, commercial control over the underlying technology could be worth billions.

The control of the patents is crucial to several startups that together quickly raised more than $80 million to turn CRISPR into cures for devastating diseases. They include Editas Medicine and Intellia Therapeutics, both of Cambridge, Massachusetts. Companies expect that clinical trials could begin in as little as three years.

Zhang cofounded Editas Medicine, and this week the startup announced that it had licensed his patent from the Broad Institute. But Editas doesn’t have CRISPR sewn up. That’s because Doudna, a structural biologist at the University of California, Berkeley, was a cofounder of Editas, too. And since Zhang’s patent came out, she’s broken off with the company, and her intellectual property—in the form of her own pending patent—has been licensed to Intellia, a competing startup unveiled only last month. Making matters still more complicated, Charpentier sold her own rights in the same patent application to CRISPR Therapeutics.

In an e-mail, Doudna said she no longer has any involvement with Editas. “I am not part of the company’s team at this point,” she said. Doudna declined to answer further questions, citing the patent dispute.

Few researchers are now willing to discuss the patent fight. Lawsuits are certain and they worry anything they say will be used against them. “The technology has brought a lot of excitement, and there is a lot of pressure, too. What are we going to do? What kind of company do we want?” Charpentier says. “It all sounds very confusing for an outsider, and it’s also quite confusing as an insider.”

Academic labs aren’t waiting for the patent claims to get sorted out. Instead, they are racing to assemble very large engineering teams to perfect and improve the genome-editing technique. On the Boston campus of Harvard’s medical school, for instance, George Church, a specialist in genomics technology, says he now has 30 people in his lab working on it.

Because of all the new research, Zhang says, the importance of any patent, including his own, isn’t entirely clear. “It’s one important piece, but I don’t really pay attention to patents,” he says. “What the final form of this technology is that changes people’s lives may be very different.”

The new gene-editing system was unearthed in bacteria—organisms that use it as a way to identify, and then carve up, the DNA of invading viruses. That work stretched across a decade. Then, in June 2012, a small team led by Doudna and Charpentier published a key paper showing how to turn that natural machinery into a “programmable” editing tool, to cut any DNA strand, at least in a test tube.

The next step was clear—scientists needed to see if the editing magic could work on the genomes of human cells, too. In January 2013, the laboratories of Harvard’s Church and Broad’s Zhang were first to publish papers showing that the answer was yes. Doudna published her own results a few weeks later.

Everyone by then realized that CRISPR might become an immensely flexible way to rewrite DNA, and possibly to treat rare metabolic problems and genetic diseases as diverse as hemophilia and the neurodegenerative disease Huntington’s.

Venture capital groups quickly began trying to recruit the key scientists behind CRISPR, tie up the patents, and form startups. Charpentier threw in with CRISPR Therapeutics in Europe. Doudna had already started a small company, Caribou Biosciences, but in 2013 she joined Zhang and Church as a cofounder of Editas. With $43 million from leading venture funds Third Rock Ventures (see “50 Smartest Companies: Third Rock Ventures”), Polaris Partners, and Flagship Ventures, Editas looked like the dream team of gene-editing startups.

In April of this year, Zhang and the Broad won the first of several sweeping patents that cover using CRISPR in eukaryotes—or any species whose cells contain a nucleus (see “Broad Institute Gets Patent on Revolutionary Gene-Editing Method”). That meant that they’d won the rights to use CRISPR in mice, pigs, cattle, humans—in essence, in every creature other than bacteria.

The patent came as a shock to some. That was because Broad had paid extra to get it reviewed very quickly, in less than six months, and few knew it was coming. Along with the patent came more than 1,000 pages of documents. According to Zhang, Doudna’s predictions in her own earlier patent application that her discovery would work in humans was “mere conjecture” and that, instead, he was the first to show it, in a separate and “surprising” act of invention.

The patent documents have caused consternation. The scientific literature shows that several scientists managed to get CRISPR to work in human cells. In fact, its easy reproducibility in different organisms is the technology’s most exciting hallmark. That would suggest that, in patent terms, it was “obvious” that CRISPR would work in human cells, and that Zhang’s invention might not be worthy of its own patent.

What’s more, there’s scientific credit at stake. In order to show he was “first to invent” the use of CRISPR-Cas in human cells, Zhang supplied snapshots of lab notebooks that he says show he had the system up and running in early 2012, even before Doudna and Charpentier published their results or filed their own patent application. That timeline would mean he hit on the CRISPR-Cas editing system independently. In an interview, Zhang affirmed he’d made the discoveries on his own. Asked what he’d learned from Doudna and Charpentier’s paper, he said “not much.”

Not everyone is convinced. “All I can say is that we did it in my lab with Jennifer Doudna,” says Charpentier, now a professor at the Helmholtz Centre for Infection Research and Hannover Medical School in Germany. “Everything here is very exaggerated because this is one of those unique cases of a technology that people can really pick up easily, and it’s changing researchers’ lives. Things are happening fast, maybe a bit too fast.”

This isn’t the end of the patent fight. Although Broad moved very swiftly, lawyers for Doudna and Charpentier are expected to mount an interference proceeding in the U.S.—that is, a winner-takes-all legal process in which one inventor can take over another’s patent. Who wins will depend on which scientist can produce lab notebooks, e-mails, or documents with the earliest dates.

“I am very confident that the future will clarify the situation,” says Charpentier. “And I would like to believe the story is going to end up well.”

NIH grants aim to decipher the language of gene regulation

Bethesda, Md., Jan. 5, 2015 - The National Institutes of Health has awarded grants of more than $28 million aimed at deciphering the language of how and when genes are turned on and off. These awards emanate from the recently launched Genomics of Gene Regulation (GGR) program of the National Human Genome Research Institute (NHGRI), part of NIH.

"There is a growing realization that the ways genes are regulated to work together can be important for understanding disease," said Mike Pazin, Ph.D., a program director in the Functional Analysis Program in NHGRI's Division of Genome Sciences. "The GGR program aims to develop new ways for understanding how the genes and switches in the genome fit together as networks. Such knowledge is important for defining the role of genomic differences in human health and disease."

With these new grants, researchers will study gene networks and pathways in different systems in the body, such as skin, immune cells and lung. The resulting insights into the mechanisms controlling gene expression may ultimately lead to new avenues for developing treatments for diseases affected by faulty gene regulation, such as cancer, diabetes and Parkinson's disease.

Over the past decade, numerous studies have suggested that genomic regions outside of protein-coding regions harbor variants that play a role in disease. Such regions likely contain gene-control elements that are altered by these variants, which increase the risk for a disease.

"Knowing the interconnections of these regulatory elements is critical for understanding the genomic basis of disease," Dr. Pazin said. "We do not have a good way to predict whether particular regulatory elements are turning genes off or activating them, or whether these elements make genes responsive to a condition, such as infection. We expect these new projects will develop better methods to answer these types of questions using genomic data."

[There is an interesting new scenario. This columnist (AJP; andras_at_pellionisz_dot_com) has devoted close to half a Century of very hard work to develop advanced geometrical understanding of the function of neural and genomic systems, as they arise from their so well known and so beloved structure. Geometrization (mathematization) of biology, however, is rather poorly received (when Mandelbrot was offered to lead, with very significant resources, declined the offer since "biologists were not ready"; Benoit upheld his proper impression through his life, as shown in his Memoirs).

End of cancer-genome project prompts rethink: Geneticists debate whether focus should shift from sequencing genomes to analysing function.

Nature, 2015 January 5.

A mammoth US effort to genetically profile 10,000 tumours has officially come to an end. Started in 2006 as a US$100-million pilot, The Cancer Genome Atlas (TCGA) is now the biggest component of the International Cancer Genome Consortium, a collaboration of scientists from 16 nations that has discovered nearly 10 million cancer-related mutations.

The question is what to do next. Some researchers want to continue the focus on sequencing; others would rather expand their work to explore how the mutations that have been identified influence the development and progression of cancer.

“TCGA should be completed and declared a victory,” says Bruce Stillman, president of Cold Spring Harbor Laboratory in New York. “There will always be new mutations found that are associated with a particular cancer. The question is: what is the cost–benefit ratio?”

Stillman was an early advocate for the project, even as some researchers feared that it would drain funds away from individual grants. Initially a three-year project, it was extended for five more years. In 2009, it received an additional $100 million from the US National Institutes of Health plus $175 million from stimulus funding that was intended to spur the US economy during the global economic recession.

The project initially struggled. At the time, the sequencing technology worked only on fresh tissue that had been frozen rapidly. Yet most clinical biopsies are fixed in paraffin and stained for examination by pathologists. Finding and paying for fresh tissue samples became the programme’s largest expense, says Louis Staudt, director of the Office for Cancer Genomics at the National Cancer Institute (NCI) in Bethesda, Maryland.

Also a problem was the complexity of the data. Although a few ‘drivers’ stood out as likely contributors to the development of cancer, most of the mutations formed a bewildering hodgepodge of genetic oddities, with little commonality between tumours. Tests of drugs that targeted the drivers soon revealed another problem: cancers are often quick to become resistant, typically by activating different genes to bypass whatever cellular process is blocked by the treatment.

Despite those difficulties, nearly every aspect of cancer research has benefited from TCGA, says Bert Vogelstein, a cancer geneticist at Johns Hopkins University in Baltimore, Maryland. The data have yielded new ways to classify tumours and pointed to previously unrecognized drug targets and carcinogens. But some researchers think that sequencing still has a lot to offer. In January, a statistical analysis of the mutation data for 21 cancers showed that sequencing still has the potential to find clinically useful mutations (M. S. Lawrence et al. Nature 505, 495–501; 2014).

On 2 December, Staudt announced that once TCGA is completed, the NCI will continue to intensively sequence tumours in three cancers: ovarian, colorectal and lung adenocarcinoma. It then plans to evaluate the fruits of this extra effort before deciding whether to add back more cancers.

Expanded scope

But this time around, the studies will be able to incorporate detailed clinical information about the patient’s health, treatment history and response to therapies. Because researchers can now use paraffin-embedded samples, they can tap into data from past clinical trials, and study how mutations affect a patient’s prognosis and response to treatment. Staudt says that the NCI will be announcing a call for proposals to sequence samples taken during clinical trials using the methods and analysis pipelines established by the TCGA.

The rest of the International Cancer Gene Consortium, slated to release early plans for a second wave of projects in February, will probably take a similar tack, says co-founder Tom Hudson, president of the Ontario Institute for Cancer Research in Toronto, Canada. A focus on finding sequences that make a tumour responsive to therapy has already been embraced by government funders in several countries eager to rein in health-care costs, he says. “Cancer therapies are very expensive. It’s a priority for us to address which patients would respond to an expensive drug.”

The NCI is also backing the creation of a repository for data not only from its own projects, but also from international efforts. This is intended to bring data access and analysis tools to a wider swathe of researchers, says Staudt. At present, the cancer genomics data constitute about 20 petabytes (1015 bytes), and are so large and unwieldy that only institutions with significant computing power can access them. Even then, it can take four months just to download them.

Stimulus funding cannot be counted on to fuel these plans, acknowledges Staudt. But cheaper sequencing and the ability to use biobanked biopsies should bring down the cost, he says. “Genomics is at the centre of much of what we do in cancer research,” he says. “Now we can ask questions in a more directed way.”

Nature 517, 128–129 (08 January 2015) doi:10.1038/517128a

Variation in cancer risk among tissues can be explained by the number of stem cell divisions

Cristian Tomasetti1,*, Bert Vogelstein2,*

Science 2 January 2015:

Vol. 347 no. 6217 pp. 78-81

DOI: 10.1126/science.1260825

- Author Affiliations

1Division of Biostatistics and Bioinformatics, Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine and Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 550 North Broadway, Baltimore, MD 21205, USA.

2Ludwig Center for Cancer Genetics and Therapeutics and Howard Hughes Medical Institute, Johns Hopkins Kimmel Cancer Center, 1650 Orleans Street, Baltimore, MD 21205, USA.

↵*Corresponding author. E-mail: (C.T.); (B.V.)


Some tissue types give rise to human cancers millions of times more often than other tissue types. Although this has been recognized for more than a century, it has never been explained. Here, we show that the lifetime risk of cancers of many different types is strongly correlated (0.81) with the total number of divisions of the normal self-renewing cells maintaining that tissue’s homeostasis. These results suggest that only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to “bad luck,” that is, random mutations arising during DNA replication in normal, noncancerous stem cells. This is important not only for understanding the disease but also for designing strategies to limit the mortality it causes.


Crunching the numbers to explain cancer

Why do some tissues give rise to cancer in humans a million times more frequently than others? Tomasetti and Vogelstein conclude that these differences can be explained by the number of stem cell divisions. By plotting the lifetime incidence of various cancers against the estimated number of normal stem cell divisions in the corresponding tissues over a lifetime, they found a strong correlation extending over five orders of magnitude. This suggests that random errors occurring during DNA replication in normal stem cells are a major contributing factor in cancer development. Remarkably, this “bad luck” component explains a far greater number of cancers than do hereditary and environmental factors.

Cancer’s Random Assault


New York Times

It may sound flippant to say that many cases of cancer are caused by bad luck, but that is what two scientists suggested in an article published last week in the journal Science. The bad luck comes in the form of random genetic mistakes, or mutations, that happen when healthy cells divide.

Random mutations may account for two-thirds of the risk of getting many types of cancer, leaving the usual suspects — heredity and environmental factors — to account for only one-third, say the authors, Cristian Tomasetti and Dr. Bert Vogelstein, of Johns Hopkins University School of Medicine. “We do think this is a fundamental mechanism, and this is the first time there’s been a measure of it,” said Dr. Tomasetti, an applied mathematician.

Though the researchers suspected that chance had a role, they were surprised at how big it turned out to be.

“This was definitely beyond my expectations,” Dr. Tomasetti said. “It’s about double what I would have thought.”

The finding may be good news to some people, bad news to others, he added.

Smoking greatly increases the risk of lung cancer, but for other cancers, the causes are not clear. And yet many patients wonder if they did something to bring the disease on themselves, or if they could have done something to prevent it.

“For the average cancer patient, I think this is good news,” Dr. Tomasetti said. “Knowing that over all, a lot of it is just bad luck, I think in a sense it’s comforting.”

Among people who do not have cancer, Dr. Tomasetti said he expected there to be two camps.

“There are those who would like to control every single thing happening in their lives, and for those, this may be very scary,” he said. “ ‘There is a big component of cancer I can just do nothing about.’

“For the other part of the population, it’s actually good news. ‘I’m happy. I can of course do all I know that’s important to not increase my risk of cancer, like a good diet, exercise, avoiding smoking, but on the other side, I don’t want to stress out about every single thing or every action I take in my life, or everything I touch or eat.’ ” Dr. Vogelstein said the question of causation had haunted him for decades, since he was an intern and his first patient was a 4-year-old girl with leukemia. Her parents were distraught and wanted to know what had caused the disease. He had no answer, but time and time again heard the same question from patients and their families, particularly parents of children with cancer.

“They think they passed on a bad gene or gave them the wrong foods or exposed them to paint in the garage,” he said. “And it’s just wrong. It gave them a lot of guilt.”

Dr. Tomasetti and Dr. Vogelstein said the finding that so many cases of cancer occur from random genetic accidents means that it may not be possible to prevent them, and that there should be more of an emphasis on developing better tests to find cancers early enough to cure them.

“Cancer leaves signals of its presence, so we just have to basically get smarter about how to find them,” Dr. Tomasetti said.

Their conclusion comes from a statistical model they developed using data in the medical literature on rates of cell division in 31 types of tissue. They looked specifically at stem cells, which are a small, specialized population in each organ or tissue that divide to provide replacements for cells that wear out.

Dividing cells must make copies of their DNA, and errors in the process can set off the uncontrolled growth that leads to cancer.

The researchers wondered if higher rates of stem-cell division might increase the risk of cancer simply by providing more chances for mistakes.

Dr. Vogelstein said research of this type became possible only in recent years, because of advances in the understanding of stem-cell biology.

Continue reading the main story


John 6 hours ago

As my doctors told me, "You're the healthiest guy I've ever seen, except for that life-threatening cancer."

Tim Hunter 7 hours ago

Caused by chance really means "caused by a reason we do not yet understand". I firmly believe that when we live the way we do, surrounded by...

imperato 7 hours ago

So why does a blue whale containing the largest number of cells of any organism on the planet not have a correspondingly high cancer rate?


The analysis did not include breast or prostate cancers, because there was not enough data on rates of stem-cell division in those tissues.

A starting point for their research was an observation made more than 100 years ago but never really explained: Some tissues are far more cancer-prone than others. In the large intestine, for instance, the lifetime cancer risk is 4.8 percent — 24 times higher than in the small intestine, where it is 0.2 percent.

The scientists found that the large intestine has many more stem cells than the small intestine, and that they divide more often: 73 times a year, compared with 24 times. In many other tissues, rates of stem cell division also correlated strongly with cancer risk.

Some cancers, including certain lung and skin cancers, are more common than would be expected just from their rates of stem-cell division — which matches up with the known importance of environmental factors like smoking and sun exposure in those diseases. Others more common than expected were linked to cancer-causing genes. To help explain the findings, Dr. Tomasetti cited the risks of a car accident. In general, the longer the trip, the higher the odds of a crash. Environmental factors like bad weather can add to the basic risk, and so can defects in the car.

“This is a good picture of how I see cancer,” he said. “It’s really the combination of inherited factors, environment and chance. At the base, there is the chance of mutations, to which we add, either because of things we inherited or the environment, our lifestyle.”

Dr. Kenneth Offit, chief of the clinical genetics service at Memorial Sloan Kettering Cancer Center in Manhattan, called the article “an elegant biological explanation of the complex pattern of cancers observed in different human tissues.”

Finding the simple patterns in a complex world (Barnsley: "Cancers are fractals")

An ANU mathematician has developed a new way to uncover simple patterns that might underlie apparently complex systems, such as clouds, cracks in materials or the movement of the stockmarket.

The method, named fractal Fourier analysis, is based on new branch of mathematics called fractal geometry.

The method could help scientists better understand the complicated signals that the body gives out, such as nerve impulses or brain waves.

"It opens up a whole new way of analysing signals," said Professor Michael Barnsley, who presented his work at the New Directions in Fractal Geometry conference at ANU.

"Fractal Geometry is a new branch of mathematics that describes the world as it is, rather than acting as though it's made of straight lines and spheres. There are very few straight lines and circles in nature. The shapes you find in nature are rough."

The new analysis method is closely related to conventional Fourier analysis, which is integral to modern image handling and audio signal processing.

"Fractal Fourier analysis provides a method to break complicated signals up into a set of well understood building blocks, in a similar way to how conventional Fourier analysis breaks signals up into a set of smooth sine waves," Professor Barnsley said.

Professor Barnsley's work draws on the work of Karl Weierstrass from the late 19th Century, who discovered a family of mathematical functions that were continuous, but could not be differentiated

"There are terrific advances to be made by breaking loose from the thrall of continuity and differentiability," Professor Barnsley said.

"The body is full of repeating branch structures – the breathing system, the blood supply system, the arrangement of skin cells, even cancer is a fractal."

[Michael Barnsley - with the founder of the field, Benoit Mandelbrot gone - is a paramount leader of both the mathematics of fractals, as well as its applications. Though the hitherto most lucrative application (fractal prediction of the obviously non-derivable stock-price curves) was not led by either of them (see Elliot Wave Theory), chances are that the required mathematical/algorithmic/software development will call for so significant investment, that "cloud computing companies" might spearhead or even monopolize the industry of FractoGene. Cloud computing provides the capital, infrastructure and the built-in capacity of enforcing royalties for algorithms run on myriads of their servers. 2015 is likely to be the year when the horse-race fully unfolds - andras_at_pellionisz_dot_com ]

A fractal geometric model of prostate carcinoma and classes of equivalence

[There is no need to read the poster - or the paper in print. Just looking at the Broccoli Romanesca (and the Hilbert fractal similarly widespread) will remind everyone by 2015 that "fractal genome grows fractal organisms" (FractoGene). What other concept grasps the essence of Recursive Genome Function? - Pellionisz_dot_com]

The human genome: a multifractal analysis

[The academic (non-profit) publication below was published in 2011 - just a year before the FractoGene patent was issued ("The Utility of Fractal Genome Grows Fractal Organisms, thus correlation of fractal defects explains genome function to yield more precise diagnosis and therapy"). Why re-published this particular article nearing 2015? It seems obvious that "Old School Genomics" has a very hard time in dealing with the "double paradigm-shift" (from "Junk DNA" to FractoGene and from "Central Dogma" to The Principle of Recursive Genome Function). Non-profit entities (and those that do not enter the US market) with the present IP-structure need not be "licensed". However, the tremendous individual efforts need to be encouraged by a suitable reward system for the "New School" to prevail. In a newly lauched blog (separately) we shall collectively work out the most affordable and most encouraging use of the prioneering of Dr. Pellionisz. This, of course, does not exclude the available legal means of licensing for those leading (or even just entering) "for-profit use in the US market" of the utilities inherent in, and protected by issued patent with accompanied trade secrets. -]

Pedro A Moreno1*†, Patricia E Vélez23†, Ember Martínez4, Luis E Garreta1, Néstor Díaz4, Siler Amador4, Irene Tischer1, José M Gutiérrez5, Ashwinikumar K Naik6, Fabián Tobar3 and Felipe García3

* Corresponding author: Pedro A Moreno

† Equal contributors

Author Affiliations

1 Escuela de Ingeniería de Sistemas y Computación, Universidad del Valle, Santiago de Cali, Colombia

2 Profesora del Departamento de Biología, FACNED, Universidad del Cauca, Popayán, Colombia

3 Escuela de Ciencias Básicas. Facultad de Salud, Universidad del Valle, Santiago de Cali, Colombia

4 Departamento de Sistemas, Universidad del Cauca, Popayán, Colombia

5 Instituto de Física de Cantabria, Universidad de Cantabria-CSIC, Santander, España

6 Vaatsalya HealthCare Solutions Pvt Ltd, Bangalore, India

For all author emails, please log on.

BMC Genomics 2011, 12:506 doi:10.1186/1471-2164-12-506

The electronic version of this article is the complete one and can be found online at:

Received: 13 April 2011

Accepted: 14 October 2011

Published: 14 October 2011

© 2011 Moreno et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Formula display:



Several studies have shown that genomes can be studied via a multifractal formalism. Recently, we used a multifractal approach to study the genetic information content of the Caenorhabditis elegans genome. Here we investigate the possibility that the human genome shows a similar behavior to that observed in the nematode.


We report here multifractality in the human genome sequence. This behavior correlates strongly on the presence of Alu elements and to a lesser extent on CpG islands and (G+C) content. In contrast, no or low relationship was found for LINE, MIR, MER, LTRs elements and DNA regions poor in genetic information. Gene function, cluster of orthologous genes, metabolic pathways, and exons tended to increase their frequencies with ranges of multifractality and large gene families were located in genomic regions with varied multifractality. Additionally, a multifractal map and classification for human chromosomes are proposed.


Based on these findings, we propose a descriptive non-linear model for the structure of the human genome, with some biological implications. This model reveals 1) a multifractal regionalization where many regions coexist that are far from equilibrium and 2) this non-linear organization has significant molecular and medical genetic implications for understanding the role of Alu elements in genome stability and structure of the human genome. Given the role of Alu sequences in gene regulation, genetic diseases, human genetic diversity, adaptation and phylogenetic analyses, these quantifications are especially useful.


The human genome is one of the most complex molecular structures ever seen in nature. Its extraordinary information content has revealed a surprising mosaicims between coding and non-coding sequences [1-4]. This highly regionalized structure introduces complex patterns for understanding the gene structure and repetitive DNA sequence composition and its role in human development, physiology, medicine and phylogeny. The coding regions are defined, in part, by an alternative series of motifs responsible for a variety of functions that take place on the DNA and RNA sequences, such as, gene regulation, RNA transcription, RNA splicing, and DNA methylation. For example, sequencing of the human genome revealed a controversial number of interrupted genes (25,000 - 32,000) with their regulatory sequences [1,2] representing about 2% of the genome. These genes are immersed in a giant sea of different types of non-coding sequences which make up around 98% of the genome. The non-coding regions are characterized by many kinds of repetitive DNA sequences, where almost 10.6% of the human genome consists of Alu sequences, a type of SINE (short interspersed elements) sequence [3]. These elements are not randomly distributed throughout the genome but rather are biased toward gene-rich regions [5]. They can act as insertional mutagens and the vast majority appears to be genetically inert [6]. LINES, MIR, MER, LTRs, DNA transposons, and introns are other kinds of non-coding sequences, which together conform about 86% of the genome. In addition, some of these sequences are overlapped one to another, for example, the CpG islands (CGI), which complicates analysis of the genomic landscape. In turn, each chromosome is characterized by some particular properties of structure and function. Furthermore, the new era of rapid sequencing methods will have available more than one thousand human genome sequences [7], which reveals the genetic variation between different human groups. This knowledge will have a major impact on human health (disease origin), population studies and adaptation, among others. All these structural variations are challenging the inventive of theoretical and experimental scientists to create, develop and apply new approaches to quantify them. These variations allow carrying out studies of comparative genomics aimed at discovering correlations with some life characterizing properties [8,9]. Given that all these genomic variations produce a regionalized genomic landscape in the human genome, we thought fractal geometry could be an appropriate approach to studying how the genetic information content is fragmented.

The methodologies derived from fractal geometry have been a very useful approach to studying the degree of fragmentation (or irregularity) in natural, artificial and statistical structures or processes [10]. Fractal structures are characterized by self-similarity, scaling independence, and a fractal dimension, an exponent obtained from a power or scaling law [11,12]. Thus, power laws are powerful tools for searching self-similar properties in biological structures and processes and for quantifying the scaling properties of information contents.

Few studies have used the fractal approach and power laws to study the whole human genome [13,14]. However, due to the complexity of the human genome, one exponent may not be enough to characterize a complex phenomenon. Multifractal formalism allows using more exponents [15]. In this case, the object of analysis is divided into several fractal sets, each generating a fractal dimension that is then translated into a continuous spectrum of exponents (the so-called singularity spectrum). The multifractality degree (MD) obtained from this continuous spectrum allows measuring the genetic information content. Multifractal systems are common in nature, especially in geophysics. They include fully developed turbulence [16], stock market time series, heartbeat dynamics [17], human gait, and natural luminosity time series, among others. In post-genomics times, multifractal analysis has been a very useful approach to studying problems related with microorganism classification [18,19], distinguishing coding and non-coding sequences [20], studying proteins [21], promoter prediction [22], and - recently - this formalism was used to study human chromosomes [23] and the genetic information content in the C. elegans genome [24]. In the latter work, a significant relationship between the structural genetic information content and multifractal parameters was found, which has important biological implications. We thought that applying a similar method could be a valid approach to study the structure of the human genome. In the present paper, we report multifractal analysis from the draft sequence of the human genome.


Three approaches were followed to examine multifractality in the human genome from the Chaos Game Representation (CGR) (Figure 1A).

thumbnailFigure 1. Analyses of multifractal parameters: A: CGR of an H. sapiens chromosome I fragment (~80,000 bp). B: Generalized dimension spectra for two chromosome fragments with the highest (blue) and lowest multifractality (red). A medium multifractality is depicted (green) for comparison. C: Multifractal spectrum τ(q) for the fragments of B. D: Number of chromosome fragments per RM. E: Distribution of 2-D points (Dq (q = 1), Dq (q = -1)) of the human genome. Dq (q = 1) is called the information dimension.

1) Multifractal analysis by chromosome fragment

1.1) Analyses of multifractal parameters

The multifractal parameters for 9,379 chromosome fragments were calculated and analyzed (Additional file 1). Initially, the generalized dimension spectrum and MD for all chromosome fragments were determined. The extreme generalized dimension spectra and a medium spectrum are depicted for comparison (Figure 1B). Note that the maximum varies very little due to the fact that negative q values are associated with the structure and properties of sparse regions, with few points in the CGR of the human genome. In contrast, the Dq minimum varies widely because positive q values emphasize regions where the points are dense.

Additional file 1. Multifractal and molecular parameters for whole human genome. The file contains the Hs_refseq human genome sequence build 36.2 divided by fragments of 300 kb and multifractal and molecular parameters for 9,379 human chromosome fragments. All REs: All repetitive elements.

Format: XLS Size: 9.1MB Download file

This file can be viewed with: Microsoft Excel ViewerOpen Data

Subsequently, the corresponding scaling exponents τ(q) were calculated for each fragment (Additional file 2). The three multifractal spectra τ(q) show differences related to each other (Figure 1C). The scaling exponent τ(q) can reveal aspects of chromosome fragment structure. Monofractal behavior would correspond to a straight line for τ(q); for multifractal behavior, τ(q) is nonlinear. The changing curvature for the data for the chromosome fragments indicates multifractality. In contrast, τ(q) tends to be linear for that chromosome fragment with the lowest multifractality, indicating partial loss of multifractality.

Additional file 2. τ(q) parameters for the human genome. The file contains theτ(q) parameters for 9,379 human chromosome fragments.

Format: RAR Size: 179KB Download fileOpen Data

Using the whole data set for each chromosome we calculated the MD from each generalized dimension spectrum. Thus, the degree of multifractality for all chromosome fragments goes from ~0.79 to 1.56 with an average of 1.042 and median of 1.018 (Additional file 1). Analysis by range of multifractality (RM) reveals that the multifractal behavior for the whole data set is biased toward low multifractal values, as expected (Figure 1D).

Next, we used a discrimination method based on 2-D distributions to study the information dimension for all chromosome fragments. The data show two different informational patterns (similar to a > symbol), one with high information content (Figure 1E, dots on top) and the other with low and medium information content (Figure 1E, dots on bottom) being the occurrence the latter more numerous in data than the former. We hypothesize that these behaviors are related with some molecular parameter, which is analyzed in the following section.

1.2) Analyses of molecular parameters

The annotated contents of coding and non-coding sequences for each fragment were determinated (Additional file 1). These counts were similar to those reported by other studies [1,2] suggesting that our results are consistent at chromosome level. We hypothesize that these multifractal behaviors might be explained by different repetitive DNA contents in the human genome, similar to the results found in C. elegans [24]. Therefore, we examine several molecular density parameters against the MD. We especially focused on the Alu sequence content, given its high polymorphism. We observe 1,078,720 Alu sequences which is equivalent to about 10.58% of the human genome where chromosome fragments contain 0-563 Alu sequences with an average of 115 Alus, i.e., one Alu element for about every 2,600 bp of genomic DNA. We demonstrated how strong the relationship between the MD and Alu content is (Figure 2A).

thumbnailFigure 2. Analyses of molecular parameters: Relationships between the MD versus A: Alu content, R2 ~0.86, p < 0.05 and B: Alu subfamilies: Alu-S (R2 ~0.84, p < 0.05), Alu-J (R2 ~0.7), and Alu-Y (R2 ~0.52). C: Alu content per range of ΔDq. D: Multifractality versus log (CGI), R2 ~0.64, p < 0.05. E: LINE, MIR, MER and LTR contents per RM. F: Distribution of 3-D points (Dq (q = 1), Dq (q = -1), Alu content) of the human genome. We used a cut point ≥ 217.9 Alus (blue dots) according to paragraph 1.4.

This relationship was assessed in terms of Alu families and the Alu-S was found to be more correlated than the other Alu families (Figure 2B). Furthermore, the Alu contents (in conjunction with CGI) are biased toward high multifractal ranges suggesting the significant role of these sequences in determining the non-linearity in the human genome (Figure 2C).

When sequencing the human genome, a strong relationship between Alu and CGI contents [1,2] also became evident. We observe that CGI have a lower multifractal relationship than that found for the Alu elements (Figure 2D). However, when both parameters are combined a significant fit was obtained (R2 = 0.85, p < 0.05). Other molecular parameters such as gene density, exons, introns, LINE, MIR, MER, and LTRs did not show a significant fit by a simple linear regression. However, when all repetitive elements (Alu, LINE, MIR, MER, and LTRs) are taken into account the R2 ~0.57. Thus, among the studied genomic features, Alu has the highest correlation with multifractal degree.

Multivariate analyses of ΔDq versus all variables (Alu, G+C, CGI, LINE, MIR, MER, LTRs, nCoding, nNonCoding, exons, genes, and SNPs) per chromosome were carried out and for each case the most relevant variables explaining ΔDq were selected. The most frequently used variables are (G+C), Alu, CGI, which are significant in 23, 23, 21 cases of the 24 chrs. (Additional file 3). CGI coefficients in all regressions are negative, probably compensating the high positive (G+C) coefficients, given that (G+C) and CGI are strongly correlated (R ~0.805). Positioning Alus among the most relevant variables confirms our prior analyses based on 1 and 2 dimensional regression. In the same way, we analyzed ΔDq for the whole genome, obtaining again (G+C), Alu, CGI as the most relevant variables explaining ΔDq (Additional file 4). Moreover, when the long interspersed repeats are analyzed by RM they tend to be located on low and medium multifractality (LMM) ranges (Figure 2E).

Additional file 3. Multivariate analysis per chromosome. The file contains a significant multivariate analysis per chromosome: consolidated components.

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Additional file 4. Multivariate analysis for all genome. The file contains a significant multivariate analysis for all genome.

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Given that the information dimension studied takes a form of > symbol (Figure 1E), we studied its behavior using a discrimination method based on 3-D distributions. In this analysis, the high information content is related to Alu content, whereas the low and medium information contents are rather related to low Alu contents and other genomic structures (Figure 2F).

1.3) Multifractal map of the human genome

We examined the multifractality and Alu content across the genomic landscape to map these relationships in each human chromosome. The analysis reveals how similarly these two variables behave. This is particularly clear when the determination coefficient for the linear regression is calculated for all chromosomes (Figure 3, Additional file 5). All R2 oscillate between ~0.78 and 0.92, with the exception of chromosomes Y, 21, 19, X, and 11. The apparent low correlation (0.24 ≤ R2 ≤ 0.76) of these chromosomes can be explained by the presence of some atypical chromosomic fragments: they may contain some kind of repeat (chrs. 4, 21, and Y) or present a lack of Alu contents (chrs. 11, 12, and 19). Once these fragments (nine in total) are removed from the analysis, the R2 for all chromosomes improve significantly (0.78 ≤ R2 ≤ 0.92, p < 0.05), including chromosome Y (R2 = 0.52). The chr. 17 has the highest determination coefficient between multifractality and Alu content with chromosome Y having the lowest. With the exception of the atypical chr. Y, these results indicate that multifractality in each human chromosome is dependent on the content of repetitive DNA - type Alu-. Additionally, other determination coefficients for several molecular parameters were calculated in this study (Additional file 5). Thus, among the studied molecular parameters, Alu shows the highest correlation with MD. A multivariate regression analysis also showed a similar result (Additional file 3).

thumbnailFigure 3. Multifractal map of the human genome. Overview between the MD (green) and Alu density (purple) across the human chromosomes. (*): VSTRs.

Additional file 5. Determination coefficients per chromosome. The file contains determination coefficients per chromosome between the MD versus several molecular parameters. NCFs: Number of chromosome fragments. NRCF: Number of removed chr. fragments. R2 are indicated as R^2. The seventh column shows the corrected R2 when nine data (sixth column) from the second column are removed from the analyses. (r): for 1 or 2 chromosomic fragments, few Alu content and high multifractality and (0): for 1 chromosomic fragment without Alu content. *: See Figure 3. All REs: All repetitive elements.

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Given that other repetitive elements could contribute to increase the local multifractality, five chromosome fragments with a low number of Alus and high MD in chromosomes 4, 21, and Y called our attention (Figure 3, asterisks, Additional file 5). We analyzed these sequences and found many variable short repeats in tandem (VSRTs) (Additional file 6). Thus, the presence of these repeats increases local multifractality but reduces the entire chromosome multifractality for these chromosomes, as mentioned before.

Additional file 6. VSTRs sequences. The file contains chromosome fragment sequences with VSRTs for chromosomes 21 and Y.

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1.4) Chromosomal location of the most multifractal chromosome fragments

Human genome sequencing revealed that chromosomes 19, 16, 17, and 22 are richer in genes, CGI, and Alu elements [1]. Based on averages for ΔDq and Alus for these chromosomes we defined a threshold for chromosome fragments as ΔDq ≥ 1.159 and Alu contents ≥ 217.9 (Additional file 7). This allows to separate chromosome fragments with the highest multifractality from those with LMM (Additional file 8). A discrimination method based on distributions of 3-D points shows how both groups of chromosome fragments can be easily differentiated (Figure 4A). The plot reveals that the highest multifractality and Alu contents are observed in 1,292 fragments suggesting the existence of an abundant number of multifractal regions in the human genome with an average multifractality around 1.24 and an average of ~305 Alus. As expected, many fragments (~29%) are located on chromosomes 19, 17, 16, and 22, respectively (Figure 4B, above). Similar results were obtained by using a 3-D plot with MD-Alu-Dq(q = 1) (data not shown). Chromosome fragments with LMM and low Alu contents, in contrast, are situated mainly on the other chromosomes (~86.2%), being chromosomes 4, 13, 18, 5, and Y those with the lowest multifractality (Figure 4B, below), an average multifractality of 1.0, and average Alu of ~79.

Additional file 7. The most multifractal chromosome fragments in the human genome. The file contains genomic location of the most multifractal chromosome fragments.

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Additional file 8. Chromosome fragments with LMM. The file contains a threshold definition and genomic location for the chromosome fragments with LMM.

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thumbnailFigure 4. Genomic location of the most multifractal chromosome fragments: A: Discrimination method based on three parameters. Each chromosome fragment dataset is characterized by three quantities. The first quantity (x-axis) is the MD for each chromosomic fragment. The second quantity (y-axis) is the density of Alu content of the chromosomic fragments. The third quantity (z-axis) is the correlation coefficient τ(q). Blue color indicates those fragments with ΔDq ≥ 1.159 and Alu contents ≥ 217.9. B: Above, distribution for chromosome fragments with high multifractality and below, for fragments with LMM.

1.5) Analyses by gene function, gene family, and gene length

One would expect to find other molecular characteristics of the gene associated with the multifractality; hence other related molecular parameters were examined. Several biased distributions toward high ranges of multifractality for gene functions, cluster of orthologous genes (KOGS), metabolic pathways (KEGGs), and number of exons were found (Figure 5A, Additional file 9). We only found gene function information for 5,823 chromosome fragments with an average multifractality degree (AMD) of 1.126 and median of 1.132. For example, many genes for the cell division cycle lie on chromosome fragments with an AMD of 1.203; many genes of the major histocompatibility complex, classes I and II are situated on fragments with AMD = 1.06; and many members of the melanoma antigen family lie on fragments with AMD = 0.96 to mention a few.

thumbnailFigure 5. Distributions by gene function, gene family, and gene length: A: Gene functional distributions per RM. These distributions are strongly significant up to 80% of the ranges. B: Percentage of gene families per RM. Gene families: CA: Carbonic anhydrase, CD: cluster of differentiation, GPR: G protein-coupled receptors, KCN: potassium channels, OR: olfactory receptor, RPS: ribosomal proteins, SLC: solute carrier, SNORA: small nucleolar RNA, USP: ubiquitin-specific peptidases, ZNF: Zinc fingers, C2H2-type. C: Degree of gene fragmentation per RM. AGL: average of gene length, R2 ~0.55. AEL: average of exon length, R2 ~0.91. AIL: average of intron length, R2 ~0.74.

Additional file 9. Gene function versus RM. The file contains the analyses by gene functions, KEGGs, KOGs and exons versus RM.

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To gain further insights into the gene function, we focused on about 208 human gene families, consisting of 4,614 genes [25,26]. We asked about the multifractal genomic context for these gene families. The distributions obtained show three different multifractal behaviors (Figure 5B): low-skewed (for OR, KCN, HLA, IFN, KRT, CDH, and RGS), high-skewed (for ZNF, SNORA, USP, RPS, SNORD, GTF, DHX, ALOX, and UBE2), and "medium" for most gene families. Other gene families can be placed within some of these categories (Additional file 10).

Additional file 10. Gene family versus RM. The file contains the analysis of gene family versus RM.

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When multifractality is related to the information content (for example, number of exons, Figure 5A), it is expected that the more genetic information exists, the greater is the extent of genetic information fragmentation. To verify this assumption we looked for the average lengths of genes, exons, and introns in relation to the RM. The three corresponding distributions show how the average lengths decrease as multifractality increases (Figure 5C, Additional file 11). Another approach to validate this assumption is to observe the number of information units (IU) (exons plus introns) per RM. Here, the distribution shows that the number of IUs increases when the RM increases (data not shown).

Additional file 11. Gene length versus RM. The file contains the analysis of gene length versus RM.

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2) Multifractal analysis by chromosome

We next explored the multifractal behavior of each chromosome. We found that the AMD and Alu content profiles have very similar behaviors (Figure 6A). This is particularly evident when observing how well these two variables fit (Figure 6B, Additional file 12). Following the linear regression line, three groups of chromosomes can be distinguished (by visual inspection): a first group where chromosomes 19, 17, 22, and 16 exhibit the highest multifractality (and the highest Alu contents), a second group consist of chromosomes 15, 20, 1, 10, 12, 9, 7, 14, and 21 with medium multifractality, and a third group of chromosomes 2, 11, 8, 6, Y, 3, 18, 5, 13, X, and 4 with the lowest multifractality, respectively. A similar analysis showed that the CGI were also highly correlated with the AMD (R2 ~0.86, p < 0.05) (Additional file 13).

thumbnailFigure 6. Multifractal classification for the human chromosomes: A: Distributions of the average degree of multifractality (Av. ΔDq) and Alu content per chromosome. B: Discrimination method based on multifractal formalism in a distribution of two-dimensional points, R2 ~0.967, p < 0.05. On top: hierarchical clustering for the averaged multifractal parameters by chromosome between Dq(-20, 20) (color scale bar is indicated). Minimum similarities are indicated near nodes and the asterisks show the only two exceptions found.

Additional file 12. Averaged multifractality versus Alus. The file contains averaged ΔDq versus averaged Alus per chromosome.

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Additional file 13. Averaged multifractality versus CGI. The file contains averaged ΔDq versus averaged CGI per chromosome.

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We asked whether this subjective classification could be obtained by hierarchical clustering of the complete data set of averaged multifractal parameters, using multifractality as a similarity measure (Additional file 14). The clustering process classified the chromosomes into three multifractality groups (on top of Figure 6B), with among group similarities of 0.84 and 0.4, respectively: low, medium and high confirming (in part) the visual observation. Nearly all chromosomes (92%) lie on the consecutive, visually identified low, medium and high sections on the regression line. The only exceptions are chromosomes 22 and Y, which are placed in other groups.

Additional file 14. Multifractality and hierarchical clustering analysis. The file contains the averaged multifractal parameters per chromosome for hierarchical clustering analysis.

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3) Multifractal analysis by average of chromosome regions

Analysis by chromosome region proved to be a valid approach to study the genetic information content in the C. elegans genome [24]. Here, we applied the same approach to analyze several characteristics of the human genome. It is known that chromosome 21, involved in Down syndrome, shows a degree of asymmetric regionalization in the distribution of the Alu elements (Figure 3) [1,2]. We hypothesized that one part of chromosome 21 should have low multifractality and the other one high multifractality. Indeed, the data show that the first 50% of chromosome 21 is of low multifractality (< 1.0), whereas the other 50% has a higher multifractality (> 1.08) (Figure 7A, Additional file 15).

thumbnailFigure 7. Multifractality per average of chromosome región: A: Multifractal distribution per chromosome, where each chr. region (each bar) has an equal length. Blue color represents those chromosome regions with high averaged multifractality (ΔDq > 1.04). Degraded blue-red color depicts medium multifractality (ΔDq ≤ 1.04). Red color: low multifractality. B: Correspondence between averages of gene, CGI (R2 ~0.62, p < 0.05) and Alu (R2 ~0.95, p < 0.05) contents versus averaged multifractality across the human chromosome 1.

Additional file 15. Chr 21 multifractal analysis by regions. The file contains multifractal parameters by averaged region of chromosome 21.

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Other relevant characteristics are observed in some chromosome bands and arms (Figure 7A). For example, the X chromosome, involved in X chromosome inactivation (XCI), which is rich in LINE1 elements and poor in Alu sequences showed a 0.95 ≤ ΔDq ≤ 1.027 (Additional file 16). The Y chromosome has two particular regions to the Yp and Yq ends, the pseudoautosomal region and the palindromic region, respectively [1]. We thought that the palindromic regions should have low multifractality because of their symmetric structure. We found, in fact, that this region has lowered non-linearity. Moreover, recombination rates in chromosome 8 tend to be much higher in distal regions (around 20 Mb) [1] and the analysis showed medium non-linearity at this region as expected (Additional file 17). Regarding chromosome 1, rich in Alu sequences in one of its arms [27], we found significantly high multifractality (~1.13) at this region; in contrast, the other three regions have a ΔDq ≤ 1.058 (Additional file 18). Similar situations can be analyzed for other chromosomes. As two opposing references we use chromosomes 4 and 19 for comparison (Additional file 19).

Additional file 16. Chrs X and Y multifractal analyses by regions. The file contains multifractal parameters by averaged region of chromosome X and Y.

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Additional file 17. Chr 8 multifractal analysis by regions. The file contains multifractal parameters by averaged region of chromosome 8.

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Additional file 18. Chr 1 multifractal analysis by regions. The file contains multifractal parameters by averaged region of chromosome 1.

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Additional file 19. Chrs 4 and 19 multifractal analyses by regions. The file contains multifractal parameters by averaged region of chromosomes 4 and 19.

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Antibodies to histone modifications previously linked to active transcription, showed close correspondence to regions rich in genes and CGI in human methaphase epigenome [28]. We analyzed chr. 1 and found that CGI profiles correspond well to multifractality (Figure 7B, Additional file 20).

Additional file 20. Averaged CGI versus multifractality of chr. 1. The file contains averaged CGI versus averaged multifractality of chromosome 1.

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We discovered a strong relationship between the multifractal parameters and part of the genetic information coded by the human genome.

Initially, the multifractality in human genome was found strongly dependent on the Alu contents

Herein, thousands of chromosome fragments with multifractality ranging from low to high values were analyzed (Figure 1A-C). For all chromosome fragments, τ(q) is a nonlinear function (Figure 1C), indicating that the molecular structure of the chromosome fragments has a multifractal behavior. However, in many chromosome fragments, τ(q) tends to be close to linear behavior, especially for τ(q≥2), indicating partial loss of multifractality. These results suggest that nucleotide fluctuations are less anti-correlated in many chromosome fragments. In fact, the fragment distribution is biased toward low and medium multifractal values (Figure 1D), suggesting that the human genome has a large number of regularly arranged elements, highly periodic and not very polymorphic. This is not surprising because the human genome has about 98.9% of non-coding sequences with a complex composition given by introns and intergenic regions. That is, at least 55% of this information is poorly polymorphic given that these regions mainly consist of introns, LINEs (especially L1), LTRs and DNA transposons [1,2]. In contrast, the human genome also has a significant number of chromosome fragments with high multifractality (Figure 1D). That means these regions should be rich in specific types of sequences that are highly polymorphic and organized in a large number of possible combinations. When the information dimension was analyzed a dual informational behavior confirmed such assumption (Figure 1E). Indeed, the multifractality was found to be strongly correlated with the Alu content (Figure 2A), which became visible when plotted against the information dimension (Figure 2F). This result is very significant given that the Alu family is highly polymorphic [29,30] and in a 300 kb chromosome fragment one can find Alu elements in many combinations in up to 50% of its length. The Alu elements are not identical and can be classified into three major families: Alu-J, Alu-S and Alu-Y representing the oldest, intermediate, and youngest Alus, respectively and each family is divided into one or more levels of subfamilies [31]. In total, ~45 subfamilies encompass the complete Alu family. We found that multifractality was mainly dependent on the Alu-S contents (Figure 2B), especially the Alu-Sx, an expected result since these sequences are the most abundant Alu members in the human genome [1]. Analysis via RM confirmed that the Alu sequences tend to be located toward medium and high ranges of multifractality (Figure 2C) because of the high Alu content in the human genome.

The CGI showed a moderate relationship with the multifractality (Figure 2C, D), which might be because more than 95% of CGI are less than 1,800 pb long [1]. Genes, exons, introns, LINES, MIR, MER and LTR contents did not show any significant relationship with the multifractality because most of these sequences have a low number of members, are large and have few polymorphisms. For example, LINE elements are ~6 kb long, more numerous than Alus and consist of four families, being LINE-1 the most abundant family (~17%) in the genome [32], and their density pattern is quite uniform for most chromosomes [1]. Thus, the combination of number of members, size and polymorphism seem to be determining characteristics for multifractality changes. The earlier mentioned abundant number of polymorphic Alu sequences confirms the relation between these characteristics and multifractality. In fact, an in silico comparative genomics study between public and Celera versions of human genome sequences identifies several hundred new Alu insertion polymorphisms, showing that these elements are highly polymorphics [31]. A similar behavior is found in C. elegans where the TTAGGC repeat is abundant in number and combinations within the flanking sequences [24].

Subsequently, we elaborated a multifractal map of the human genome (Figure 3), which shows MD and Alu density along the human chromosomes. The map reveals that the human chromosomes contain many significant correlation structures for Alu-rich regions. Thus, the high contents of Alu account for the high aperiodicity and genetic variability of many chromosome sections. A similar result in C. elegans reported changes in multifractality related to a specific type of repetitive DNA [24]. Additionally, the correlations for CGI are lower but significant. However, no significant correspondence was found in regions poor in Alu sequences and rich in LINE, MIR, MER and LTR sequences. Not all multifractality is due to the Alu contents, many VSTRs can also contribute to increasing local multifractality (Figure 3, asterisks). We found very poor correspondence to the number of genes perhaps due to their low frequency. These results, taken together, indicate that the observed multifractality is primarily related to nonlinear distributions for those chromosome fragments which are rich in Alu sequences, next for those with high CGI content and in few instances, for those with high VSRT contents.

Hundreds of highly multifractal chromosome fragments mapped in chromosomes rich in genetic information

There were a large number of chromosome fragments with very high multifractality (Figure 4A), mainly located on chromosomes 19, 17, 22, and 16 (Figure 4B, above). All of these chromosome sections, so we suggest, generate a mosaic of regions locating the genetic information far from equilibrium [17,24], which could be interpreted both, as a protector "shield" for the human genome against environmental fluctuations and as "genomic attractors" to maintain many components, functions and processes under a "deterministic" genomic control. In contrast, the same analysis also identified thousands of LMM chromosome fragments (Figure 2C) with low Alu content (Figure 4B, below) and perhaps prone to being affected by the environment. This result might be interpreted as some genome sections with low nonlinearity that might have high genetic instability associated with some particular (structural or functional) gene property.

Several gene characteristics are related to multifractality

This is not striking since three-fourths of all genes in the genome are associated with Alus (Figure 5A) [30]. Therefore, some gene families tend to be located preferentially within a multifractal genomic context (Figure 5B). For example, the hOR gene family lies mainly on a low multifractal genomic context. This is due to this family has a very periodic and repetitive structure. It is known that the OR gene family has about 390 active members which were propagated on the genome by gene duplication. Hence they share a high homology due to their high structural homogeneity and possess many clusters of regular characteristics; nonetheless, their functional expression depends on a complex interplay between regulatory sequences and the environment [33]. A similar behavior is observed in the KCN gene family, responsible for building potassium channels for cell communication. In contrast, the ZNF gene family, which codes for regulatory proteins and is, therefore, involved in many cellular functions, is located in a medium and high multifractal genomic context. For example, the ZEB2 protein involved in a chemical signaling pathway regulates early growth and development and obeys a pre-determinate genetic program. In addition, these genes have a high structural inhomogeneity and many irregular characteristics. Similar inferences might apply for the RPS gene family, which codes for highly conserved proteins for the ribosome, for the SNORA machinery involved in the nuclear splicing and for USPs that help to control the levels of many proteins in the cell [26]. This seems to suggest that the low multifractal genetic context might be related to information inputs from environmental processes, and the high one to inputs from deterministic processes. Thus, a few gene families in the human genome might be subjected to two types of information (or stimulus) inputs, while most gene families seem to be subjected to a complex regulatory interplay between epigenetic and genetic controls.

On the other hand, the degree of gene fragmentation by RM (Figure 5C) behaves according to the multifractal theory: multifractality increases when the length of exons and introns in the human genome decreases and the number of IUs per interrupted gene increases with multifractality, as expected.

The multifractal approach per chromosome permitted classifying the human chromosomes. This analysisvalidated the strong relationship to the Alu elements (Figure 6) we found especially for chromosomes 19, 17, 22, and 16, which are rich in genetic information content [1,2]. Particularly chromosome 19 is by far the most multifractal chromosome and has the highest gene density of the whole genome. It is also unusual with respect to its density of repeat sequences. In fact, nearly 55% of this chromosome consists of repetitive elements, whereas chromosomes 6, 7, 14, 20, 21 and 22 all have repeat contents ranging from 40% to 46% (the genome average is 44.8%). This difference is due mainly to an unusually high content of SINEs in chromosome 19 [1]. In contrast, chromosomes 13, X, and 4 have the lowest multifractality because their Alu content is lower than the autosomal average, they have low gene density. Some of these chromosomes have very large "gene deserts" and the CGI and LINE contents are the highest percentage among all autosomes [1,30]. A similar behavior can be observed for chromosomes 19, 17, and 4, as reported in a recent multifractal analysis [23].

Our analysis permits classifying human chromosomes into three multifractality groups suggesting that the chromosome molecular structure might be organized as a system operating far from equilibrium [24] (Figure 6B). Thus, those chromosomes with low multifractality might be closer to equilibrium and have greater genetic instability. If so, this would explain, why some chromosomes would be involved in some genomic disorders (structural and numerical chromosome alterations)[34]. For example, some microdeletion syndromes have been reported for chr. 4: Wolf-Hirschhorn syndrome, chr. 5: Cri du chat syndrome and chr. 15: Angelman and Prader-Willi syndromes. Some aneuploids can be present in chr. 8: Syndrome of Warkany, chr. 13: Patau syndrome, chr. 18: Edward syndrome, chr. 21: Down syndrome, chr. X: Turner syndrome (XO), Klinefelter syndrome (XXY), triple X syndrome and other tetra and pentaploids of chr. X. For chr. Y: XYY syndrome and Turner syndrome. With the exception of chromosomes 21 and Y, all were classified as chromosomes with low multifractality and are more susceptible to genetic damages or a wrong meiotic segregation.

The multifractal approach by chromosome region reveals different genomic scenarios (Figure 7A)

For instance, 21 chromosome regions with low multifractality might promote genetic instability during meiotic segregation in Down syndrome. Similar behaviors might arise for chromosomes X and Y to explain XCI and sex determination. For example, the most remarkable enrichment of repetitive sequences obtained for L1, which accounts for 29% of the X chromosome sequence compared to the average of only 17% [1]. Some studies have reported significant association between L1 and coverage and inactivation, and others have refuted this result [35]. However, the low multifractality, especially at the third region (AMD ~0.96) may be prone to XCI. With regard to chromosome Y, the pseudoautosomal region is more stable, while the palindromic (more periodic) region is unstable and more prone to producing some genetic disorder such as the mixed gonadal dysgenesis and infertility [1,34]. On the contrary, the 8p region in which a vast section of ~15 Mb has a strikingly high mutation rate lay on a medium multifractality region [36]. Similar behavior can be inferred in the C. elegans chromosome arms, rich in mutation rates [24].

A similar approach showed that the CGI and Alus correspond well to multifractality (Figure 7B). This result is significant because of the role that CGI play in heritability of epigenetic states during the active transcription or modifications associated with active chromatin [28].

Finally, we propose a descriptive, non linear model for the function and organization of the human genome (Figure 8)

Firstly, several studies have suggested that multifractal systems might be organized as systems operating far from equilibrium [16,17,24]. Thus, the detection of a multifractal scaling in the human genome structure suggests that its molecular structure might be organized as a system operating far from equilibrium, meaning that no variable describing the state of the system shows a regular repetition of values. The high multifractality which strongly depends on Alu contents (and upon CGI to a lesser degree) and is located mainly in highly aperiodic regions, takes the chromosome away from equilibrium giving greater genetic stability, protection, and attraction of mutations (Figures 2A-C, 3F, 3, and 8C). Thus, hundreds of regions in the human genome might have a high genetic stability (Figures 1B-E, and 8A, B) and the most important genetic information of the human genome (genes) would be safeguarded from environmental fluctuations. It is because Alu elements (and CGI) are biased toward gene-rich regions [5]. Furthermore, it is well known that the Alu elements are highly polymorphic [29] or highly aperiodic and that a marked reduction of Alus is located within the interrupted genes, especially in exons [6]. Hence, a great number of mutations fall into the flanking regions of the coding sequences [37] and Alu elements become effectors of gene transcription by providing new enhancers, promoters and polyadenylation signals to many genes [38]. Based on these findings and those found in C. elegans [24], it seems that the non-linearity might be located on highly polymorphic genetic units that are distributed in many combinations through the genome. If so, we inquired on how these sequences have come to exist. Possibly, this might be explained by the fact that the multifractal scaling in the human genome appears to be located on fractal structures, which are mathematically created (in a deterministic way) by superposition of seed sequences [23]. So these seeds may have been the Alu sequences, which might have increased in number by retrotransposition, a process involving the insertion of reverse transcribed DNAs of Alu-derived transcripts back into the genome, apparently by hijacking the LINE-1 retrotransposition machinery [31]. Thus, multifractality may have occurred extensively in the past by the apparent "over-transposition" of different functional units (Alus, CGI) carried by each DNA sequence. Nowadays, it is hypothesized that the majority of transposable elements have been silenced perhaps by some repressive mechanism [39] to protect the genome. However, our results suggest that the Alu elements may themselves be responsible for genetic stability and protection to the genome. Thus, the human multifractal map developed here provides a tool to identify regions that are rich in genetic information and genome stability.

thumbnailFigure 8. Summary diagram: a conceptual non linear model for the human genome: From left to right multifractality increases. In A: multifractality profile for 9,379 chromosome fragments (from 0.79 to 1.56). In B: Figure 1D. In C above: Alu content profile for 9,379 chromosome fragments and below Figure 2C. In D: Figure 2E. In E: Figure 5A, C. In F: Figure 5B. In G: Figure 6B.

Secondly, there is a strong tendency to increase genetic information content when multifractality increases and to increase gene fragmentation when multifractality increases. These results are consistent with what the multifractal theory predicts (Figures 5A, C, and 8E). Thus, the human genome seems to be made by many information units (interrupted genes, Alus and CGIs) with different degrees of fragmentation (or size) that account for the aperiodic scaling of short and long range correlations found by other authors [14].

Thirdly, a multifractal genomic context seems to be a significant requirement for the functional and structural organization of thousands of genes and many gene families, i.e., a low multifractal context seems to be necessary for many sequences (generated by gene duplication and periodicy) to interact with environmental signals, while a high multifractal context (aperiodic) seems to be prone (or a "genomic attractor") to many genes; and some (very aperiodic) gene families are involved in deterministic and genetic processes (Figures 5A, B, and 8E, F). Thus, the highly multifractal regions would be a guaranty to maintain a deterministic regulation control in the genome [24], although most of the human genome sequences can be subjected to a complex epigenetic and genetic control as observed when the human epigenome due to the CGI contents is related to multifractality [28].

Fourthly, the human chromosome classification and some chromosomic region assays may have some medical implications. That is, the structure of low non-linearity exhibited for some chromosomes (or chr. regions) might imply an environmental predisposition to be sensible targets for structural and numerical chromosomic alterations (Figures 6, 7, and 8G). In fact, the loss of non-linearity is associated with failure or alterations of many vital systems close to equilibrium [17,40,41]. Additionally, the sex chromosomes must have low multifractality to maintain the sexual dimorphism and likely the XCI.

All these fractal and biological arguments might explain why the Alu elements are shaping the human genome in nonlinear manner. We believe that applying comparative multifractal genomics among many human genomes and other model organisms can help to respond to how the genome came to exist.


We report evidence for multifractality in the human genome. We identified thousands of chromosome fragments with low, medium and high multifractality, which can be translated in terms of variable genetic stability. Using these fragments we demonstrated -by different approaches- that changes in multifractality depend strongly on changes in contents of Alu sequences. The generated multifractal map of the human genome allows discussing the multifractal context in which thousands of genes and repetitive sequences lie. Thus, the Alu elements (and CGI) are non-linearity shapers and protectors of the genetic information of the human genome.

Likewise, the averaged multifractality permitted analyzing chromosome regions and classifying human chromosomes into three groups. This non-linear classification has significant medical implications because it is able to explain some chromosomal disorders, among other genomic particularities.

All of these findings help to propose a useful and integrative conceptual non-linear model to discuss and quantify the structural variation and nonlinear organization of the human genome.


Databases, sequences, and multifractal approaches

The Hs_refseq human genome sequence build 36.2 was downloaded from the NCBI web site [42]. Three multifractal approaches were followed in this study: 1) By chromosome fragment, 2) by chromosome, 3) by average of chromosome regions. In the first approach, we tested several fragment sizes of DNA sequence and we found 300 kb was an adequate length to be analyzed. This selection was based on several criteria such as percentage of discarded genome, average gene size, gene family, genetic and multifractal context, and scale independence for chromosome fragment size (Data not shown). Nevertheless, other sizes could have been taken into account. Subsequently, the contig order for each chromosome was defined according to the contig files at the 36.2 version and each contig was divided into fragments of 300 kb. That resulted in 9,389 fragments, representing 2,816,700 kb. It is about 98.6% of the whole human genome, discarding about 1.4% of the genome. Another ten chromosome fragments were removed from the analysis, because of an excessive number of Ns and lack of annotation, leaving 9,379 chromosome fragments (Additional file 1). By using these fragments, five types of analyses were implemented: analyses of multifractal parameters, analyses of molecular parameters, multifractal map of the human genome, chromosomal location of the most multifractal chromosome fragments, and analyses by gene function, gene family, and gene length. In the second approach, the resulting fragments per chromosome were averaged for multifractality to obtain a measure for each chromosome. In the third approach some chromosomes with some structural particularities were studied. Here, the resulting fragments per chromosome from the first approach were divided into four regions (or 27 for chr. 1) and averaged to evaluate the multifractality of each chromosome region.

Molecular parameters and chaos game representation

The (G+C) contents and Ns were counted for each DNA fragment of 300 kb by a script written in Python. Likewise, several molecular parameters were counted from different files: CGI from seq_cpg_islands.gz file, Alu (Y, S, J), LINEs, MIRs, MERs and LTRs from file, genes from file, exons and introns from gbk.gz file, SNPs from file, and the number of gene functions from rna.q file. All these files were downloaded from NCBI human build 36.2. KEGG( webcite), and KOGs ( webcite) were analyzed. As control, we compared some molecular parameter profiles (G+C and Alus) with those reported in literature [2].

Subsequently, the CGR was implemented according to methods in [43,44]. Figure 1A shows an example of a CGR.

Multifractal analysis and discrimination analyses

A fractal is a geometric fragmented figure whose parts are an approximate scaled copy of the whole figure, i.e., the figure possesses self-similarity. The fractal dimension D of the figure is basically the scaling rule the figure obeys. Generally, a power law is supposed:


where N(E) is the number of equal parts required to cover the figure when a scaling factor of E is applied. The power law allows to calculate the fractal dimension as

D=ln (N(E))/ln (E)

The fractal dimension obtained by the box-counting algorithm covers the figure with disjoint boxes of size ε = 1/E and counts the number of required boxes. Multifractal analysis is used, when multiple scaling rules apply. In this case, not one but a spectrum of fractal dimensions Dq, for all integer q, are evaluated [24,44]. Generalizing the box-counting algorithm to the multifractal case, Eq. (1) is obtained:

Dq(ε)=ln(∑i(MiM0)q)ln(ε)1q−1 (1)

where the number Mi of points that fall in the i-th grid box is determined and related to the total number M0 and εis the box size.

The multifractal spectrum is obtained as the limit:

Dq=limε→∞Dq(ε) (2)

Variation of the integer q allows to emphasize different regions and discriminate their fractal behavior: Positive q values emphasize dense regions; a high Dq stands for richness in structure and properties in these regions. Negative q values emphasize sparse regions; a high Dq indicates much structure and properties in these regions. In real world applications, the limit Dq is easily approximated from data by a linear fit: transformation of Eq. (1) yields

ln(Mqi)=Dq(ε)(q−1)ln(ε)+(q−1)ln(Mq0) (3)

which shows that ln(Miq) for fixed q is a linear function in ln(ε), therefore Dq can be evaluated as slope of the fitted relationship between ln(Miq) and (q - 1)ln(ε) [11]. We used this box-counting method for the multifractal spectrum estimation of CGR points and the corresponding analysis according to [10,45].

Directly from the multifractal dimension Dq, the correlation exponent τ(q) is derived asτ(q) = (q -1)Dq. The degree of multifractality, ΔDq, is the difference between maximum and minimum values of Dq: ΔDq = Dqmax - Dqmin [17,46]. When ΔDq is high, the multifractal spectrum is rich in information and highly aperiodic; when ΔDq is small; the resulting dimension spectrum is poor in information and highly periodic. For each chromosome the number of Alu versus the MD per fragment were plotted. Discrimination analyses were performed using 2-D and 3-D plots, with combined molecular and multifractal parameters.

Statistics analyses

The whole data set and each set of chromosome fragments per chromosome were analyzed by simple and multivariate regressions using the PASW statistics 18 software, to determine the goodness of the fit of several molecular parameters versus MD [47]. For multivariate regression of ΔDq the data were normalized (values between 0 and 1). In each chromosome we determined the 5 variables with highest coefficient absolute values and the most relevant ones were considered. For some molecular parameters, their RM at a 95% of occurrence level was analyzed. And to classify the human chromosomes, a clustering analysis was generated by using the Hierarchical Clustering Explorer version 3.5 program (HCE3.5) [48]. The clustering tree was generated by using the following parameters: row by row normalization by control, complete linkage method and Person's correlation coefficient.


CGR: Chaos Game Representation; MD or ΔDq: multifractality degree; RM: range of multifractality; AMD: average of multifractality degree; LMM: low and medium multifractality; GCI: CpG islands; XCI: X chromosome inactivation; chr.: chromosome.

Authors' information

Pedro A. Moreno was formerly a graduate student at University of Houston and is currently an assistant professor at the Universidad del Valle ( webcite). He teaches courses in bioinformatics, molecular biology, and information technologies. Pedro has participated in several researches working with biologists, mathematicians, and engineers in molecular biology, bioinformatics, metagenomics, fractal geometry and is currently an advisor for many students at the University. He pioneered bioinformatics research in Colombia with fractal geometry studies applied to biological problems. Patricia E. Vélez is a professor at Universidad del Cauca and Director of the BIMAC Group ( webcite) and she has been pioneered in leadership several researches on breast cancer, human genetics, bioinformatics, and fractal geometry applied to genetics problems. Ember Martínez is a graduate student and professor at Universidad del Cauca. Luis E. Garreta is a doctoral student at Universidad del Valle. Néstor M. Díaz is a graduate student and professor at Universidad del Cauca. Siler Amador is a professor at Universidad del Cauca. Irene Tischer is a professor at Universidad del Valle and Director of the Laboratorio de Bioinformática. José M. Gutiérrez was formerly a post-doctoral associate at Cornell University and is currently a professor at Universidad de Cantabria, Spain. Ashwinikumar K. Naik is a medical doctor and bioinformatician in Bangalore and participated in the human genome sequencing in Celera Genomics. Fabian Tobar is a doctoral student and bioinformatician at Laboratorio de Bioinformática, Universidad del Valle. Felipe Garcia was formerly a postdoctoral associate at Harvard University. He is currently a professor at the Universidad del Valle and Director of the Laboratory of Molecular Biology and Microbiology.

Authors' contributions

PAM conceived the research idea, participated in its design, execution, coordination, and drafted the manuscript. PEV helped to discuss, execute and draft the manuscript. EM carried out part of the writing of scripts in java for multifractal analysis and wrote part of the phyton code for molecular parameter counting. LG participated in setting up a bioinformatics server for processing and maintaining the databases. NMD and SA were responsible for security issues in informatics, web site technology ( webcite) and mathematical approaches. IT was involved in the mathematics and statistical analyses and helped to discuss the manuscript. JMG verified the equations and java code for multifractal analysis. AKN helped to discuss the human genome characteristics. All previous authors are part of the research grant approved by COLCIENCIAS. FT and FG participated in the gene analyses. All authors read and approved the final manuscript.


We gratefully acknowledge the Departamento Administrativo de Ciencia, Tecnología e Innovación - COLCIENCIAS of the Republic of Colombia for supporting this project with Biotechnology Research Grant (#1103-12-16765). Thanks to Dr. Alberto Bohorquez and Dr. Heiber Cárdenas for their comments and suggestions. Finally, thanks to the Universidad del Cauca by the computer facilities and Escuela de Ingeniería de Sistemas y Computación at Universidad del Valle for the financial support for publication.


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5 Crazy Habits You Might Adopt With Low-Cost Genome Sequencing

By Maxx Chatsko | More Articles

December 21, 2014

The $1,000 human genome took a giant leap closer to reality when Illumina (NASDAQ: ILMN ) launched the HiSeq X Ten Sequencing System in early 2014. Sequencing your genome costs over five times that amount using any other system, and had cost nearly 10 times that amount as recently as 2007. In other words, the company is easily setting the pace for the next-generation sequencing market -- and causing prices to drop precipitously every few years.

While Illumina specializes in data quantity for full-length genomes, the PacBio RS II from Pacific Biosciences (NASDAQ: PACB ) allows researchers to zoom into specific regions of a sequence with exceptional accuracy. The two systems are often used together to provide a full range of capabilities. That bodes well for genomics researchers and pharmaceutical companies, but the appetite for larger volumes of high quality data will trickle down to consumers in the form of even lower-cost gene sequencing.

If sequencing costs fall to several hundred dollars (or less) by the end of the decade, everyday life will look a little different than it does today. Let's take a look at five habits you may adopt, from the time you're born to the day you retire, when low-cost genome sequencing becomes commonplace.

1. The habit of screening the full genomes of newborns

Today, all babies born in a hospital in the United States are screened for various diseases before they're sent home. Although the conditions tested vary slightly from state to state, current tests send blood samples drawn from a baby's heel to the hospital's lab for testing. While considered one of the most successful public health programs on the planet, today's newborn genetic screening tests only look for several dozen health conditions. Full-genome sequencing could alleviate diagnostic bottlenecks inherent to current blood tests and greatly expand the usefulness of newborn sequencing.

By allowing parents to peer into the full genome of their newborn, doctors could monitor individuals genetically shown to be at increased risk of disease or even begin preventative or early treatment. Most parents would welcome the insights, according to a study recently published in Genetics in Medicine. Doctors approached 514 parents each within 48 hours of their child's birth, explained the genome's impact on human health, and asked if they'd be interested in newborn genomic screening. Nearly 83% expressed some level of interest in the tests if they were available, which could become routine in the next decade.

2. The habit of routine sequencing "checkups"

Sequencing wouldn't stop once you left the hospital after being born. While you may be born with a unique genetic code, your environment plays a critical role in determining which genes are expressed and silenced. Factors such as nutrient intake, stress levels, exposure to specific chemicals, altitude, physical activity, and many more can turn genes on and off throughout your lifetime.

If sequencing costs become low enough, then you might undergo routine genetic screenings every few years, at your annual physical, or even every time you become ill to track changes in your genome over time. Similar to newborn genomic screening, routine genomic checkups could detect diseases at the earliest stages of development, which, if used across a sizable population, would have a profound effect on our approach to healthcare by allowing more preventative treatments.

3. The habit of buying products optimized for your genes

You shouldn't have to fight back anxiety every time you peer into your genome for fear of being at an elevated risk for disease. Luckily, some of your results will have nothing to do with health at all. Not convinced that reading your genome sequence could ever be fun? Well, specific results could affect the way you shop.

Although likely unknown to most consumers and investors, personal care behemoth Procter & Gamble (NYSE: PG ) has established itself as a genomics leader. The company sequenced the fungus responsible for most human dandruff to develop more effective shampoos under its Head & Shoulders brand -- and patented the microbe's genes in the process. Genomics research has also allowed the company to develop premium diaper lines that are less likely to cause skin rashes and study how specific cosmetic agents affect skin cells of all ages and profiles.

While having a treasure trove of genomics data is useful for internal development, Procter & Gamble is actively preparing for the day that consumers have easy access to cheap genome sequencing, too. Why? The company could develop personalized personal care products marketed to individuals with specific genetic traits.

Here's a fictional example: Let's say you always get dry skin after washing your face with certain products. Your latest sequencing results tell you that you have one of two possible genes that determine how your skin retains moisture. Procter & Gamble could market two face wash products -- one tailored for each genetic outcome -- you could buy the one that matches your gene, and enjoy more moisturized skin. Shopping, product labeling, and advertising would never be the same.

4. The habit of seeking personalized cancer medicine

If you can have personalized face wash, then why not medicine, too? While the media often talks about personalized medicine, the ability to quickly and cheaply sequence a patient's genome could make it a reality. There are many hurdles to overcome, but viable stepping stones are already within reach.

Take cancer for instance. Doctors could sequence a cancerous tissue sample, which contains a genome that varies from that of the patient, to determine where the cancer originated and if specific mutations have occurred. The information could then be used to develop a personalized treatment plan to maximize drug response and potentially reduce side effects. Sequencing could even be repeated after each therapy session to track mutations and adjust the treatment plan.

Good news: cancer genome sequencing is actually being used today. In fact, two drugs (Xalkori from Pfizer and Zykadia from Novartis) have already been approved by the U.S. Food and Drug Administration to treat a specific mutation observed in lung cancer. But the potential is much greater. Since cancer is a disease of an individual's cells, approaching drug development with one-size-fits-all clinical trials may never produce cures. There's a very long way to go in understanding which mutations respond to which types of drugs, but cancer genome sequencing offers one promising avenue.

5. The habit of sequencing... everything

Advances in sequencing the 6 billion base pairs in the human genome will trickle down (and up) to technologies aimed at sequencing other organisms and living things. We could find new drug candidates by sequencing rare plants and discover genes with industrial importance to create the ultimate microbial factories for manufacturing biobased chemicals. We could even equip the next Mars or asteroid rover with a tiny sequencer, beam extraterrestrial genomes back to Earth, and reconstruct them piece by piece by synthesizing DNA (sequencing is "reading" DNA, synthesis is "writing" DNA).

Sound crazy? Don't tell that to J. Craig Venter and Synthetic Genomics, which, with the help of DARPA, are working on just such a machine. That may not affect you directly, but your household may one day own a similar device. Although years into the future, a Digital Biological Converter could allow you to upload swabs of a sick family member's infection, receive recommended treatment options from the Centers for Disease Control over a secure connection, download them, and "print" a therapeutic. No trip to the doctor or pharmacy required.

What does it mean for investors?

Low-cost genome sequencing could extend many benefits to society ranging from discovering, monitoring, and treating disease to making shopping personalized. While investments have historically been confined to a limited number of players who have acted as gatekeepers for related technologies (Illumina has returned 4,620% in the last decade), cheaper sequencing will broaden access and allow multiple companies, some of which you may never have considered (i.e. Procter & Gamble), to share in the benefits.

The Dark Corners of Our DNA Hold Clues about Disease

A “deep-learning” algorithm shines a light on mutations in once obscure areas of the genome

December 18, 2014 |By Patchen Barss

The so-called “streetlight effect” has often fettered scientists who study complex hereditary diseases. The term refers to an old joke about a drunk searching for his lost keys under a streetlight. A cop asks, "Are you sure this is where you lost them?" The drunk says, "No, I lost them in the park, but the light is better here."

For researchers who study the genetic roots of human diseases, most of the light has shone down on the 2 percent of the human genome that includes protein-coding DNA sequences. “That’s fine. Lots of diseases are caused by mutations there, but those mutations are low-hanging fruit,” says University of Toronto (U.T.) professor Brendan Frey who studies genetic networks. “They’re easy to find because the mutation actually changes one amino acid to another one, and that very much changes the protein.”

The trouble is, many disease-related mutations also happen in noncoding regions of the genome—the parts that do not directly make proteins but that still regulate how genes behave. Scientists have long been aware of how valuable it would be to analyze the other 98 percent but there has not been a practical way to do it. [What if Prof. Pellionisz has been right, now for 12 years, against a first very hostile, and now "accepting" wilderness?]

Now Frey has developed a “deep-learning” machine algorithm that effectively shines a light on the entire genome. A paper appearing December 18 in Science describes how this algorithm can identify patterns of mutation across coding and noncoding DNA alike. The algorithm can also predict how likely each variant is to contribute to a given disease. “Our method works very differently from existing methods,” says Frey, the study’s lead author. “GWAS-, QTL- and ENCODE-type approaches can't figure out causal relationships. They can only correlate. Our system can predict whether or not a mutation will cause a change in RNA splicing that could lead to a disease phenotype.”

RNA splicing is one of the major steps in turning genetic blueprints into living organisms. Splicing determines which bits of DNA code get included in the messenger-RNA strings that build proteins. Different configurations yield different proteins. Misregulated splicing contributes to an estimated 15 to 60 percent of human genetic diseases.

Frey, a computer engineer who has a cross appointment in the university’s Department of Medical Research, trained his algorithm using millions of data points: DNA sequences, genetic variations and RNA splicing patterns. The algorithm was then able to extrapolate how likely it was that any of tens of thousands of mutations could cause a splicing error associated with a particular disease.

The research team tested the method on spinal muscular atrophy as well as nonpolyposis colorectal cancer. Frey says the team’s “most ambitious case” was its study of autism spectrum disorder; about 100 genes are known to be associated with it. In fact, many researchers think it is likely that autism comprises many disorders, each resulting from unique mutations but all resulting in common symptoms.

Working with U.T. autism researcher Stephen Scherer, Frey compared mutations in autism patients’ genomes with those of controls. Nothing unusual popped up. But when Frey and Scherer tested the genomes against the mutations flagged by Frey’s algorithm, they “saw patterns emerge.” According to Frey, “Kids with autism are more likely to have these ‘high-scoring’ mutations that change the meaning of the genome, and that are thought to be involved with brain functions and developmental functions.”

Not only did the algorithm’s analysis jibe with existing knowledge about autism genetics, it also identified 17 new disease-causing gene candidates. With each of the three diseases addressed in the study, the algorithm both made predictions that were consistent with existing data and also pointed toward additional regions of the genome where researchers might search next.

The combination of whole-genome analysis and predictive models for RNA splicing makes Frey’s method a major contribution to the field, according to Stephan Sanders, an assistant professor at the University of California, San Francisco, School of Medicine. “I’m looking forward to using this tool in larger data sets and really getting sense of how important splicing is,” he says. Sanders, who researches the genetic causes of diseases, notes Frey’s approach complements, rather than replaces, other methods of genetic analysis. “I think any genomist [sic] would agree that noncoding [areas of the genome] are hugely important. This method is a really novel way of getting at that,” he says.

Although other experts, along with the study’s authors, caution that it is a long journey from this type of research to new treatments, they also agree that Frey’s method reveals an important path toward that goal. “Whole-genome sequencing is absolutely essential,” says Robert Ring, chief science officer at Autism Speaks and the former head of Pfizer’s autism unit. “But making sense of it is really where the rubber hits the road. These guys are bringing machine learning to whole-genome data and developing new ways of finding where genetic changes might be clinically significant. This is where the likelihood of new treatments and diagnoses are.”

Roche Acquires Bina Technologies’ Powerful Genome Analysis Platform

By Allison Proffitt

December 19, 2014 | Bina Technologies announced this morning that it has been acquired by Roche. Financial details were not disclosed. The Roche acquisition is, “the best outcome that could have happened for our company,” co-founder and CEO Narges Bani Asadi told Bio-IT World today.

[It was like yesterday when I spent a lovely lunch in a Palo Alto cafe with Narges Bani Asadi - at that time a Stanford Student - over the merits of start-ups suitable for genome analytics with the use of HPC platform, suitable for rapid diagnosis in hospital settings, with intrinsic algorithms of recursive genome function. Neither the amazingly rapidly kicked off Bina, nor Roche has been, or is at this point of time licensed to use the fractal utility (protected by US patent 8,280,641 and ensuing trade secrets). The breakthrough, however, is extremely significant, since it is the "existence proof" that the "next big thing" of genome analytics start-ups are, in fact, successful M/A targets. This validates the kind of investment that is pouring into making "mere sequencing" a sustainable business proposition. Ever since my 2008 YouTube I broadcast the question "Is IT Ready for the Dreaded DNA Data Deluge?" By now, "sequencing" became a commodity, with an unthinkable oversupply of "huge data" in genomics - yet "a trickle of analytics" is already merged with one of the biggest of "Big Pharma". From now on, the cut-throat competition is if particular "Big Pharma" companies could sustain their "going genomics" by rapid M/A-s, or the type of "leveraging pharma companies" either by "fast and furious" (like Boston-based Foundation Medicine) hyperescalating smaller entities, or by "massive IT" (clearly led by 3 in the USA; Google Genomics, IBM/Watson & New York Genome Institute, and Amazon Web Services & Illumina, and scores of giants around the World, like Samsung, Sony, Siemens, SAP etc.) would leverage best the clear trend of all pharma companies "going all the way in genomics". Remember, this is the message of 2014 -]

The acquisition is an “arm’s length” relationship, Asadi said. Bina will retain its brand, management team, location, customers, and partnerships. “It’s an amazing outcome for us,” she said. Asadi will report to Dan Zabrowski, Head of Roche Sequencing.

Bina Technologies emerged from stealth mode in May 2012, when Asadi was a Stanford Ph.D. student. Then, the company touted its Bina Box as a fast and customized platform to do secondary genomic analysis, alignment and variant calling. In the years since, the company has steadily rolled out new products, expanded to tertiary analysis, and rebranded its offerings. Bina has evolved from a tools provider to a solutions provider, Asadi said. In February, the company announced new members of its Scientific Advisory Board, signaling an increased interest in clinical genomics.

Under Roche, much of the company’s trajectory will remain the same, Asadi said. Bina recently announced selection of its platform by the US Department of Veterans Affairs (VA) to provide whole genome, whole exome, and SNP Chip DNA data analysis as part of the VA's Million Veteran Program (MVP), which aims to enroll 1 million veterans. The acquisition by Roche will enable Bina to further expand support to similar big-data population studies, as well as grow its offering for global enterprise and clinical research customers.

Roche also plans to fully support the continued development of Bina’s newest offering, the Genomics Management Solution product, Asadi said.

GMS is a platform for managing and analyzing the genomic information that an organization collects over time, serving many different customers within the organization: IT staff, bioinformaticians, and clinical researchers. It includes a read alignment, variant calling, and expression module (RAVE) and a module for annotation and analytics intelligence (AAiM).

Asadi stresses that the deployment model of GMS is independent from its functionality. Some customers prefer the hardware/software combination solutions Bina first launched. Bina Desktop and Bina Rack (formerly Bina Enterprise) are hardware offerings still available. But other customers, especially pharma customers Asadi said, prefer to work in public or private cloud environments.

Bina has also already started working to supporting Roche’s next generation sequencing technology, and “provide an end-to-end software platform—from sample to answer—that will accompany a proprietary NGS technology that Roche is building,” Asadi said.

"The acquisition of Bina is a significant step for Roche to enable the promise of personalized healthcare by delivering the highest quality genomic data possible," said Asadi’s new boss, Dan Zabrowski, Head of Roche Sequencing, in a press release. "Informatics and data management are critical to providing a seamless, end-to-end sequencing solution. Bina's products are designed to improve the efficiency and value of genomic analysis, and the company continues to develop new methodologies and algorithms that link NGS data to disease-relevant genetic markers."

For her part, Asadi is enthusiastic about the growth and learning opportunities at Roche.

“We’re going to have the support of Roche to develop and scale our company much faster than before, and also have access to really deep experience and knowledge in Roche. Roche is a company of 120 years’ experience and collective learning that operates in more than 150 countries! I look forward to learning a lot!”

Experts expose fundamental role of chaos and complexity in biological information processing. (In life, Fractal/Chaotic nonlinear dynamics governs [AJP])

Published on December 14, 2014 at 7:15 AM

Do chaos and complexity play a fundamental role in biological information processing?

[2012: Nicolis, Mandelbrot passed away. Encode-2 finally discarded junk/gene "frighteningly unsophisticated" dogmas. While science was introduced in 1989, utility of Fractogene "fractal genome grows fractal organisms" went into force in days (after a Decade of waste), 8,280,641. Clinical application global path was laid down also in 2012 (prized by India), collaborative Springer textbook chapter on science with ample references to the new school submitted also in 2012. FractoGene is in force till late-March of 2026]

The interdisciplinary approach to problems that till recently were addressed in the hermetic framework of distinct disciplines such as physics, informatics, biology or sociology constitutes today one of the most active and innovative areas of science, where fundamental issues meet problems of everyday concern.

John Nicolis, an eminent Greek scientist and thinker who passed away unexpectedly on the 20th of April 2012, brought out to the highest degree the interdisciplinary approach to key scientific problems and, at the same time, their cultural dimension. Complexity has been at the core of his interests for almost 40 years. He imprinted on it a new direction focusing on the generation and processing of information in hierarchical systems, that is to say, systems involving coexisting components evolving on different scales and coupled to each other in a nonlinear fashion through positive and negative feedback loops. He defined three basic levels of organization:

-The ``syntactical'' level where the elementary dynamical processes are taking place.

-The ``semantic'' level, where relationships between stimuli impinging on a system and the formation of "categories" related to global, collective properties e. g. the attractors that emerge from the syntactical level and follow a dynamics of their own.

-The ``pragmatic level'', where different hierarchical systems are viewed as players communicating dynamically via a set of selected strategic rules such as cooperation, competition, cheating, etc.

Based on this vision John Nicolis generated a phenomenal number of ideas and intuitions, In the present volume surveys by eminent international specialists of the mechanisms presiding in information processing and communication are provided. Physical, biological and cognitive systems are approached from different, complementary points of view using the unifying methods of nonlinear dynamics, chaos theory, probability and information theories and complexity science. Unexpected connections between these disciplines are stressed by bringing together ideas and tools that had so far been developed independently of each other. Epistemological issues in connection with incompleteness and self-reference are also addressed.

The following topics are featured in the volume.

I. Glimpses at nonlinear dynamics and chaos:

Nonlinear dynamics and chaos theory provide the general setting within which complexity and information processing can be formulated. In the opening chapter by G. Contopoulos et al the transition from quantum to classical behaviour is analysed in the paradigmatic case of the scattering problem. The connection between classical and quantum descriptions is further addressed in the chapter by M. Axenides and E. Floratos, where the classic Lorenz attractor is revisited using a formulation originally developed by Nambu in the context of quantum mechanics. G. Tsironis et al discuss in their chapter the onset of spatio-temporal complexity in nonlinear lattices. In the chapter by D. Mac Kernan a systematic probabilistic approach is outlined based on coarse-grained description and symbolic dynamics. Symbolic dynamics is taken up again in the closing chapter of this Part by A. Shilnikov et al., where fractal-hierarchical organizations of the parameter space of Lorenz-type chaotic systems induced by homoclinic and heteroclinic bifurcations are revealed using a binary representation of the solutions.

II. Chaos and information:

Information theory finds its origin in Shannon's 1949 classic paper. In the opening chapter of this Part H. Haken develops the quantum expression of Shannon information along with an extension of Jaynes' maximum entropy principle into the quantum domain. The conditions under which entangled states and long-range coherence can be secured as necessary conditions for information processing at the quantum mechanical level, are addressed in the following chapter by S. Nicolis. A dynamical approach to information is subsequently developed in the chapter by C. Nicolis, devoted to nonlinear systems giving rise to multiple simultaneously stable states and to stochastic resonance. Different signatures of multistability and of stochastic resonance on a hierarchy of entropy-related quantities characterizing the system as an information processor are identified. Finally, in the closing chapter by W. Ebeling and R. Feistel the origin of information processing is addressed in relation to the origin and evolution of life. Central to their approach is the idea that there exists a universal process of self-organized emergence of systems capable of processing symbolic information. They coin to it the name of "ritualization transition" and discuss its status with respect to kinetic phase transitions familiar from physics.

III. Biological information processing

Undoubtedly Information processing and the very concept of Information, for that matter, find their most exciting expressions in living matter. In the opening chapter of this Part, P. Schuster addresses the information processing mechanisms responsible for the build up of an evolutionary memory within a population. The conditions under which optimality can be achieved are also analysed using computer simulations along with mathematical modelling, and connections to nonlinear dynamics and irreversible thermodynamics are suggested. Evolutionary arguments are also central in the chapter by Y. Almirantis et al, where the structure of the genome and, in particular, the distribution patterns of the distances between different groups along it are explored and correlated with known evolutionary phenomena. The ubiquity of power law behaviours is established and a model based on aggregative dynamics capable of reproducing these patterns is proposed. Pattern formation on a much larger scale associated to embryonic development is considered in the closing chapter by S. Papageorgiou. A biophysical model is proposed to explain the appearance of a sequential pattern along the anterior-posterior axis of a vertebrate embryo, in coincidence with the 3' to 5' order of the genes in the chromosome.

IV. Complexity, chaos and cognition:

This Part deals with the multiple facets of information processing by the brain, a question that has been at the center of interests of John Nicolis throughout his career. Different approaches to cognition are developed and the status of self-referential processes is discussed. In the opening chapter W. J. Freeman summarises the role of chaos in brain function from a "bottom-up approach". He discusses the state of "criticality" of the celebral cortex and its placid properties of a system at the edge of chaos, an idea that J.S. Nicolis employed in his studies of the mechanisms of cognition in the brain as a hierarchical system. W.J. Freeman, offers a discussion on the state of the art of the issue of brain waves, emerging patterns, fractality, quantum-field considerations and the role of noise in the emergence of coherent and intermittent states in brain dynamics. The spectral properties of brain recordings are studied in comparison with the spectral signatures of a Lorenz-type model, at its turbulent regime, by Provata et al. Bringing out the relevance of chaotic dynamics in understanding the phenomenology of brain recordings. F.T. Arrechi, is addressing the issue of cognition and language with respect to brain dynamics in a hierarchical system perspective via a "top down" approach. He proposes a quantum-like model where apprehension, judgment and self-consciousness could be discussed. He shows that the uncertainty in the information content of spike-train recording is ruled by a "quantum" constant, that can be given a numerical value depending on the specifics of the experimental set up. Subsequently, K. Kaneko presents a tantalizing approach to bridge the gap between dynamical systems and biological information processing. Chaotic itinerancy in high-dimensional dynamical systems, induced switches of states, and interference between slow and fast modes via "super-selection rules", also a preoccupation of J. S. Nicolis, are reviewed and applied to cell differentiation, adaptation, and memory. The necessity to expand the mathematical framework to include self-referential dynamics for such "super selection rules" is also stressed. Closing this part, I. Tsuda, discusses self-reference and chaotic itinerancy with relation to the dynamics of cognition, perception ambiguity and paradoxical games from a purely dynamical-systems point of view.

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V. Dynamical games and collective behaviours:

Continuing on the theme of games C. Grebogi and coworkers address the outstanding and fundamental problem of species coexistence. They approach this problem augmenting evolutionary games with mobility for the species dynamics, under cyclic competitions, which enables them to elucidate the underlying fundamentally nonlinear mechanisms. The emerging picture is one of a complex, non-trivial, chaotic landscape for coexistence and extinction. The emergent properties of the collective behaviour of animal groups is the theme that follows where T. Bountis et al study collective behaviours and phase transitions in models of bird flocking. With an emphasis on the interplay between topological and dynamical constrains present in the complex interactions of the constituent parts, they discuss the emerging complex patterns of motion. In the same vein but with another biological model of social animal behaviour, that of ants, S.C. Nicolis presents evidence of fractal scaling laws in the ubiquitous activity of animal construction. Fractal scaling laws have also been associated with the underlying process of self-organized criticality, a theme that John Nicolis was enthusiastically and frequently discussing in his work and teaching. Y.-P. Gunji offers his view of an extended self-organised criticality in asynchronously tuned cellular automata. He provides a link with dynamical games based on cellular automata, distributed in space, and demonstrates the subtleties in information flow of synchronous versus asynchronous updating for their local states. He demonstrates that asynchronous information updating is the main formative cause of self-organized criticality.

Closing the volume, O. E. Rössler dialogues here with John Nicolis and invites us in a journey on the theme of scientific revolution crossing space-time barriers, from Heraclitus to Hubble.

The general approach followed and the ideas put forward in this volume will prove useful to students, researchers and the general public attracted by the interdisciplinary approach to science. .

Quotes From the Book:

"Mapping the continuous description of a system into a discrete set of states also means that the original, fine grained dynamics induces a symbolic dynamics describing how the sequence of letters from an alphabet unfold in time. This provides a natural link with the information theory view of chaos pioneered by John Nicolis." Chapter 4, Coarse Graining Approach to Chaos, by Donal MacKernan.

"Our interest [...] is focused on the self-organization of information, on the way how a physical system can be enabled to create symbols and the related symbol-processing machinery out of ordinary pre-biological roots."

Chapter 9, Selforganization of Symbols and Information, by Werner Ebeling and Rainer Feistel.

"The late Professor J.S. Nicolis always emphasized [...]the relevance of a dynamical systems approach to biology. In particular, viewing the genome as a "biological text" captures the dynamical character of both the evolution and function of the organisms in the form of correlations indicating the presence of a long-range order. This genomic structure can be expressed in forms reminiscent of natural languages and several temporal and spatial traces left by the functioning of dynamical systems: Zipf laws, self-similarity and fractality".

Chapter 11 Long-Range Order and Fractality in the Structure and Organization of Eukaryotic Genomes, by Dimitris Polychronopoulos, Giannis Tsiagkas, Labrini Athanasopoulou, Diamantis Sellis and Yannis Almirantis.

"In the last decades a wholistic approach has emerged aiming at explaining the complex phenomena of life. In this direction different branches of Science like Chemistry, Physics, Mathematics have contributed. Systems Biology consists of this inter-disciplinary field where the development of powerful computational techniques plays a fundamental role. This new field aims at discovering emerging properties at the level of cells, tissues, organisms, populations functioning as a whole system."

Chapter 12, Towards Resolving the Enigma of HOX Gene Collinearity, by Spyros Papageorgiou

[A recent lucid but deep insight from an undisputable, double-degree biomathematician, director of $600 M "Mount Sinai Center of Genomics and Scale Free Biology" is here , and the late-2014 horse-race status is outlined in the second entry down here ("Cancer Genomics") - AJP]

Craig Venter on How the Genomic Era Is Just Starting

By Craig Venter December 04, 2014

2000 The human genome is decoded for the first time.

There have been lots of stories written about all the hype over getting the genome done and the letdown of not discovering lots of cures right after. The biggest finding when we announced the genome in 2000 was that we only had 20,000-some-odd genes. Some people thought that because we were humans, we had to have more than every other animal. We had to have 10 times more, 100 times more. Everybody wanted there to be this nice, linear path where you have a gene for each trait—you know, there’s a gene that codes for your nose. It’s so naive.

Only now are we really starting to appreciate all the changes that have occurred over the past 15 years. On the computing side and the sequencing side, both of those just passed a cost and performance threshold that will allow for a major impact on medicine. We’re just now where I wanted to be in 2000. In the last three years, we’ve seen some impact on medicine with the discovery of the driver mutations in cancer. If you have lung cancer, the most important thing you can know is your genetic code. Roughly 4 percent of people with lung cancer will have this ALK gene translocation that seems to indicate that Pfizer’s (PFE) drug has a better-than-60-percent chance of shrinking your tumor. Instead of a blockbuster drug that you can give to everybody that has cancer, you end up with a drug that you give to 4 percent of the people we know can benefit from it. That is a fundamental change in medicine.

There’s been a huge increase in the last three years of people measuring these driver mutations, but revolutions in medicine are slow. My understanding is only about 3 percent of cancer patients in the U.S. get genetic screening of their tumors. We have the tools to do it now, but the physicians don’t have the training and the know-how to help get this implemented to benefit their patients. The only way to come up with all of the cures that were promised is to sequence large numbers of genomes. For each gene in your genome, you quite often get a different version of that gene from your father and a different version from your mother. We need to study these relationships across a very large number of people. It’s going to be important to know what the variant is you got from your mother and from your father, and whether that correlates with 30 other variants across the genome that are associated with susceptibility for a certain type of cancer, for example.

That’s why we started my new company Human Longevity. We’re trying to sequence 40,000 genomes in the next six months and then scale up to 100,000 a year. We have a goal of getting to a million genomes by 2020. It’s around $1,000 to $1,500 to do a genome today, but we’re counting on continued Moore’s Law-type change to take it down to a few dollars per genome.

We’ve proven that DNA is our software, the software of cells. But genomics can’t really, truly impact medicine—get us to preventative medicine, get us to new treatments—until we can truly read that software. We have less than 1 percent of the information that people will have in the future. So to me, we’re just starting the genomic era now.—As told to Ashlee Vance

[I am a great admirer of Craig - while I call in my lectures pubicly George Church "the Edison of Genomics", I call Craig Venter "the Tesla of Genomics" - you figure out the difference. As a software & IT specialist, however, I can not fully agree with Venter that the genome is "our software" (elsewhere they call the genome yet another natural language). While we must totally congratulate that Craig now entered the Silicon Valley horse-race of Google Genomics versus Longevity versus Chinese owned Complete Genomics, one must note that nobody can "read that software" who does not understand the (computer) code. Is the genome "written" in Python, C, Fortran, Basic? Obviously not. Do the "language-like features" of the genome make it a "natural language" like Arabic or English? Obviously not. The genome is a code and (contrary to too many claims) has never been "decoded" by merely "sequencing the DNA". You can lay out all the Cyrillic letters of "War and Peace" (in Russsian), yet you can not read it, let alone understand it, without understanding Russian. The genome/epigenome system encodes life by the mathematics of nonlinear dynamics. A bit of complication is, that there is a dual representation (by directly coding but fractured) "genes" and the opposite valence of measurement-type "non-coding" regulatory sequences. You bet on the mathematics. My thesis to beat is that "fractal genome governs fractal growth of organisms" - and the utility is FractoGene - Dr. Pellionisz]

Cancer Genomics

Complexity is in the Eye of the Belwildered

The Dreaded DNA Data Deluge is Deduced by FractoGene to Diagnostic and Therapheutic Utility

Book cover of "Cancer Genomics" (on the left) depicts the oncoming "Zeitgeist" that the recurring waves of cancerous growth not only invoke Mandelbrot's inspiration of coining "FRACTAL" (see on the right the insert from Mandelbrot's "The Fractal Geometry of Nature", page C16). Significantly, the book "Cancer Genomics" invokes the classic artwork of Hokusai, but the original inscription-box is replaced by a double helix, since cancer is universally known as a genome misregulation syndrome (the original Japonese inscription is: "Thirty six views of Mount Fuji / offshore from Kanagawa / Beneath the wave" ). The book "Cancer Genomics" does explicitly say "advanced...analysis methods, such as fractal dimension calculations, can also be applied" (in contrast to Mandelbrot, who deliberatelly stayed away from "mathematization (geometrization) of biology, see his autobiography, "The Fractalist" - the index in his masterpiece "The Fractal Geometry of Nature" does not mention the word "cancer" at all). On the cover of "Cancer Genomics", the upper right insert shows an apparently phased-out, maddeningly complex set of "pathways" ("everything is connected to everything, thus blockage of certain pathways appears not to be the barrier to a Tsunami that just gets around"). The FractoGene concept (Pellionisz, 2002) draws utility (2012) by relating "fractal genome governing growth of fractal organisms". Claims and "know how of Best Methods" (held as "trade secrets after most recent CIP in 2007"). The aim is to relate fractal genome & growth of cancers to better predict, diagnose and treat by precision therapy, based on detecting fractal defects in the genome (prior to development of cancerous protein-structures). Investment & Licensing, as well as Advisership, Consultancy avenues are now open, mail "Letter of Interest" to Attorney Kevin Roe, Esq, contact info shown in top part of this webpage).

Ever since Leroy Hood declared "Genomics=Informatics" (2002), those who never believed the "biggest mistakes of the history of molecular biology" prepared for sequencing AND analytics of Full Human Genomes in droves. This task was predicted a decade ago to cause an earthquake-like "Big One" - a major collision of the tectonic plates of Genomics and Big IT".

Well, it took an entire decade - but just in the USA top IT companies are in a horse-race. Below is (a partial...) list of major contenders, Google Genomics, Amazon Web Services, and IBM - in alliance with genome data sources. (Not belabored here are further USA-based efforts, like Craig Venter competing in Mountain View with Google, at UCSC Dave Haussler warehousing cancer data for NCBI. Foreign competitors of Sony, Panasonic, Samsung in Asia and Siemens, SAP in Europe are treated separately. China, Russia, India (etc) are also joining the fray - potentially altering the ge(n)opolitical equilibrium)


Ambitious Google drive to put human genome online gathers steam

Published time: November 08, 2014

[see YouTube here]

Google’s plan to store entire copies of the human genome online is edging closer to reality. With 3,500 genomes already stored on its servers and more medical institutes jumping onboard, the blueprint of every person on Earth could soon be in the cloud.

The potentially game-changing project, called Google Genomics, has now been quietly moving forward for a year and a half.

Perhaps with so many ambitious plans coming out of the company’s secretive Google X research and development division, from nanobots to sniff out cancer to tremor-canceling spoons for Parkinson's patients, it’s easy for even deeply ambitious projects to get overlooked.

READ MORE: Google’s next data collection project: Human body

RT first wrote about the search giant’s plan to create individual genome databases in July, but even promotional videos hashing out the details of the project attracted just 5,000 views over the past four months.

Maybe the fact that Google Drive currently cannot cope with entire copies of the genome has left many thinking the project is mere speculative pipe dream at this stage of the game.

READ MORE: Google nanobots: Early warning system for cancer, heart disease inside the body

But for futurists, whose first commandment is Moore's Law, that which is impossible today will likely be outdated tomorrow.

Google itself was quick to point out that at the inception of the human Genome project, it took 15 years and $3 billion just to do the first human genome sequence. Today, it can all be done in a day, and for about $1,000.

Just how many gigs am I?

But just how much memory is needed to save all 6 billion of the nucleotide letters that comprise a single genome sequence? Google estimates it’s around 100 gigabits, which might not seem like a lot, until you consider just how many of us there are.

For example, if you wanted to read the DNA of everyone (officially!) living in Moscow, it would take more than 1.2 million terabit hardrives. While that is obviously an enormous amount of information to process, Google’s current search index stands at 100 petabyes – 100,000 terabytes. The average search query, however, takes 0.25 seconds.

And it is applying this self-same search technology to the Google Genomics which is viewed as the key.

At the inception of the project, scientists began hammering out an application programming interface (API) which would allow them to move DNA data into Google server clusters and conduct experiments using the companies renowned web-indexing technology.

And as scientists have expanded their studies beyond individual genomes, hammering out a synthesis between data science and life science could propel the pace of medical advancement over the coming years.

“We saw biologists moving from studying one genome at a time to studying millions,” David Glazer, the software engineer who led the effort and was previously head of platform engineering for Google+, the social network, told the MIT Technology Review. “The opportunity is how to apply breakthroughs in data technology to help with this transition.”

Currently, different genome data sets are exclusively available to specific research labs. The goal then, is to create one centralized database where researchers can compare millions of genome sequences at one time.

Speaking to Technology Review, Sheila Reynolds, a research scientist at the Institute for Systems Biology in Seattle, one idea is to create “cancer genome clouds” where scientists can share information and quickly run virtual experiments as easily as a web search.

“Our bird’s eye view is that if I were to get lung cancer in the future, doctors are going to sequence my genome and my tumor’s genome, and then query them against a database of 50 million other genomes,” Deniz Kural, CEO of Seven Bridges, which stores genome data on behalf of 1,600 researchers in Amazon’s cloud, told the magazine. “The result will be ‘Hey, here’s the drug that will work best for you.’”

But as Reynolds noted, not every research institute has the ability to download a petabyte of data, or the computing power to analyze it.

With a centralized database, however, those technological trammels would be put out to pasture.

The treatment potential of being able to compare the genomes of multiple individuals suffering from the same ailments is astronomical, as is the profit motive for whoever holds the keys to the data locker.

This reality has already put Google, Amazon and Microsoft and IBM in a race to see who will store the data. And on a fair playing field, the competition has driven prices down.

Saving you for a quarter a year

Currently, storing a single human genome with Google is going to cost you $25 a year, in the same ballpark as Amazon. Running analysis of the data, of course, is gonna cost you. The catch, of course, is that people’s DNA is 99.1 percent identical. Once you can whittle it down to the 0.1 percent that makes us who we are, less than a gig will be needed to store the essence of you in the cloud. So in the long term, a bit of analysis and a quarter will get your unique genomic sequence put up in the cloud for a year.

Glazer did tell the magazine just how many customers Google Genomics has now, though at least 3,500 genomes from public projects are already stored on Google’s server farm.

According to The Verge, the National Cancer Institute has already signed on to the project, and has expressed its willingness to pay $19 million to upload copies of its 2,600 terabyte Cancer Genome Atlas to Google Genomics and Amazon’s data center.

The project, however, definitely comes with its privacy pitfalls.

As Gizmodo recently noted, a study in the Journal Science last year showed it was possible to identify several men from the publicly available 1000 Genomes Project based on their Y chromosomes and age, location, and family tree data.

Insurance companies would also likely be thrilled to get their hands on that data.

There is also the issue of whether scientists should tell people if they unknowingly have a rare disease, or have unknown siblings out there in the world.

But while both concerns of privacy and practicality are inevitable in any venture of this scope, the likelihood that the seemingly infinite permutations of AGCT which tell the story of every person on earth seems all but inevitable.

[Can you guess why is the above article on Google Genomics in (the English language broadcast of Russia)??? Hint: think of Google vs. Baidu; BGI of China - missing from this list - is also actively pursuing both sequencing and analytics - but not very publicly... - AJP]


Illumina on AWS - Customer Success Story

[see YouTube on Amazon and Illumina here]

AWS Case Study: Illumina

Biologists around the world use DNA sequencers created by California-based Illumina for a broad range of genomics applications including whole-genome sequencing. The company built its BaseSpace tool on AWS to allow researchers to upload massive data sets directly to the cloud for analysis and to store the results long-term with Amazon Glacier.

Baylor, DNAnexus, Amazon Web Services collaboration enables largest-ever cloud-based analysis of genomic data


Houston, TX - Oct 25, 2013

With their participation in the completion of the largest cloud-based analysis of genome sequence data, researchers from the Baylor College of Medicine Human Genome Sequencing Center are helping to usher genomic scientists and clinicians around the world into a new era of high-level data analysis. (A “cloud” is a virtual network of remote internet servers used to store, manage and process information.)

“The mission of the Baylor Human Genome Sequencing Center is to drive genomics and genomic analysis to be at the leading edge of everything in the field,” said Dr. Jeffrey Reid, assistant professor in the Human Genome Sequencing Center at BCM, who led the BCM portion of the project. “In terms of analysis, the future of genomic research and genomic medicine is in the cloud. We are very much going towards more computing and not less.”

Together with the Platform-as-a-Service company DNAnexus and Amazon Web Services, the largest provider of cloud computing, BCM sequenced the DNA of more than 14,000 individuals -- 3,751 whole genomes and 10,771 whole exomes using next generation sequencing. (An exome contains all the genes in a genome and are the part of the genome that provides the blueprints for proteins.) The individuals whose genetic material was sequenced are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium or CHARGE project aimed at advancing understanding of human genetics and the contributions to heart disease and aging.

Reid gave a presentation on the project Oct. 25 at the American Society of Human Genetics annual meeting in Boston.

The BCM Human Genome Sequencing Center-developed Mercury pipeline, a semi-automated and modular set of tools for the analysis of next generation sequencing data in both research and clinical contexts, was an integral part of the project. The pipeline identifies mutations from genomic data, setting the stage for determining the significance of these mutations as a cause of serious disease.

Led by Dr. Eric Boerwinkle, professor and director of the Human Genetics Center at The University of Texas Health Science Center at Houston and associate director of the Human Genome Sequencing Center at BCM, the CHARGE project involves more than 300 researchers across five institutions around the world. The cloud-based analysis makes it possible for the large group to have access to an expansive network of data over a server that is HIPAA certified to not compromise patient privacy.

“The collaboration between the CHARGE consortium and the Human Genome Sequencing Center is leading to discovery of those genes contributing to risk of the most important diseases plaguing the U.S. population across all age groups,” said Boerwinkle. “Ultimately, these discoveries forge a path toward novel therapeutics and diagnostics. The use of cloud computing and collaboration with DNAnexus is allowing us to achieve our goals faster and in a more cost-effective manner.”(Boerwinkle will give an updated presentation November 15 at the Cold Spring Harbor Laboratory’s Personal Genomes & Pharmacogenomics Meeting.)

“Having access to this much data was unique,” said Reid. “Many institutions do not have the local compute resources and infrastructure to support large scale analysis projects like this one, so we were lucky to come together with DNAnexus and Amazon Web Services to make this project possible.”

The project required approximately 2.4 million core-hours of computational time, generating 440 TB (terabytes) of results and nearly a petabyte of storage that took place over a four-week period.

By comparison, the 1,000 genomes project sequenced 2,535 exomes and required 25 TB of data.

“It is very important for us to create a centralized space where researchers from all over the world can come and collaborate with the data,” said Reid. “This project creates expansive access to this data over a protected network that will advance research.”


IBM’s Watson takes on brain cancer

[See YouTube on IBM & NYC Genome Center here]

Analyzing genomes to accelerate and help clinicians personalize treatments

New York Genome Center (NYGC) and IBM are collaborating to analyze genetic data to accelerate the race to personalized, life-saving treatment for brain cancer patients.

IBM's Watson cognitive computing system will be designed to analyze the genomic data from a small group of patients diagnosed with glioblastoma, one of the most aggressive and malignant brain cancers. Also the most common type of brain cancer in adults, glioblastoma kills more than 13,000 Americans each year.

IBM and NYGC's computational biology experts are renowned for accelerating life sciences discoveries using deep analytical approaches and next generation information technologies.

The system, expected to be deployed as a cloud-based prototype, will combine modern genomic analytics and comprehensive data bases of medical biomedical literature with Watson’s cognitive computing power to help clinicians uncover individual genetic patterns of glioblastoma. IBM will be taking advantage of NYGC’s genomic and clinical expertise to continue to develop and refine the Watson system with the shared goal of transforming care for all types of cancer, based on the genetic characteristics of that person’s cancer.

With a decade of research and development behind it, the Watson prototype is IBM’s first solution specifically targeted at interpreting data from genomic data. By analyzing gene sequence variations between normal and cancerous biopsies of brain tumors, Watson will then be used to review medical literature and clinical records to help clinicians consider a variety treatments options tailored to an individual’s specific type and personalized instance of the cancer.

Normally, a diagnosis of glioblastoma presents a prognosis of about a year to live, depending on the stage and spread of the cancer at the time. This includes the difficult period of interpreting the best treatment based on the knowledge and information at hand. The Watson system is designed to complement rapid genome sequencing and to help dramatically reduce the time from gathering the genomic data of an individual's tumor variant to clinical interpretation, enabling clinicians to more rapidly make decisions on how they can treat their patients.

Oncologists could use the cloud-delivered system in real-time to analyze genetic data with the intelligent machine curation of comprehensive biomedical literature and drug databases. This analysis can help pinpoint potential therapeutic options that are specific to a patient’s cancer genome, to aid oncologists in their treatment and care decisions.

As these types of intelligent systems become commercially available in medicine, it is expected that many more patients will have access to treatments that are increasingly more tailored to their disease's DNA. The system can continually "learn" as it encounters new patient scenarios and as more information becomes available through new medical research, journal articles and clinical studies.

"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 systems like Watson," said Dr. John E. Kelly, 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. This is a major transformation that can help improve the lives of millions of patients around the world.”

Exponential Medicine by Singularity University - San Diego, 2014

Ray Kurzweil's "Singularity University" kicks off by Sunday (Nov. 9) a landmark meeting in San Diego - now headquarters (not hometown) of Craig Venter.

For some, it may be difficult to make sense of the title - as both "exponential" and "singularity" are clearly mathematical terms, seemingly with not much in common. What is the meeting all about?

To simplify, I would call it in spades "Computerization of Medicine". That explains instantly why are key figures there like Ray Kurzweil (now a Googler...) and Craig Venter (now close to Venter's "hometown" in the Bay Area he launched a bold attempt in Mountain View to compete head-on with Google by an ex-Googler Franz Och, based on the 20 year old notion that the genome is a bit like a natural language). Further, it also may explain why Vinod Khosla, with a subcontinent of IT outsourcing behind him, enters this most interesting new turmoil. Peter Diamandis talks about "exponential thinking" (in plain English "disruption, and the need for bold thinking") - another tell-tale sign.

Kurzweil is no stranger to bold thinking & fractals. His famed book "The Singularity is Near" (2005) shows in the index some seven encounters; look "fractals". Venter is famous among others for his saying "What is the difference between you and God?" - "We had computers!"

Enter Peter Diamandis - the only person among the major movers & shakers mentioned above, who actually holds the M.D. title of a physician (interestingly, he put his M.D. program on hold while at MIT pursued a master's degree in aeronautics and astronautics, and returned to Harvard to complete his M.D.).

Medicine, for ages, had to do very little with mathematics, let alone computers that did not exist until very recent history. The disruption is so dramatic, that one may even want to question why is it inevitable?

The two keywords are "genomics" and "cancer". Today, professional mathematicians (Dave Haussler, Eric Schadt, Eric Lander etc) totally agree that the "digital information of the genome" and the "genome-disease (a.k.a. cancer)" are (separately and especially together) are simply beyond comprehension of the un-aided human mind. The "aid" is clearly by mathematics (software enabling algorithms), implemented by the abundance of computing power.

Breakthrough will not be easy - that is why it is so lucrative. "Medicine" has traditionally been the "human art" to help people with "ill-understood" conditions. Indeed, the very notion (on the cover of Newsweek lately) that "You Can Not Cure a Disease That You Don't Understand"), is enigmatic for those medical doctors who openly confess that most diseases & their medication are "poorly understood".

Steve Jobs hoped (to late for him, too early for science) that cancer will go down in history as the first disease resolved by the power of mathematics and computers.

Most of those presently alive will see it becoming to happen. Surprising? Hardly. Centuries ago, most people died of infections that can be cured by popping antibiotics. I remember to be terrified as a young boy by swimming pools in hot summer days - for fear of polio. In the history of medicine, along came Flaming, Sabin, Salk (etc) and the world has changed.

These days, we live similar times of disruption.

Look up the program of the conference

Join the conference by live stream


TIME Magazine 2003 Summit versus 2014 Special Issue

Time 2003 Monterey 50th Anniversary: Jim Watson for his discovery of the structure of DNA

Time 2014 Special Issue: A Decade Later the issue is not the known structure, but the mathematical function. Sorry, 1% "genes" and 99% "junk" will not do it, anymore. "The more we learn about the genome, the more we learn how complicated it is" (p.12). "Will we ever finally - actually - decode it? Maybe it doesn't matter....You just have to know how to read the map" (p.13). Although FractoGene was introduced at the 2003 Monterey meeting (in the "gene euphoria" noted by select few), like "the splitting of the atom" required Quantum Physics, the recent Newsweek cover ("You can not cure a disease that you don't understand") will require the advanced mathematics of non-linear dynamics of fractal recursion. A similar much earlier but equially massive change was required from Alchemy (trying, in vain, without understanding to turn lead to gold...) to build the new science of physics-based Chemistry.

Ovarian cancer oncogene found in 'junk DNA'

A research team mined junk DNA sequences to identify a non-protein-coding RNA whose expression is linked to ovarian cancer.

Most genetic studies have focused on the portion of the human genome that encodes protein, which is a fraction that accounts for just 2% of human DNA overall. Yet the vast majority of genomic alterations associated with cancer lie outside protein-coding genes, in what traditionally has been derided as junk DNA. Researchers today know that junk DNA is anything but junk, as much of it is transcribed into RNA, for example, but finding meaning in those sequences remains a challenge.

Supported by the Basser Research Center for BRCA at the Abramson Cancer Center at the Perelman School of Medicine at the University of Pennsylvania in Philadelphia, a research team led by Lin Zhang, PhD, built a DNA copy number profile for nearly 14,000 long noncoding RNAs, or lncRNAs. They did this across 12 cancer types, including ovarian and breast cancers that include the two major BRCA-related cancers. They found that the number of copies of lncRNA genes on a chromosome consistently changes in 12 different cancer types. Also, lncRNA genes are widely expressed in cancer cells.

Using clinical, genetic, and gene expression data as filters to distinguish genes whose copy number alteration causes cancer from those for whom copy number changes are incidental, the team whittled down their list from 14,000 to a more manageable number, each of which they systematically tested using genetic experiments in animals. Their study was published in Cancer Cell (2014; doi:10.1016/j.ccr.2014.07.009).

Of the 37 lncRNAs the team fully tested, one known as focally amplified lncRNA on chromosome 1 (FAL1) had all the makings of an RNA oncogene. FAL1 is one of only a handful of lncRNAs to be linked to cancer to date. This knowledge is being applied for clinical applications.

For example, FAL1 expression may be a biomarker of BRCA-related cancer prognosis and the basis of new anticancer therapeutics. As proof-of-principle of the potential efficacy, Zhang's team grew human ovarian tumors in immunocompromised mice, then injected short-interfering RNAs to block the tumors' growth using RNA interference against FAL1. The tumors in treated animals shrank over the course of the experiment, while tumors in control animals continued to grow.

FAL1 is overexpressed in ovarian and breast cancer samples. Blocking the activity of the gene via RNA interference reduces cancer cells' growth, while overexpressing it in normal cells increases their growth. High FAL1 expression in human ovarian cancer samples tended to correlate with poor clinical prognosis.

"This is the first genome-wide study to use bioinformatics and clinical information to systematically identify one lncRNA, which we found to be oncogenic," Zhang said.

FAL1 expression may be able to serve as a biomarker of BRCA-related cancer prognosis, assuming these findings can be validated in other populations. But there also is the potential for new anticancer therapeutics, Zhang said, whether those are therapeutics specifically targeting FAL1 RNA or small molecules that block the interaction between FAL1 and BMI1.

[Only a handful of "Old Schooler" detractors cling to the disarmingly naive and totally non-mathematical (thus for software, useless) primitive notion of Crick (1956) & Ohno (1972) that genome function can ever be explained by less than 1% of the human DNA (tossed aside as "Junk DNA"), and in the DNA>RNA>PROTEIN expression there is "never" a sequence-information recurring from PROTEIN>DNA. The "Genes & Junk" Old School has been dead as a doornail by the first ENCODE, the latest (2007). The Principle of Recursive Genome Function (2008) explains put genome regulation on a mathematical basis (fractal recursive iteration) , where "fractal defects" in the DNA derail recursion and thus FractoGene (fractal DNA grows fractal organisms) opens up the new mathematical science , with the immediate protected utility of detecting "fractal defects of DNA" , popping up in the DNA, yield much earlier (and mathematically precise) diagnosis of the onset of cancerous growth (appearing as tumors later). Also, by matching the full genome (focusing on the 99% of "non-coding" DNA) with genome-tested available therapies, a mathematical matching yields "precision therapy". This vastly improves on the 80% non-effective "trial and error practice" of the many decades since "War on Cancer " by Nixon - who knows how many $100 Bn dollars mis-spent, yet leaving who knows how many hundreds of million patients to one of the most dreadful and expensive "slow turture" - andras_at_pellionisz_dot_com]

Priority Health Becomes First Health Plan to Cover Foundation Medicine's Tests

October 16, 2014

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb) – Priority Health has begun coverage of Foundation Medicine's genomic profiling services for cancer, making the health plan the first in the country to provide such coverage, the companies said after the close of the market on Thursday.

The positive coverage decision is for FoundationOne and FondationOne Heme. FoundationOne interrogates the entire coding region in 315 genes and select introns in 28 genes that are commonly altered in solid tumors. FoundationOne Heme analyzes DNA in 405 genes and RNA in 265 genes that are often altered in blood-based malignancies, sarcomas, and select pediatric cancers. Both services provide information that enable clinicians to more appropriately select therapies for their patients.

During the summer, the New York State Department of Health approved Foundation Medicine to market the tests to residents of the state.

Priority Health Associate Vice President of Medical Affairs John Fox said in a statement that cancers have been historically categorized and treated based on where they are located in the body. "With additional information available about the underlying genomic drivers of a tumor's growth, we're helping our members to access customized treatment options with targeted therapies," he said.

The health plan is based in Grand Rapids, Mich., and has more than 900,000 healthcare providers in its network. According to Priority Health's website, it has 600,000 members.

-Explanation for tests:----------------------------------------------------------------------------------------------------------------------

FoundationOne is a targeted genomic sequencing test for solid tumors that profiles the coding regions of 236 cancer-related genes, as well as 47 introns from 19 other genes for alterations associated with existing and experimental molecularly targeted therapies.

FoundationOne Heme specifically targets hematologic cancers such as leukemia, lymphoma, and myeloma, as well as sarcomas and pediatric cancers to guide treatment options for patients based on the genomic profiles of their cancer. The test involves sequencing of 405 full genes, select introns of another 31 genes, and RNA sequencing targeting 265 genes that are validated molecular targets for therapy or unambiguous drivers of oncogenesis in these cancers based on current knowledge.

[The Business Model of Genome Informatics has just become completed by providing a definitive answer to "where is the money?" Even without USA Insurance System "genome matched cancer therapy is viable (for the rich in the USA) - or for civilized countries where health care is a government supported system with built-in incentives for paying only for drugs that actually work. For what used to be in the US as "sick care" here, where "repeat customers" of cancer patients are "welcome to use as many chemos as possible before they die", the announcement that US Insurance System(s) will become interested in cost-efficacy is huge news. It enlarges the "reimbursed patient-base" in a rapidly escalating manner - and at the same time companies such as Foundation Medicine that leverage MANY Pharma-companies, inevitably trigger a competition among them "which pharma company will excel over competition by genome-testing their products". Foundation Medicine deserves huge credit for making this happen. At the same time, please note that FMI probes only "the coding regions of 236 genes" (though as Fouding Advisor noted, "cancer-related" genes could be potentially as many as all (19,000) human genes. Also note, that presently, for lack of understanding fractal recursive genome function (when misregulated, resulting in cancer), for the 98.7% of the human genome (that is "non-coding"), the leading edge of FMI currently probes only 19 genes (0.1% of all genes) for their "non-coding" (intronic) segments. The incredibly good news is that FMI already on their way to probe for cancer "non-coding DNA" at all. The growth potential is obviously phenomenal, and is phenomenally lucrative. - andras_at_pellionisz_dot_com]

ASHG: Data Science to Help Genomics Move from 'Artisanal' to 'Factory' (Google? IBM? Apple? GE Health? Microsoft? ... or Fast and Furious?)

October 20, 2014

By Ciara Curtin

SAN DIEGO (GenomeWeb) – While genomics has showed promise at a small scale for matching patients to treatments, scaling that capability up so that personalized medicine may be realized for all will require a lot more data to be sifted through, speakers at this year's American Society of Human Genetics meeting said.

"How can we apply those breakthroughs in data technology to help with the transition from world of one to a world of millions?" asked Google's David Glazer, referring to the increasing number of people who have undergone genome sequencing, at ASHG.

Genomics is generating a storm of data, not just in terms of sequencing reads coming off of newer and faster machines, but also in terms of sheer research output as more journal articles showing links between variants and disease are published. At the same time, groups are working on building data standards to facilitate the sharing of clinical and genomic data.

IBM's Ajay Royyuru also noted at ASHG that between 6,000 and 10,000 articles are published a year that mention cancer — an amount that people just can't realistically read, even though researchers and clinicians need to keep up to date to find the best treatment for patients.

"This is a problem that really deserves help," Royyuru said.

The key factors of such a process, Royyuru said, is that it has to be comprehensive and objective as well as scalable and fast. Additionally, he said, it has to be transparent and show the reasoning that led it to its conclusions.

He and his colleagues at IBM are turning to supercomputer Watson to digest those papers and how their findings may relate to patients.

Through the Precision Oncology workflow he and his colleagues developed, patient sequencing data is fed into Watson, which then compares it to what's housed in databases like PubMed, the National Cancer Center's Pathway Interaction Database, and DrugBank, among others. From this, Watson develops a conceptual model of the disease and outputs a set of treatment options. It also provides the reasoning behind choosing those possible therapies that may then be presented to a tumor board, for example.

The process of generating a report takes five to 10 minutes, he said.

Additionally, Royyuru said, Watson would learn from the process as data regarding the treatment given to a patient and that patient's response are fed back in.

Currently this pipeline is a prototype that IBM is working on in conjunction with the New York Genome Center, and Royyuru added that IBM plans on recruiting additional beta testers next year.

In addition to Watson, other data technologies and expertise from the computer science field could be refashioned to analyze genomic data.

Companies like Google have experience working with large amounts of data. For instance, Glazer noted that 100 hours of video are uploaded to YouTube every minute and that the number of Gmail users is 150 times the number of US PhDs.

He and his colleagues also have begun to test their tools — like Dremel and BigQuery —on genomic data from the 1,000 Genomes Project. The first step of a principal component analysis of 1,000 Genomes Project data is to make a similarity matrix, and that takes, he said, about two hours on 60 eight-core machines.

Begin able to quickly build research questions one after the other is part of what's needed for innovation, Glazer added.

Still, he noted that to move genomics and personalized medicine from its current "artisanal" status to "factory" mode, there needs to be better standards. The Global Alliance for Genomics and Health, of which Google and organizations like BGI-Shenzhen, Genome Canada, the US National Institutes of Health, and the Wellcome Trust are a part, are working on developing such standards to improve interoperability and enable data sharing. The group also is working with the Genome in a Bottle Consortium to develop benchmarking references.

Glazer believes these efforts will lead to more innovation to analyze and explore data.

[Glazer was publicly told, even if he did not know before, that innovation to analyze Recursive Genome Function was filed in 2002 August 1st, now in force till 2026 Mid-March, 8,280,641 AJP]

Mount Sinai Opens New Genomics Lab (in Branford, Connecticut) with Bank of Ion Torrent Sequencer

Bio-IT Word (Sept 11)

By Aaron Krol

September 11, 2014 | The old Roche 454 facility in Branford, Connecticut, will soon be returning to genomic science, as the Icahn Institute at Mount Sinai prepares to set up its second sequencing facility on grounds abandoned by Roche in its shutdown of 454 Life Sciences. Mount Sinai announced today that it has leased the space and purchased an initial bank of eight Ion Proton high throughput sequencers. “These instruments are getting installed, and we’ll be up and running next month,” says Glenn Farrell, Director of Mount Sinai’s Department of Genetics and Genomic Sciences.

Mount Sinai already operates one of the world’s leading hospital-affiliated sequencing centers at the Icahn School of Medicine in New York City. Under the leadership of systems biologist Eric Schadt, the Icahn Institute for Genomics and Multiscale Biology has become known both for tackling research studies into human disease on a grand scale, and for its early adoption of genomic testing as a tool in patient care. An Ion Proton cancer hotspot panel used at the Institute was recently approved by the New York State Department of Health for clinical use in refining cancer treatments, and Mount Sinai pursues more ambitious clinical projects under its research umbrella.

The New York City lab where Dr. Schadt works is now space-limited, Farrell told Bio-IT World, and Mount Sinai is establishing a second genetic testing location that can be more easily scaled up as the hospital system’s sequencing capabilities continue to grow. Branford is also home to a number of genetic specialists, making it an attractive setting for the new center. “With the 454 employees, and the adjacency to Yale University, you’ve got a lot of people with this type of skill set to hire,” says Farrell, adding that Mount Sinai is hiring between 20 and 25 scientists to staff the facility.

Among those hires is Todd Arnold, previously the VP for Research & Development at 454, and now the Managing Director of the new genetic testing lab. His team will be immediately joining a major research project already underway at the Icahn Institute: the Resilience Project, which aims to screen hundreds of thousands of healthy individuals for mutations that are predicted to cause devastating genetic disorders, with the goal of understanding factors that protect against these diseases.

“At the Icahn Institute, we’re known for big data, and we want to look at massive amounts of data points and separate the signal from the noise,” says Farrell. “We’re going to see projects, like the Resilience Project, that need massive high-throughput sample handling and analysis done at this facility.” The lab will also be involved in clinical diagnostics for the Mount Sinai hospital system.

Support for Life Tech

The Icahn Institute has designed a custom Ion Proton AmpliSeq Panel to use in these large-scale projects, covering 26,000 amplicons across more than 700 genes. As Eric Schadt explained to Bio-IT World by email, this panel, the largest ever designed for the platform, is intended to have as broad a clinical reach as possible. The genetic loci included in the panel cover all known variants linked to rare Mendelian disorders, as well as numerous gene-drug associations. “We then complemented this data by covering all regions harboring variants that are associated with common human diseases across the entire disease spectrum,” Schadt added, “so for example those loci that have been identified and highly replicated in GWAS [genome wide association studies] and WES/WGS [whole exome sequencing/whole genome sequencing] studies.” The resulting panel should be able to meaningfully contribute not only to the Resilience Project, but also to research on complex chronic diseases like cancer, diabetes, heart disease, and neurological disorders. Schadt also writes that the panel will be able to pick up both single-nucleotide variants, and small indels, which have often been a challenge for short-read technologies like the Proton.

[Branford, Connecticut is an outskirt of Yale University, where the late Prof. Mandelbrot was awarded Sterling Professorship. It is a delight to see Eric Schadt, who approves the fractal approach, "coming home" in more than one sense]

NCI, NVIDIA Providing $2M for Omics-based Cancer Data Research

August 28, 2014

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb) – The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the NVIDIA Foundation on Wednesday announced that they will provide up to $2 million in funding for the development of omics-based, data-intensive scientific tools to treat cancer.

CPTAC said it anticipates funding up to three awards totaling $1.8 million, while NVIDIA will make one award in the amount of $200,000 for projects aimed at creating tools that will enable the mining and interpretation of large-scale publicly available omics datasets. CPTAC and NVIDIA noted three research areas of interest, including the development of computational tools that use datasets to elucidate cancer biology and to advance the diagnosis, treatment, or prevention of cancer.

The organizations also are seeking projects to integrate new computational omics analysis methods into existing genomic data analysis pipelines to advance cancer biology knowledge and enable researchers to leverage omics advancements in cancer diagnosis and treatment, CPTAC and NVIDIA said.

Also of interest are efforts to develop new multi-omic simulation and/or visualization techniques that make computational biology accessible to researchers who have no programming experience.

The projects will use datasets from The Cancer Genome Atlas and CPTAC, as well as other publicly available omics datasets. Proposals will be assessed based on whether they advance new approaches or apply new insights "through parallel and/or visual computing in the area of computational omics;" whether the project will be used by or benefit multiple researchers and motivate new innovations; and whether the work leverages computational methods to solve a specific problem in computational omics, resulting in a "substantial impact" in cancer research.

Other criteria for funding include whether a project defines clear goals and a milestone-based plan for completion within a two-year time frame, and whether the work identifies obstacles and reasonable approaches to overcome them.

Applications are due Oct. 8.

[Applicants may want to secure the use of FractoGene IP (Patent 8,280,641 and Improvements of Best Methods post-2007, held as Trade Secrets). Should NVIDIA wish to secure that FractoGene IP excludes any "non-GPU" appliance-embedding, needs to match or overbid the soleley FPGA-based exclusive offer. All contacts to Kevin Roe, Esq. Fractogene Legal Department, 155 E Campbell Avenue, Campbell, CA 95008]

Fractal Genome yields 389,000 hits (392,000 a week after) - here is a list of over a thousand FRACTAL items just in PubMed.

My patent 8,280,641 has an original priority date of Aug. 1, 2002. Upon submission, since the utility of "fractal genome grows fractal organisms" ran head-against BOTH of the at the time ruling twin axioms ("Junk DNA" and "Central Dogma" of Nobelist and living Francis Crick), was blatantly dismissed - just like other (one-fold...) paradigm-shifts. For instance, "Jumping Genes" won a Nobel after 40 years of marginalization and ridicule. Never mind opinions. Ask "what is in it for me?" and "what is the deal?" (now that I finally have the patent in force...)

Since my FractoGene could not possibly be published, I filed the utility as a patent. USPTO (though both ENCODE -I in 2007 and ENCODE-II in 2012 shook the world that "the community of scientists must re-think longtime beliefs"), took a leisurely time (over a Decade...) to actually issue my patent. It is now in force till late March, 2026.

Today, Fractal Genome yields 389,000 hits on Google. Just in the top-rated PUBMED, after my priority date, you will find FRACTAL in 1,161 instances:

1. PLoS One. 2014 Aug 8;9(8):e104682. doi: 10.1371/journal.pone.0104682. eCollection


Exhaled aerosol pattern discloses lung structural abnormality: a sensitivity

study using computational modeling and FRACTAL analysis.

Xi J(1), Si XA(2), Kim J(1), Mckee E(3), Lin EB(4).

Author information:

(1)School of Engineering and Technology, Central Michigan University, Mount

Pleasant, Michigan, United States of America.

(2)Science Division, Calvin College, Grand Rapids, Michigan, United States of


(3)College of Medicine, Central Michigan University, Mount Pleasant, Michigan,

United States of America.

(4)Department of Mathematics, Central Michigan University, Mount Pleasant, Michigan,

United States of America.

BACKGROUND: Exhaled aerosol patterns, also called aerosol fingerprints, provide

clues to the health of the lung and can be used to detect disease-modified airway

structures. The key is how to decode the exhaled aerosol fingerprints and

retrieve the lung structural information for a non-invasive identification of

respiratory diseases.

OBJECTIVE AND METHODS: In this study, a CFD-FRACTAL analysis method was developed

to quantify exhaled aerosol fingerprints and applied it to one benign and three

malign conditions: a tracheal carina tumor, a bronchial tumor, and asthma.

Respirations of tracer aerosols of 1 µm at a flow rate of 30 L/min were

simulated, with exhaled distributions recorded at the mouth. Large eddy

simulations and a Lagrangian tracking approach were used to simulate respiratory

airflows and aerosol dynamics. Aerosol morphometric measures such as

concentration disparity, spatial distributions, and FRACTAL analysis were applied

to distinguish various exhaled aerosol patterns.

FINDINGS: Utilizing physiology-based modeling, we demonstrated substantial

differences in exhaled aerosol distributions among normal and pathological

airways, which were suggestive of the disease location and extent. With FRACTAL

analysis, we also demonstrated that exhaled aerosol patterns exhibited FRACTAL

behavior in both the entire image and selected regions of interest. Each exhaled

aerosol fingerprint exhibited distinct pattern parameters such as spatial

probability, FRACTAL dimension, lacunarity, and multiFRACTAL spectrum.

Furthermore, a correlation of the diseased location and exhaled aerosol spatial

distribution was established for asthma.

CONCLUSION: Aerosol-fingerprint-based breath tests disclose clues about the site

and severity of lung diseases and appear to be sensitive enough to be a practical

tool for diagnosis and prognosis of respiratory diseases with structural


PMCID: PMC4126729

PMID: 25105680 [PubMed - in process]

2. Phys Rev Lett. 2014 Jul 25;113(4):046806. Epub 2014 Jul 25.

Anderson localization on the bethe lattice: nonergodicity of extended States.

De Luca A(1), Altshuler BL(2), Kravtsov VE(3), Scardicchio A(4).

Author information:

(1)Laboratoire de Physique Théorique de l'ENS and Institut de Physique Theorique

Philippe Meyer 24, Rue Lhomond, 75005 Paris, France.

(2)Physics Department, Columbia University, 538 West 120th Street, New York, New

York 10027, USA.

(3)Abdus Salam International Center for Theoretical Physics, Strada Costiera 11,

34151 Trieste, Italy and L. D. Landau Institute for Theoretical Physics, 2

Kosygina Street, 119334 Moscow, Russia.

(4)Physics Department, Columbia University, 538 West 120th Street, New York, New

York 10027, USA and Abdus Salam International Center for Theoretical Physics,

Strada Costiera 11, 34151 Trieste, Italy and Physics Department, Princeton

University, Princeton, New Jersey 08544, USA and INFN, Sezione di Trieste, Strada

Costiera 11, 34151 Trieste, Italy.

Statistical analysis of the eigenfunctions of the Anderson tight-binding model

with on-site disorder on regular random graphs strongly suggests that the

extended states are multiFRACTAL at any finite disorder. The spectrum of FRACTAL

dimensions f(α) defined in Eq. (3) remains positive for α noticeably far from 1

even when the disorder is several times weaker than the one which leads to the

Anderson localization; i.e., the ergodicity can be reached only in the absence of

disorder. The one-particle multiFRACTALity on the Bethe lattice signals on a

possible inapplicability of the equipartition law to a generic many-body quantum

system as long as it remains isolated.

PMID: 25105646 [PubMed - in process]

3. J Exp Psychol Hum Percept Perform. 2014 Jul 7. [Epub ahead of print]

Haptic Perceptual Intent in Quiet Standing Affects MultiFRACTAL Scaling of

Postural Fluctuations.

Palatinus Z, Kelty-Stephen DG, Kinsella-Shaw J, Carello C, Turvey MT.

Research on dynamic touch has shown that when a rod strapped to the shoulders is

wielded via axial rotations, flexions-extensions, and lateral bending of the

trunk, participants can selectively perceive whole rod length and partial rod

length (e.g., a leftward segment) with precision comparable to wielding by hand

(Palatinus, Carello & Turvey, 2011). The present research addressed whether this

haptic ability is preserved in quiet standing, when postural control is limited

to center of pressure (COP) fluctuations at the mm/ms scale, and, if so, whether

the intentions ("perceive partial," "perceive whole") are distinguishable within

the fluctuations. Given standard manipulations of rod length and attached mass,

participants provided significantly distinct, appropriately scaled, whole and

partial estimates of rod length. COP displacement time series were subjected to

multiFRACTAL, detrended fluctuation analysis. The resultant spectrum of FRACTAL

scaling exponents for gradually different-sized fluctuations revealed that

"perceive partial" was manifest as larger exponents for progressively smaller

fluctuations than "perceive whole." Our results indicate (a) that the significant

mechanical variables for haptically perceiving object extent are available in the

small scale of normal body sway, and (b) that these seemingly "passive" movements

reflect the intention of the perceiver. (PsycINFO Database Record (c) 2014 APA,

all rights reserved).

PMID: 24999615 [PubMed - as supplied by publisher]

4. Opt Lett. 2014 Jul 1;39(13):3718-21. doi: 10.1364/OL.39.003718.

Experimental confirmation of long-memory correlations in star-wander data.

Zunino L, Gulich D, Funes G, Ziad A.

In this Letter we have analyzed the temporal correlations of the angle-of-arrival

fluctuations of stellar images. Experimentally measured data were carefully

examined by implementing multiFRACTAL detrended fluctuation analysis. This

algorithm is able to discriminate the presence of FRACTAL and multiFRACTAL

structures in recorded time sequences. We have confirmed that turbulence-degraded

stellar wavefronts are compatible with a long-memory correlated monoFRACTAL

process. This experimental result is quite significant for the accurate

comprehension and modeling of the atmospheric turbulence effects on the stellar

images. It can also be of great utility within the adaptive optics field.

PMID: 24978719 [PubMed - in process]

5. Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Mar;89(3):032916. Epub 2014 Mar 24.

Multiscale multiFRACTAL analysis of traffic signals to uncover richer structures.

Wang J(1), Shang P(2), Cui X(3).

Author information:

(1)Department of Mathematics, School of Science, Beijing Jiaotong University,

Beijing 100044, People's Republic of China and Division of Interdisciplinary

Medicine and Biotechnology, Department of Medicine, Beth Israel Deaconess Medical

Center/Harvard Medical School, Boston, Massachusetts 02215, USA.

(2)Department of Mathematics, School of Science, Beijing Jiaotong University,

Beijing 100044, People's Republic of China.

(3)Division of Interdisciplinary Medicine and Biotechnology, Department of Medicine,

Beth Israel Deaconess Medical Center/Harvard Medical School, Boston,

Massachusetts 02215, USA.

MultiFRACTAL detrended fluctuation analysis (MF-DFA) is the most popular method

to detect multiFRACTAL characteristics of considerable signals such as traffic

signals. When FRACTAL properties vary from point to point along the series, it

leads to multiFRACTALity. In this study, we concentrate not only on the fact that

traffic signals have multiFRACTAL properties, but also that such properties

depend on the time scale in which the multiFRACTALity is computed. Via the

multiscale multiFRACTAL analysis (MMA), traffic signals appear to be far more

complex and contain more information which MF-DFA cannot explore by using a fixed

time scale. More importantly, we do not have to avoid data sets with crossovers

or narrow the investigated time scales, which may lead to biased results.

Instead, the Hurst surface provides a spectrum of local scaling exponents at

different scale ranges, which helps us to easily position these crossovers.

Through comparing Hurst surfaces for signals before and after removing periodical

trends, we find periodicities of traffic signals are the main source of the

crossovers. Besides, the Hurst surface of the weekday series behaves differently

from that of the weekend series. Results also show that multiFRACTALity of

traffic signals is mainly due to both broad probability density function and

correlations. The effects of data loss are also discussed, which suggests that we

should carefully handle MMA results when the percentage of data loss is larger

than 40%.

PMID: 24730922 [PubMed - in process]

6. Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Mar;89(3):032814. Epub 2014 Mar 31.

Topological properties and FRACTAL analysis of a recurrence network constructed

from fractional Brownian motions.

Liu JL(1), Yu ZG(2), Anh V(3).

Author information:

(1)Hunan Key Laboratory for Computation and Simulation in Science and Engineering

and Key Laboratory of Intelligent Computing and Information Processing of

Ministry of Education, Xiangtan University, Xiangtan, Hunan 411105, China.

(2)Hunan Key Laboratory for Computation and Simulation in Science and Engineering

and Key Laboratory of Intelligent Computing and Information Processing of

Ministry of Education, Xiangtan University, Xiangtan, Hunan 411105, China and

School of Mathematical Sciences, Queensland University of Technology, GPO Box

2434, Brisbane, Q4001, Australia.

(3)School of Mathematical Sciences, Queensland University of Technology, GPO Box

2434, Brisbane, Q4001, Australia.

Many studies have shown that we can gain additional information on time series by

investigating their accompanying complex networks. In this work, we investigate

the fundamental topological and FRACTAL properties of recurrence networks

constructed from fractional Brownian motions (FBMs). First, our results indicate

that the constructed recurrence networks have exponential degree distributions;

the average degree exponent 〈λ〉 increases first and then decreases with the

increase of Hurst index H of the associated FBMs; the relationship between H and

〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif

rank distribution of recurrence networks, so that we can better understand

networks at the local structure level. We find the interesting superfamily

phenomenon, i.e., the recurrence networks with the same motif rank pattern being

grouped into two superfamilies. Last, we numerically analyze the FRACTAL and

multiFRACTAL properties of recurrence networks. We find that the average FRACTAL

dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the

associated FBMs, and their dependence approximately satisfies the linear formula

〈dB〉≈2-H, which means that the FRACTAL dimension of the associated recurrence

network is close to that of the graph of the FBM. Moreover, our numerical results

of multiFRACTAL analysis show that the multiFRACTALity exists in these recurrence

networks, and the multiFRACTALity of these networks becomes stronger at first and

then weaker when the Hurst index of the associated time series becomes larger

from 0.4 to 0.95. In particular, the recurrence network with the Hurst index

H=0.5 possesses the strongest multiFRACTALity. In addition, the dependence

relationships of the average information dimension 〈D(1)〉 and the average

correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with

linear functions. Our results strongly suggest that the recurrence network

inherits the basic characteristic and the FRACTAL nature of the associated FBM


PMID: 24730906 [PubMed - in process]

7. Biomed Res Int. 2014;2014:320767. doi: 10.1155/2014/320767. Epub 2014 Feb 25.

Streamlining cutaneous melanomas in young women of the Belgian Mosan region.

Hermanns-Lê T(1), Piérard S(2).

Author information:

(1)Department of Dermatopathology, Unilab Lg, University Hospital of Liège, 4000

Liège, Belgium ; Dermatology Unit, Diagnostic Centre, 4800 Verviers, Belgium.

(2)INTELSIG Laboratory, Montefiore Institute, University of Liège, 4000 Liège,


Sporadic cutaneous melanoma (SCM) has shown a dramatic increase in incidence in

Caucasian populations over the past few decades. A particular epidemiological

increase was reported in women during their childbearing age. In the Belgian

Mosan region, a progressive unremitting increase in SCM incidence was noticed in

young women for the past 35 years. The vast majority of these SCMs were of the

superficial type without any obvious relationship with a large number of

melanocytic nevi or with signs of frequent and intense sunlight exposures as

disclosed by the extent in the mosaic subclinical melanoderma. A series of

investigations pointed to a possible relationship linking the development of some

SCM to the women hormonal status including the effect of hormonal disruptors.

These aspects remain, however, unsettled and controversial. It is possible to

differentiate and clearly quantify the SCM shape, size, scalloped border, and

variegated pigmentation using computerized morphometry as well as FRACTAL and

multiFRACTAL methods.

PMCID: PMC3955611

PMID: 24716193 [PubMed - in process]

8. Clin Physiol Funct Imaging. 2014 Jan 13. doi: 10.1111/cpf.12126. [Epub ahead of


Twenty-four hour variation in heart rate variability indices derived from

fractional differintegration.

Lewis MJ(1), McNarry MA.

Author information:

(1)College of Engineering, Swansea University, Swansea, UK.

Assuming that RR time-series behave as a fractionally differintegrated Gaussian

process, García-González et al. (2003) recently proposed new indices for

quantifying variability and structure in RR data. One of these was the

'fractional noise quantifier' (fnQ), measuring the departure of an RR time-series

from a monoFRACTAL structure (i.e. a measure of its multiFRACTALity). Sixty-nine

participants (aged = 34·5 ± 12·4 years, body mass index

(BMI) = 23·9 ± 2·9 kg m(-2) , maximal oxygen uptake rate (V˙O2peak

) = 42·4 ± 10·9 ml min(-1)  kg(-1) , 39 males) provided continuous beat-to-beat

ECG recordings for a 24-h period. Fractional differintegration was used to

quantify fnQ, and heart rate variability was calculated in the time domain. All

variables were evaluated during consecutive 1-h periods and also during four 6-h

blocks corresponding to morning, afternoon, evening and night periods. Apart from

RR, circadian trends in all variables were independent of gender (P = 0·11-0·59).

Apart from fnQ, all variables exhibited circadian variation (0·0005<P<0·012).

Although fnQ was statistically uniform during the 24-h period, it showed a trend

towards elevated values during evening and night. The main finding of this study

was that fnQ was elevated by around 10% during the evening and night, although

this was not statistically significant. This suggests that the structure of RR

time-series in healthy individuals is most strongly 'multiFRACTAL' during evening

and night periods. fnQ appears to be a plausible surrogate measure of

multiFRACTALity in RR time-series.

© 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine.

Published by John Wiley & Sons Ltd.

PMID: 24666809 [PubMed - as supplied by publisher]

9. ScientificWorldJournal. 2014 Jan 22;2014:894546. doi: 10.1155/2014/894546.

eCollection 2014.

MultiFRACTAL framework based on blanket method.

Paskaš MP(1), Reljin IS(2), Reljin BD(3).

Author information:

(1)School of Electrical Engineering, University of Belgrade, Bulevar kralja

Aleksandra 73, 11121 Belgrade, Serbia ; Innovation Center of School of Electrical

Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11121

Belgrade, Serbia.

(2)School of Electrical Engineering, University of Belgrade, Bulevar kralja

Aleksandra 73, 11121 Belgrade, Serbia.

(3)Innovation Center of School of Electrical Engineering, University of Belgrade,

Bulevar kralja Aleksandra 73, 11121 Belgrade, Serbia.

This paper proposes two local multiFRACTAL measures motivated by blanket method

for calculation of FRACTAL dimension. They cover both FRACTAL approaches familiar

in image processing. The first two measures (proposed Methods 1 and 3) support

model of image with embedded dimension three, while the other supports model of

image embedded in space of dimension three (proposed Method 2). While the

classical blanket method provides only one value for an image (FRACTAL dimension)

multiFRACTAL spectrum obtained by any of the proposed measures gives a whole

range of dimensional values. This means that proposed multiFRACTAL blanket model

generalizes classical (monoFRACTAL) blanket method and other versions of this

monoFRACTAL approach implemented locally. Proposed measures are validated on

Brodatz image database through texture classification. All proposed methods give

similar classification results, while average computation time of Method 3 is

substantially longer.

PMCID: PMC3919058

PMID: 24578664 [PubMed - in process]

10. Water Res. 2014 Apr 15;53:322-8. doi: 10.1016/j.watres.2014.01.008. Epub 2014 Jan


Settling velocities of multiFRACTAL flocs formed in chemical coagulation process.

Vahedi A(1), Gorczyca B(2).

Author information:

(1)Red River College, Department of Civil Engineering Technology, Winnipeg,

Manitoba, Canada. Electronic address:

(2)Department of Civil Engineering, University of Manitoba, Canada. Electronic


A number of different flocculation mechanisms are involved in the formation of

chemical coagulation flocs. Consequently, two flocs with the same size may have

been formed by different mechanisms of aggregation and therefore have different

arrangement of primary particles. As a result, two flocs with the same size may

have different masses or mass distributions and therefore, different settling

velocities. Although the correct estimation of the floc mass and density is

critical for the development of the floc settling model, none of the suggested

floc settling models incorporate the information on mass distribution and

variable density of flocs. A probability-based method is used to determine the

floc FRACTAL dimensions on floc images. The results demonstrated that flocs

formed in lime softening coagulation are multiFRACTAL. The multiFRACTAL spectra

indicated the existence of a multiple FRACTAL dimensions as opposed to the unique

box-counting dimension which is a morphology-based FRACTAL dimensions typically

introduced into the Stokes' Law. These FRACTAL dimensions may provide information

on the flocs' aggregation mechanism, floc's structure, and the distribution of

mass inside the floc. More research is required to investigate how to utilize the

information obtained from the multiFRACTAL spectra to incorporate the variable

floc density and nonhomogeneous mass distribution of flocs into the floc settling


Copyright © 2014 Elsevier Ltd. All rights reserved.

PMID: 24530551 [PubMed - in process]

11. Soc Neurosci. 2014;9(3):219-34. doi: 10.1080/17470919.2014.882861. Epub 2014 Feb


Neural signatures of team coordination are revealed by multiFRACTAL analysis.

Likens AD(1), Amazeen PG, Stevens R, Galloway T, Gorman JC.

Author information:

(1)a Department of Psychology , Arizona State University , Tempe , USA.

The quality of a team depends on its ability to deliver information through a

hierarchy of team members and negotiate processes spanning different time scales.

That structure and the behavior that results from it pose problems for

researchers because multiply-nested interactions are not easily separated. We

explored the behavior of a six-person team engaged in a Submarine Piloting and

Navigation (SPAN) task using the tools of dynamical systems. The data were a

single entropy time series that showed the distribution of activity across six

team members, as recorded by nine-channel electroencephalography (EEG). A single

team's data were analyzed for the purposes of illustrating the utility of

multiFRACTAL analysis and allowing for in-depth exploratory analysis of temporal

characteristics. Could the meaningful events experienced by one of these teams be

captured using multiFRACTAL analysis, a dynamical systems tool that is

specifically designed to extract patterns across levels of analysis? Results

indicate that nested patterns of team activity can be identified from neural data

streams, including both routine and novel events. The novelty of this tool is the

ability to identify social patterns from the brain activity of individuals in the

social interaction. Implications for application and future directions of this

research are discussed.

PMID: 24517441 [PubMed - indexed for MEDLINE]

12. Comput Math Methods Med. 2013;2013:152828. doi: 10.1155/2013/152828. Epub 2013

Dec 17.

Coarse-grained multiFRACTALity analysis based on structure function measurements

to discriminate healthy from distressed foetuses.

Oudjemia S(1), Zaylaa A(2), Haddab S(1), Girault JM(2).

Author information:

(1)University of Mouloud Mammeri, Tizi-Ouzou, Algeria.

(2)Signal & Imaging Group, University François Rabelais of Tours, UMR INSERM U930,

PRES Loire Valley University, 7 Avenue Marcel Dassault, 37200 Tours, Cedex,


This paper proposes a combined coarse-grained multiFRACTAL method to discriminate

between distressed and normal foetuses. The coarse-graining operation was

performed by means of a coarse-grained procedure and the multiFRACTAL operation

was based on a structure function. The proposed method was evaluated by one

hundred recordings including eighty normal foetuses and twenty distressed

foetuses. We found that it was possible to discriminate between distressed and

normal foetuses using the Hurst exponent, singularity, and Holder spectra.

PMCID: PMC3877591

PMID: 24454527 [PubMed - indexed for MEDLINE]

13. Microvasc Res. 2014 Mar;92:62-71. doi: 10.1016/j.mvr.2014.01.005. Epub 2014 Jan


Functional slit lamp biomicroscopy for imaging bulbar conjunctival

microvasculature in contact lens wearers.

Jiang H(1), Zhong J(2), DeBuc DC(3), Tao A(4), Xu Z(4), Lam BL(3), Liu C(5), Wang


Author information:

(1)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA; Department of

Neurology, University of Miami, Miami, FL, USA. Electronic address:

(2)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA; Department of

Ophthalmology, Hangzhou First People's Hospital, Hangzhou, Zhejiang, China.

(3)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA.

(4)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA; School of

Ophthalmology and Optometry, Wenzhou Medical College, Wenzhou, Zhejiang, China.

(5)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA; Department of

Biomedical Engineering, University of Miami, Miami, FL, USA.

PURPOSE: To develop, test and validate functional slit lamp biomicroscopy (FSLB)

for generating non-invasive bulbar conjunctival microvascular perfusion maps

(nMPMs) and assessing morphometry and hemodynamics.

METHODS: FSLB was adapted from a traditional slit-lamp microscope by attaching a

digital camera to image the bulbar conjunctiva to create nMPMs and measure

venular blood flow hemodynamics. High definition images with a large field of

view were obtained on the temporal bulbar conjunctiva for creating nMPMs. A high

imaging rate of 60 frames per second and an ~210× high magnification were

achieved using the camera inherited high speed setting and Movie Crop Function,

for imaging hemodynamics. Custom software was developed to segment bulbar

conjunctival nMPMs for further FRACTAL analysis and quantitatively measure blood

vessel diameter, blood flow velocity and flow rate. Six human subjects were

imaged before and after 6h of wearing contact lenses. MonoFRACTAL and

multiFRACTAL analyses were performed to quantify FRACTALity of the nMPMs.

RESULTS: The mean bulbar conjunctival vessel diameter was 18.8 ± 2.7 μm at

baseline and increased to 19.6 ± 2.4 μm after 6h of lens wear (P=0.020). The

blood flow velocity was increased from 0.60 ± 0.12 mm/s to 0.88 ± 0.21 mm/s

(P=0.001). The blood flow rate was also increased from 129.8 ± 59.9 pl/s to 207.2

± 81.3 pl/s (P=0.001). Bulbar conjunctival nMPMs showed the intricate details of

the bulbar conjunctival microvascular network. At baseline, FRACTAL dimension was

1.63 ± 0.05 and 1.71 ± 0.03 analyzed by monoFRACTAL and multiFRACTAL analyses,

respectively. Significant increases in FRACTAL dimensions were found after 6h of

lens wear (P<0.05).

CONCLUSIONS: Microvascular network's FRACTALity, morphometry and hemodynamics of

the human bulbar conjunctiva can be measured easily and reliably using FSLB. The

alternations of the FRACTAL dimensions, morphometry and hemodynamics during

contact lens wear may indicate ocular microvascular responses to contact lens


Copyright © 2014 Elsevier Inc. All rights reserved.

PMCID: PMC3960300 [Available on 2015/3/1]

PMID: 24444784 [PubMed - in process]

14. Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Oct;88(4):042116. Epub 2013 Oct 9.

Localization-delocalization transition of the instantaneous normal modes of

liquid water.

Huang BC(1), Chang CH.

Author information:

(1)Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan.

Despite the fact that the localization-delocalization transition (LDT) widely

exists in wave systems, quantitative studies on its critical and multiFRACTAL

properties are mainly focused on solids. In this work, these properties are

investigated on the vibrational motions of liquid water. Simulations of up to

18000 molecules on the flexible extended simple point charge water model provide

nearly 10(6) instantaneous normal modes. They are shown to undergo an LDT close

to the translational transition and exhibit multiFRACTAL fluctuations while

approaching the LDT. In combination with finite-size scaling, multiFRACTAL

analysis predicts the critical frequency Im(ω(c))≈-131.6 cm(-1) for unstable

modes at room temperature. The estimated critical exponent ν≈1.60 is close to

those of other calculated systems in the same Wigner-Dyson class. At the LDT, the

FRACTAL spectrum f(α) and the most probable local vibrational intensity

α(mc)≈4.04 coincide with those of the Anderson model, which might be additional

universal properties of LDT in more general wave systems. The results extend the

validity of the multiFRACTAL scaling approach beyond Andersonian systems to a

Hessian system.

PMID: 24229125 [PubMed]

15. J Med Eng Technol. 2014 Jan;38(1):55-61. doi: 10.3109/03091902.2013.849298. Epub

2013 Nov 14.

MultiFRACTAL application on electrocardiogram.

Mercy Cleetus HM(1), Singh D.

Author information:

(1)Department of Instrumentation and Control, Dr B. R Ambedkar National Institute of

Technology , Jalandhar (Punjab) , India 144011.

MultiFRACTAL detrended fluctuation analysis is applied to analyse the degree of

disorders, complexity and irregularity based on scaling behaviour of

electrocardiogram. Since this method is based on random walk theory, noise level

due to imperfect measurement in recording is reduced and it can systematically

eliminate trends of different orders. The essence of this method is to extract

the FRACTAL features in ECG which can reflect changes in adaptability of

physiological processes and to classify the pathological conditions and can lead

to successful diagnosis. FRACTAL analysis is, therefore, a promising diagnostic

tool in cardiovascular disease diagnosis and evaluation.

PMID: 24228785 [PubMed - indexed for MEDLINE]

16. Biomed Mater Eng. 2014;24(1):163-71. doi: 10.3233/BME-130796.

Evaluation of breast cancer chemotherapy efficacy with multiFRACTAL spectrum

analysis of magnetic resonance image.

Li L(1), Hu WY, Liu LZ, Pang YC, Shao YZ.

Author information:

(1)School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275,

China State Key Laboratory of Oncology in Southern China, Imaging Diagnostic and

Interventional Center, Cancer Center, Sun Yat-sen University, Guangzhou 510060,


MultiFRACTAL spectrum analysis of dynamic contrast enhanced (DCE) breast MR

images was used to establish a new quantitative analysis method for solid tumor

blood perfusion and to explore its applicability in evaluating efficacy of breast

cancer chemotherapy. Five randomly selected patients suffering from newly

diagnosed malignant breast nodule lesions were enrolled in this study, and four

of them were treated with neoadjuvant chemotherapy. Their DCE breast MR images

were collected before and after treatment. Chemotherapeutic efficacy was analyzed

using international response evaluation criteria for solid tumors (RECIST).

Sandbox method for statistical number density was employed to measure and

calculate multiFRACTAL spectra of DCE breast MR images with spatiotemporal

characteristics. MultiFRACTAL spectral data of malignant lesions before and after

chemotherapy were compared. MultiFRACTAL spectra of malignant lesions show an

asymmetric bell-shape. Chemotherapy efficacy was assessed to be partial remission

(PR) for three patients and their multiFRACTAL spectral width significantly

increased after chemotherapy while to be stable disease (SD) for other patient

and of her changed slightly. MultiFRACTAL spectral width correlates with

blood-supply condition of tumor lesion before and after chemotherapy, providing a

potential suitable characteristic parameter for evaluating chemotherapeutic

efficacy quantitatively.

PMID: 24211895 [PubMed - indexed for MEDLINE]

17. J Theor Biol. 2014 Feb 21;343:44-53. doi: 10.1016/j.jtbi.2013.10.011. Epub 2013

Oct 31.

MultiFRACTAL analysis of neutral community spatial structure.

Yakimov BN(1), Iudin DI(2), Solntsev LA(3), Gelashvili DB(3).

Author information:

(1)Department of Ecology, Faculty of Biology, Nizhny Novgorod State University,

Prospekt Gagarina 23, Nizhny Novgorod 603950, Russia; Institute of Applied

Physics of the Russian Academy of Sciences, Ul'yanov Street 46, Nizhny Novgorod

603950, Russia. Electronic address:

(2)Department of Ecology, Faculty of Biology, Nizhny Novgorod State University,

Prospekt Gagarina 23, Nizhny Novgorod 603950, Russia; Institute of Applied

Physics of the Russian Academy of Sciences, Ul'yanov Street 46, Nizhny Novgorod

603950, Russia.

(3)Department of Ecology, Faculty of Biology, Nizhny Novgorod State University,

Prospekt Gagarina 23, Nizhny Novgorod 603950, Russia.

The spatial structure of neutral communities has nontrivial properties, which are

described traditionally by the Species-area relationship (SAR) and the Species

Abundance Distribution, (SAD). FRACTAL analysis is an alternative way to describe

community structure, the final product of which - a multiFRACTAL spectrum -

combines information both on the scaling parameters of species richness (similar

to SAR), and about species' relative abundances (similar to SAD). We conducted a

multiFRACTAL analysis of community spatial structure in a neutral lattice-based

model. In a realistic range of dispersal distances, moments of the species

abundance distribution form a family of curves of the same shape, which are

reduced to a single universal curve through a scaling collapse procedure. Trivial

scaling is observed on small and large scales, which reflects homogeneity of

species distribution at small scales and a limiting log-series distribution at

large scales. MultiFRACTAL spectra for different speciation rates and dispersal

kernels are obtained for the intermediate region of scaling. Analysis of spectra

reveals that the key model parameters determine not only the species richness and

its scaling, but also of species dominance and rarity. We discovered a phenomenon

of negative dimensions in the multiFRACTAL spectrum. Negative dimensions have no

direct interpretation from a purely physical point of view, but have biological

meaning because they reflect the negative relationship between the number of

singletons and the area.

© 2013 Elsevier Ltd. All rights reserved.

PMID: 24184220 [PubMed - in process]

18. Biochim Biophys Acta. 2014 Jan;1840(1):565-76. doi: 10.1016/j.bbagen.2013.10.015.

Epub 2013 Oct 17.

Physico-chemical characterization and the in vitro genotoxicity of medical

implants metal alloy (TiAlV and CoCrMo) and polyethylene particles in human


Gajski G(1), Jelčić Z, Oreščanin V, Gerić M, Kollar R, Garaj-Vrhovac V.

Author information:

(1)Institute for Medical Research and Occupational Health, Mutagenesis Unit, 10000

Zagreb, Croatia. Electronic address:

BACKGROUND: The main objective of the present study was to investigate chemical

composition and possible cyto/genotoxic potential of several medical implant

materials commonly used in total hip joint replacement.

METHODS: Medical implant metal alloy (Ti6Al4V and CoCrMo) and high density

polyethylene particles were analyzed by energy dispersive X-ray spectrometry

while toxicological characterization was done on human lymphocytes using

multi-biomarker approach.

RESULTS: Energy dispersive X-ray spectrometry showed that none of the elements

identified deviate from the chemical composition defined by appropriate ISO

standard. Toxicological characterization showed that the tested materials were

non-cyto/genotoxic as determined by the comet and cytokinesis-block micronucleus

(CBMN) assay. Particle morphology was found (by using scanning electron and

optical microscope) as flat, sharp-edged, irregularly shaped fiber-like grains

with the mean particle size less than 10µm; this corresponds to the so-called

"submicron wear". The very large surface area per wear volume enables high

reactivity with surrounding media and cellular elements.

CONCLUSIONS: Although orthopedic implants proved to be non-cyto/genotoxic, in

tested concentration (10μg/ml) there is a constant need for monitoring of

patients that have implanted artificial hips or other joints, to minimize the

risks of any unwanted health effects.

GENERAL SIGNIFICANCE: The FRACTAL and multiFRACTAL analyses, performed in order

to evaluate the degree of particle shape effect, showed that the FRACTAL and

multiFRACTAL terms are related to the "remnant" level of the particles' toxicity

especially with the cell viability (trypan blue method) and total number of

nucleoplasmic bridges and nuclear buds as CBMN assay parameters.

© 2013.

PMID: 24140394 [PubMed - indexed for MEDLINE]

19. Front Neurol. 2013 Oct 9;4:158. doi: 10.3389/fneur.2013.00158. eCollection 2013.

Long-Range Temporal Correlations, MultiFRACTALity, and the Causal Relation

between Neural Inputs and Movements.

Hu J(1), Zheng Y, Gao J.

Author information:

(1)Institute of Complexity Science and Big Data Technology, Guangxi University ,

Nanning , China ; PMB Intelligence LLC , Sunnyvale, CA , USA.

Understanding the causal relation between neural inputs and movements is very

important for the success of brain-machine interfaces (BMIs). In this study, we

analyze 104 neurons' firings using statistical, information theoretic, and

FRACTAL analysis. The latter include Fano factor analysis, multiFRACTAL adaptive

FRACTAL analysis (MF-AFA), and wavelet multiFRACTAL analysis. We find neuronal

firings are highly non-stationary, and Fano factor analysis always indicates

long-range correlations in neuronal firings, irrespective of whether those

firings are correlated with movement trajectory or not, and thus does not reveal

any actual correlations between neural inputs and movements. On the other hand,

MF-AFA and wavelet multiFRACTAL analysis clearly indicate that when neuronal

firings are not well correlated with movement trajectory, they do not have or

only have weak temporal correlations. When neuronal firings are well correlated

with movements, they are characterized by very strong temporal correlations, up

to a time scale comparable to the average time between two successive reaching

tasks. This suggests that neurons well correlated with hand trajectory

experienced a "re-setting" effect at the start of each reaching task, in the

sense that within the movement correlated neurons the spike trains' long-range

dependences persisted about the length of time the monkey used to switch between

task executions. A new task execution re-sets their activity, making them only

weakly correlated with their prior activities on longer time scales. We further

discuss the significance of the coalition of those important neurons in executing

cortical control of prostheses.

PMCID: PMC3793199

PMID: 24130549 [PubMed]

20. IEEE Trans Image Process. 2013 Nov;22(11):4422-35. doi: 10.1109/TIP.2013.2273669.

3D lacunarity in multiFRACTAL analysis of breast tumor lesions in dynamic

contrast-enhanced magnetic resonance imaging.

Soares F, Janela F, Pereira M, Seabra J, Freire MM.

Dynamic contrast-enhanced magnetic resonance (DCE-MR) of the breast is especially

robust for the diagnosis of cancer in high-risk women due to its high

sensitivity. Its specificity may be, however, compromised since several benign

masses take up contrast agent as malignant lesions do. In this paper, we propose

a novel method of 3D multiFRACTAL analysis to characterize the spatial complexity

(spatial arrangement of texture) of breast tumors at multiple scales.

Self-similar properties are extracted from the estimation of the multiFRACTAL

scaling exponent for each clinical case, using lacunarity as the multiFRACTAL

measure. These properties include several descriptors of the multiFRACTAL spectra

reflecting the morphology and internal spatial structure of the enhanced lesions

relatively to normal tissue. The results suggest that the combined multiFRACTAL

characteristics can be effective to distinguish benign and malignant findings,

judged by the performance of the support vector machine classification method

evaluated by receiver operating characteristics with an area under the curve of

0.96. In addition, this paper confirms the presence of multiFRACTALity in DCE-MR

volumes of the breast, whereby multiple degrees of self-similarity prevail at

multiple scales. The proposed feature extraction and classification method have

the potential to complement the interpretation of the radiologists and supply a

computer-aided diagnosis system.

PMID: 24057004 [PubMed - indexed for MEDLINE]

21. Hum Mov Sci. 2013 Aug;32(4):633-51. doi: 10.1016/j.humov.2013.01.008. Epub 2013

Aug 22.

MultiFRACTAL formalisms of human behavior.

Ihlen EA(1), Vereijken B.

Author information:

(1)Department of Neuroscience, Norwegian University of Science and Technology,

Trondheim, Norway. Electronic address:

With the mounting realization that variability is an inevitable part of human

behavior comes the need to integrate this phenomenon in concomitant models and

theories of motor control. Among other things, this has resulted in a debate

throughout the last decades about the origin of variability in behavior, the

outcome of which has important implications for motor control theories. To date,

a monoFRACTAL formalism of variability has been used as the basis for arguing for

component- versus interaction-oriented theories of motor control. However,

monoFRACTAL formalism alone cannot decide between the opposing sides of the

debate. The present theoretical overview introduces multiFRACTAL formalisms as a

necessary extension of the conventional monoFRACTAL formalism. In multiFRACTAL

formalisms, the scale invariance of behavior is numerically defined as a spectrum

of scaling exponents, rather than a single average exponent as in the monoFRACTAL

formalism. Several methods to estimate the multiFRACTAL spectrum of scaling

exponents - all within two multiFRACTAL formalisms called large deviation and

Legendre formalism - are introduced and briefly discussed. Furthermore, the

multiFRACTAL analyses within these two formalisms are applied to several

performance tasks to illustrate how explanations of motor control vary with the

methods used. The main section of the theoretical overview discusses the

implications of multiFRACTAL extensions of the component- and

interaction-oriented models for existing theories of motor control.

Copyright © 2013 Elsevier B.V. All rights reserved.

PMID: 24054900 [PubMed - indexed for MEDLINE]

22. Comput Math Methods Med. 2013;2013:262931. doi: 10.1155/2013/262931. Epub 2013

Aug 19.

Scale-specific multiFRACTAL medical image analysis.

Braverman B(1), Tambasco M.

Author information:

(1)Department of Physics, MIT-Harvard Center for Ultracold Atoms and Research

Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA

02139, USA.

FRACTAL geometry has been applied widely in the analysis of medical images to

characterize the irregular complex tissue structures that do not lend themselves

to straightforward analysis with traditional Euclidean geometry. In this study,

we treat the nonFRACTAL behaviour of medical images over large-scale ranges by

considering their box-counting FRACTAL dimension as a scale-dependent parameter

rather than a single number. We describe this approach in the context of the more

generalized Rényi entropy, in which we can also compute the information and

correlation dimensions of images. In addition, we describe and validate a

computational improvement to box-counting FRACTAL analysis. This improvement is

based on integral images, which allows the speedup of any box-counting or similar

FRACTAL analysis algorithm, including estimation of scale-dependent dimensions.

Finally, we applied our technique to images of invasive breast cancer tissue from

157 patients to show a relationship between the FRACTAL analysis of these images

over certain scale ranges and pathologic tumour grade (a standard prognosticator

for breast cancer). Our approach is general and can be applied to any medical

imaging application in which the complexity of pathological image structures may

have clinical value.

PMCID: PMC3760300

PMID: 24023588 [PubMed - indexed for MEDLINE]

23. PLoS One. 2013 Aug 21;8(8):e69000. doi: 10.1371/journal.pone.0069000. eCollection


MultiFRACTAL analysis for nutritional assessment.

Park Y(1), Lee K, Ziegler TR, Martin GS, Hebbar G, Vidakovic B, Jones DP.

Author information:

(1)Division of Pulmonary, Allergy and Critical Care Medicine, Department of

Medicine, Emory University, Atlanta, Georgia, United States of America ; College

of Pharmacy, Korea University, Sejong City, Korea.

The concept of multiFRACTALity is currently used to describe self-similar and

complex scaling properties observed in numerous biological signals. FRACTALs are

geometric objects or dynamic variations which exhibit some degree of similarity

(irregularity) to the original object in a wide range of scales. This approach

determines irregularity of biologic signal as an indicator of adaptability, the

capability to respond to unpredictable stress, and health. In the present work,

we propose the application of multiFRACTAL analysis of wavelet-transformed proton

nuclear magnetic resonance ((1)H NMR) spectra of plasma to determine nutritional

insufficiency. For validation of this method on (1)H NMR signal of human plasma,

standard deviation from classical statistical approach and Hurst exponent (H),

left slope and partition function from multiFRACTAL analysis were extracted from

(1)H NMR spectra to test whether multiFRACTAL indices could discriminate healthy

subjects from unhealthy, intensive care unit patients. After validation, the

multiFRACTAL approach was applied to spectra of plasma from a modified crossover

study of sulfur amino acid insufficiency and tested for associations with blood

lipids. The results showed that standard deviation and H, but not left slope,

were significantly different for sulfur amino acid sufficiency and insufficiency.

Quadratic discriminant analysis of H, left slope and the partition function

showed 78% overall classification accuracy according to sulfur amino acid status.

Triglycerides and apolipoprotein C3 were significantly correlated with a

multiFRACTAL model containing H, left slope, and standard deviation, and

cholesterol and high-sensitivity C-reactive protein were significantly correlated

to H. In conclusion, multiFRACTAL analysis of (1)H NMR spectra provides a new

approach to characterize nutritional status.

PMCID: PMC3749179

PMID: 23990878 [PubMed - indexed for MEDLINE]

24. Carbohydr Polym. 2013 Sep 12;97(2):269-76. doi: 10.1016/j.carbpol.2013.04.099.

Epub 2013 May 9.

Fracture behavior of a commercial starch/polycaprolactone blend reinforced with

different layered silicates.

Pérez E(1), Pérez CJ, Alvarez VA, Bernal C.

Author information:

(1)INTECIN (UBA-CONICET), Engineering Faculty, University of Buenos Aires, Av. Las

Heras 2214, C1127AAR Buenos Aires, Argentina.

In the present work, composites based on a commercial starch/PCL blend

(MaterBi-Z) reinforced with three different nanoclays: natural montmorillonite

(Cloisite Na(+) (MMT)) and two modified montmorillonites (Cloisite 30B (C30B) and

Cloisite 10A (C10A)) were prepared in an intensive mixer. The aim of this

investigation was to determine the effect of the different nanoclays on the

quasi-static fracture behavior of MaterBi-Z nanocomposites. An improvement in the

fracture behavior for the composite with low contents of C30B was obtained,

probably due to the easy debonding of clay achieved from a relatively weak

filler-matrix interaction. On the other hand, a strong interaction had a

detrimental effect on the material fracture toughness for the MaterBi-Z/C10A

composites as a result of the higher compatibility of this organo-modified clay

with the hydrophobic matrix. Intermediate values of fracture toughness,

determined using the J-integral approach (Jc), were found for the composites with

MMT due to its intermediate interaction with the matrix. The different

filler-matrix interactions observed were also confirmed from the application of

Pukánszky and Maurer model. In addition, multiFRACTAL analysis was applied to

describe the topography of fracture surfaces. Thus, the complex fracture process

could be successfully described by both experimental and theoretical tools. The

obtained results suggest that it is possible to tailor the mechanical properties

of the studied composites taking into account their further application.

Copyright © 2013 Elsevier Ltd. All rights reserved.

PMID: 23911445 [PubMed - indexed for MEDLINE]

25. PLoS One. 2013 Jul 3;8(7):e68360. doi: 10.1371/journal.pone.0068360. Print 2013.

MultiFRACTAL detrended fluctuation analysis of human EEG: preliminary

investigation and comparison with the wavelet transform modulus maxima technique.

Zorick T(1), Mandelkern MA.

Author information:

(1)Department of Psychiatry, Greater Los Angeles Veterans Administration Healthcare

System, Los Angeles, California, United States of America.

Recently, many lines of investigation in neuroscience and statistical physics

have converged to raise the hypothesis that the underlying pattern of neuronal

activation which results in electroencephalography (EEG) signals is nonlinear,

with self-affine dynamics, while scalp-recorded EEG signals themselves are

nonstationary. Therefore, traditional methods of EEG analysis may miss many

properties inherent in such signals. Similarly, FRACTAL analysis of EEG signals

has shown scaling behaviors that may not be consistent with pure monoFRACTAL

processes. In this study, we hypothesized that scalp-recorded human EEG signals

may be better modeled as an underlying multiFRACTAL process. We utilized the

Physionet online database, a publicly available database of human EEG signals as

a standardized reference database for this study. Herein, we report the use of

multiFRACTAL detrended fluctuation analysis on human EEG signals derived from

waking and different sleep stages, and show evidence that supports the use of

multiFRACTAL methods. Next, we compare multiFRACTAL detrended fluctuation

analysis to a previously published multiFRACTAL technique, wavelet transform

modulus maxima, using EEG signals from waking and sleep, and demonstrate that

multiFRACTAL detrended fluctuation analysis has lower indices of variability.

Finally, we report a preliminary investigation into the use of multiFRACTAL

detrended fluctuation analysis as a pattern classification technique on human EEG

signals from waking and different sleep stages, and demonstrate its potential

utility for automatic classification of different states of consciousness.

Therefore, multiFRACTAL detrended fluctuation analysis may be a useful pattern

classification technique to distinguish among different states of brain function.

PMCID: PMC3700954

PMID: 23844189 [PubMed - indexed for MEDLINE]

26. IEEE Trans Biomed Eng. 2013 Nov;60(11):3204-15. doi: 10.1109/TBME.2013.2271383.

Epub 2013 Jun 27.

MultiFRACTAL texture estimation for detection and segmentation of brain tumors.

Islam A, Reza SM, Iftekharuddin KM.

A stochastic model for characterizing tumor texture in brain magnetic resonance

(MR) images is proposed. The efficacy of the model is demonstrated in

patient-independent brain tumor texture feature extraction and tumor segmentation

in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain

tumor texture is formulated using a multiresolution-FRACTAL model known as

multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm

model and corresponding novel algorithm to extract spatially varying multiFRACTAL

features are proposed. A multiFRACTAL feature-based brain tumor segmentation

method is developed next. To evaluate efficacy, tumor segmentation performance

using proposed multiFRACTAL feature is compared with that using Gabor-like

multiscale texton feature. Furthermore, novel patient-independent tumor

segmentation scheme is proposed by extending the well-known AdaBoost algorithm.

The modification of AdaBoost algorithm involves assigning weights to component

classifiers based on their ability to classify difficult samples and confidence

in such classification. Experimental results for 14 patients with over 300 MRIs

show the efficacy of the proposed technique in automatic segmentation of tumors

in brain MRIs. Finally, comparison with other state-of-the art brain tumor

segmentation works with publicly available low-grade glioma BRATS2012 dataset

show that our segmentation results are more consistent and on the average

outperforms these methods for the patients where ground truth is made available.

PMID: 23807424 [PubMed - indexed for MEDLINE]

27. Microvasc Res. 2013 Sep;89:172-5. doi: 10.1016/j.mvr.2013.06.008. Epub 2013 Jun


Automated segmentation and FRACTAL analysis of high-resolution non-invasive

capillary perfusion maps of the human retina.

Jiang H(1), Debuc DC, Rundek T, Lam BL, Wright CB, Shen M, Tao A, Wang J.

Author information:

(1)Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA; Departemnt of

Neurology, University of Miami, Miami, 33136, USA.

The retina provides a window to study the pathophysiology of cerebrovascular

diseases. Pathological retinal microvascular changes may reflect microangiopathic

processes in the brain. Recent advances in optical imaging techniques have

enabled the imaging of the retinal microvasculature at the capillary level, and

the generation of high-resolution, non-invasive capillary perfusion maps (nCPMs)

with the Retinal Function Imager (RFI). However, the lack of quantitative

analyses of the nCPMs may limit the wider application of the method in clinical

research. The goal of this project was to demonstrate the feasibility of

automated segmentation and FRACTAL analysis of nCPMs. We took two nCPMs of each

subject in a group of 6 healthy volunteers and used our segmentation algorithm to

do the automated segmentation for monoFRACTAL and multiFRACTAL analyses. The

monoFRACTAL dimension was 1.885±0.020, and the multiFRACTAL dimension was

1.876±0.010 (P=0.108). The coefficient of repeatability was 0.070 for monoFRACTAL

analysis and 0.026 for multiFRACTAL analysis. This study demonstrated that the

automatic segmentation of nCPMs is feasible for FRACTAL analyses. Both

monoFRACTAL and multiFRACTAL analyses yielded similar results. The quantitative

analyses of microvasculature at the capillary level may open up a new era for

studying microvascular diseases such as cerebral small vessel disease.

Copyright © 2013 Elsevier Inc. All rights reserved.

PMCID: PMC3773708

PMID: 23806780 [PubMed - indexed for MEDLINE]

28. Comput Math Methods Med. 2013;2013:376152. doi: 10.1155/2013/376152. Epub 2013

May 20.

Classification of prolapsed mitral valve versus healthy heart from

phonocardiograms by multiFRACTAL analysis.

Gavrovska A(1), Zajić G, Reljin I, Reljin B.

Author information:

(1)Research and Development Department, Innovation Center of the School of

Electrical Engineering in Belgrade, Bulevar Kralja Aleksandra 73, 11120 Belgrade,


Phonocardiography has shown a great potential for developing low-cost

computer-aided diagnosis systems for cardiovascular monitoring. So far, most of

the work reported regarding cardiosignal analysis using multiFRACTALs is oriented

towards heartbeat dynamics. This paper represents a step towards automatic

detection of one of the most common pathological syndromes, so-called mitral

valve prolapse (MVP), using phonocardiograms and multiFRACTAL analysis. Subtle

features characteristic for MVP in phonocardiograms may be difficult to detect.

The approach for revealing such features should be locally based rather than

globally based. Nevertheless, if their appearances are specific and frequent,

they can affect a multiFRACTAL spectrum. This has been the case in our experiment

with the click syndrome. Totally, 117 pediatric phonocardiographic recordings

(PCGs), 8 seconds long each, obtained from 117 patients were used for PMV

automatic detection. We propose a two-step algorithm to distinguish PCGs that

belong to children with healthy hearts and children with prolapsed mitral valves

(PMVs). Obtained results show high accuracy of the method. We achieved 96.91%

accuracy on the dataset (97 recordings). Additionally, 90% accuracy is achieved

for the evaluation dataset (20 recordings). Content of the datasets is confirmed

by the echocardiographic screening.

PMCID: PMC3671509

PMID: 23762185 [PubMed - indexed for MEDLINE]

29. Front Comput Neurosci. 2013 Jun 4;7:72. doi: 10.3389/fncom.2013.00072.

eCollection 2013.

The relevance of network micro-structure for neural dynamics.

Pernice V(1), Deger M, Cardanobile S, Rotter S.

Author information:

(1)Bernstein Center Freiburg and Faculty of Biology, Albert-Ludwig University

Freiburg, Germany.

The activity of cortical neurons is determined by the input they receive from

presynaptic neurons. Many previous studies have investigated how specific aspects

of the statistics of the input affect the spike trains of single neurons and

neurons in recurrent networks. However, typically very simple random network

models are considered in such studies. Here we use a recently developed algorithm

to construct networks based on a quasi-FRACTAL probability measure which are much

more variable than commonly used network models, and which therefore promise to

sample the space of recurrent networks in a more exhaustive fashion than

previously possible. We use the generated graphs as the underlying network

topology in simulations of networks of integrate-and-fire neurons in an

asynchronous and irregular state. Based on an extensive dataset of networks and

neuronal simulations we assess statistical relations between features of the

network structure and the spiking activity. Our results highlight the strong

influence that some details of the network structure have on the activity

dynamics of both single neurons and populations, even if some global network

parameters are kept fixed. We observe specific and consistent relations between

activity characteristics like spike-train irregularity or correlations and

network properties, for example the distributions of the numbers of in- and

outgoing connections or clustering. Exploiting these relations, we demonstrate

that it is possible to estimate structural characteristics of the network from

activity data. We also assess higher order correlations of spiking activity in

the various networks considered here, and find that their occurrence strongly

depends on the network structure. These results provide directions for further

theoretical studies on recurrent networks, as well as new ways to interpret spike

train recordings from neural circuits.

PMCID: PMC3671286

PMID: 23761758 [PubMed]

30. Bull Math Biol. 2013 Sep;75(9):1544-70. doi: 10.1007/s11538-013-9859-9. Epub 2013

Jun 13.

On the FRACTAL geometry of DNA by the binary image analysis.

Cattani C(1), Pierro G.

Author information:

(1)Department of Mathematics, University of Salerno, Via Ponte Don Melillo, 84084,

Fisciano (SA), Italy.

The multiFRACTAL analysis of binary images of DNA is studied in order to define a

methodological approach to the classification of DNA sequences. This method is

based on the computation of some multiFRACTALity parameters on a suitable binary

image of DNA, which takes into account the nucleotide distribution. The binary

image of DNA is obtained by a dot-plot (recurrence plot) of the indicator matrix.

The FRACTAL geometry of these images is characterized by FRACTAL dimension (FD),

lacunarity, and succolarity. These parameters are compared with some other

coefficients such as complexity and Shannon information entropy. It will be shown

that the complexity parameters are more or less equivalent to FD, while the

parameters of multiFRACTALity have different values in the sense that sequences

with higher FD might have lower lacunarity and/or succolarity. In particular, the

genome of Drosophila melanogaster has been considered by focusing on the

chromosome 3r, which shows the highest FRACTALity with a corresponding higher

level of complexity. We will single out some results on the nucleotide

distribution in 3r with respect to complexity and FRACTALity. In particular, we

will show that sequences with higher FD also have a higher frequency distribution

of guanine, while low FD is characterized by the higher presence of adenine.

PMID: 23760660 [PubMed - indexed for MEDLINE]

31. J Periodontal Res. 2014 Apr;49(2):186-96. doi: 10.1111/jre.12093. Epub 2013 May


Evaluation of scaling and root planing effect in generalized chronic

periodontitis by FRACTAL and multiFRACTAL analysis.

Pârvu AE(1), Ţălu Ş, Crăciun C, Alb SF.

Author information:

(1)Department of Pathophysiology, Faculty of Medicine, "Iuliu Haţieganu" University

of Medicine and Pharmacy, Cluj-Napoca, Romania.

BACKGROUND AND OBJECTIVE: FRACTAL and multiFRACTAL analysis are useful additional

non-invasive methods for quantitative description of complex morphological

features. However, the quantitative and qualitative assessment of morphologic

changes within human gingival cells and tissues are still unexplored. The aim of

this work is to assess the structural gingival changes in patients with

generalized chronic periodontitis (GCP), before and after scaling and root

planing (SRP) by using FRACTAL and multiFRACTAL analysis.

MATERIAL AND METHODS: Twelve adults with untreated chronic periodontitis were

treated only by SRP. At baseline and after SRP, gingivomucosal biopsies were

collected for histopathological examination. FRACTAL and multiFRACTAL analysis of

digital images of the granular, spinous and basal and conjunctive layers

structure, using the standard box-counting method was performed. The FRACTAL

dimension was determined for cell membrane, nuclear membrane of cell and

nucleolus membrane of cell.

RESULTS: In GCP a higher FRACTAL dimension corresponds to a higher geometric

complexity of cells contour, as its values increase when the contour

irregularities increase. The generalized FRACTAL dimensions were determined for

the conjunctive layer structure of patients with GCP and patients with GCP and

SRP. The FRACTAL and multiFRACTAL analysis of gingival biopsies confirmed earlier

findings that SRP reduces gingival injury in patients with GCP.

CONCLUSION: It has been shown that FRACTAL and multiFRACTAL analysis of tissue

images as a non-invasive technique could be used to measure contrasting

morphologic changes within human gingival cells and tissues and can provide

detailed information for investigation of healthy and diseased gingival mucosa

from patients with GCP.

© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

PMID: 23668776 [PubMed - in process]

32. Chaos. 2013 Mar;23(1):013133. doi: 10.1063/1.4793781.

MultiFRACTAL analysis of validated wind speed time series.

García-Marín AP(1), Estévez J, Jiménez-Hornero FJ, Ayuso-Muñoz JL.

Author information:

(1)Department of Rural Engineering, University of Cordoba, P.O. Box 3048, 14080

Córdoba, Spain.

MultiFRACTAL properties of 30 min wind data series recorded at six locations in

Cadiz (Southern Spain) have been studied in this work with the aim of obtaining

detailed information for a range of time scales. Wind speed records have been

validated, applying various quality control tests as a pre-requisite before their

use, improving the reliability of the results due to the identification of

incorrect values which have been discarded in the analysis. The scaling of the

wind speed moments has been analysed and empirical moments scaling exponent

functions K(q) have been obtained. Although the same critical moment (qcrit) has

been obtained for all the places, some differences appear in other multiFRACTAL

parameters like γmax and the value of K(0). These differences have been related

to the presence of extreme events and zero data values in the data series

analysed, respectively.

PMID: 23556970 [PubMed - indexed for MEDLINE]

33. Chaos. 2013 Mar;23(1):013129. doi: 10.1063/1.4793355.

Cross-correlation detection and analysis for California's electricity market

based on analogous multiFRACTAL analysis.

Wang F(1), Liao GP, Li JH, Zou RB, Shi W.

Author information:

(1)Science College, Hunan Agricultural University, Changsha 410128, China.

A novel method, which we called the analogous multiFRACTAL cross-correlation

analysis, is proposed in this paper to study the multiFRACTAL behavior in the

power-law cross-correlation between price and load in California electricity

market. In addition, a statistic ρAMF-XA, which we call the analogous

multiFRACTAL cross-correlation coefficient, is defined to test whether the

cross-correlation between two given signals is genuine or not. Our analysis finds

that both the price and load time series in California electricity market express

multiFRACTAL nature. While, as indicated by the ρAMF-XA statistical test, there

is a huge difference in the cross-correlation behavior between the years 1999 and

2000 in California electricity markets.

PMID: 23556966 [PubMed - indexed for MEDLINE]

34. Curr Eye Res. 2013 Jul;38(7):781-92. doi: 10.3109/02713683.2013.779722. Epub 2013

Mar 28.

MultiFRACTAL geometry in analysis and processing of digital retinal photographs

for early diagnosis of human diabetic macular edema.

Tălu S.

Author information:

Department of AET, Discipline of Descriptive Geometry and Engineering Graphics,

Faculty of Mechanics, The Technical University of Cluj-Napoca, Cluj-Napoca,


OBJECTIVE: The purpose of this paper is to determine a quantitative assessment of

the human retinal vascular network architecture for patients with diabetic

macular edema (DME). MultiFRACTAL geometry and lacunarity parameters are used in

this study.

MATERIALS AND METHODS: A set of 10 segmented and skeletonized human retinal

images, corresponding to both normal (five images) and DME states of the retina

(five images), from the DRIVE database was analyzed using the Image J software.

Statistical analyses were performed using Microsoft Office Excel 2003 and

GraphPad InStat software.

RESULTS: The human retinal vascular network architecture has a multiFRACTAL

geometry. The average of generalized dimensions (Dq) for q = 0, 1, 2 of the

normal images (segmented versions), is similar to the DME cases (segmented

versions). The average of generalized dimensions (Dq) for q = 0, 1 of the normal

images (skeletonized versions), is slightly greater than the DME cases

(skeletonized versions). However, the average of D2 for the normal images

(skeletonized versions) is similar to the DME images. The average of lacunarity

parameter, Λ, for the normal images (segmented and skeletonized versions) is

slightly lower than the corresponding values for DME images (segmented and

skeletonized versions).

CONCLUSION: The multiFRACTAL and lacunarity analysis provides a non-invasive

predictive complementary tool for an early diagnosis of patients with DME.

PMID: 23537336 [PubMed - indexed for MEDLINE]

35. Behav Res Methods. 2013 Dec;45(4):928-45. doi: 10.3758/s13428-013-0317-2.

MultiFRACTAL analyses of response time series: a comparative study.

Ihlen EA.

Author information:

Department of Neuroscience, Norwegian University of Science and Technology, 7489,

Trondheim, Norway,

Response time series with a non-Gaussian distribution and long-range dependent

dynamics have been reported for several cognitive tasks. Conventional monoFRACTAL

analyses numerically define a long-range dependency as a single scaling exponent,

but they assume that the response times are Gaussian distributed. Ihlen and

Vereijken (Journal of Experimental Psychology: General, 139, 436-463, 2010)

suggested multiFRACTAL extensions of the conventional monoFRACTAL analyses that

are more suitable when the response time has a non-Gaussian distribution.

MultiFRACTAL analyses estimate a multiFRACTAL spectrum of scaling exponents that

contain the single exponent estimated by the conventional monoFRACTAL analyses.

However, a comparison of the performance of multiFRACTAL analyses with behavioral

variables has not yet been addressed. The present study compares the performance

of seven multiFRACTAL analyses. The multiFRACTAL analyses were tested on

multiplicative cascading noise that generates time series with a predefined

multiFRACTAL spectrum and with a structure of variation that mimics intermittent

response time variation. Time series with 1,024 and 4,096 samples were generated

with additive noise and multiharmonic trends of two different magnitudes

(signal-to-noise/trend ratio; 0.33 and 1). The results indicate that all

multiFRACTAL analysis has individual pros and cons related to sample size,

multiFRACTALity, and the presence of additive noise and trends in the response

time series. The summary of pros and cons of the seven multiFRACTAL analyses

provides a guideline for the choice of multiFRACTAL analyses of response time

series and other behavioral variables.

PMID: 23526256 [PubMed - indexed for MEDLINE]

36. Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Feb;87(2):022918. Epub 2013 Feb 28.

Performance of multiFRACTAL detrended fluctuation analysis on short time series.

López JL(1), Contreras JG.

Author information:

(1)Departamento de Física Aplicada, Centro de Investigación y de Estudios Avanzados

del Instituto Politécnico Nacional, Unidad Mérida, A.P. 73 Cordemex, 97310

Mérida, Yucatán, México.

The performance of the multiFRACTAL detrended analysis on short time series is

evaluated for synthetic samples of several mono- and multiFRACTAL models. The

reconstruction of the generalized Hurst exponents is used to determine the range

of applicability of the method and the precision of its results as a function of

the decreasing length of the series. As an application the series of the daily

exchange rate between the U.S. dollar and the euro is studied.

PMID: 23496602 [PubMed - indexed for MEDLINE]

37. Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Feb;87(2):022821. Epub 2013 Feb 28.

Wavelet-based multiFRACTAL analysis of nonlinear time series: the

earthquake-driven tsunami of 27 February 2010 in Chile.

Toledo BA(1), Chian AC, Rempel EL, Miranda RA, Muñoz PR, Valdivia JA.

Author information:

(1)Institute of Aeronautical Technology (ITA) and World Institute for Space

Environment Research (WISER), CTA/ITA/IEFM, São José dos Campos-SP 12228-900,


We study general multiFRACTAL properties of tidal gauge and long-wave time series

which show a well defined transition between two states, as is the case of sea

level when a tsunami arrives. We adopt a method based on discrete wavelets,

called wavelet leaders, which has been successfully used in a wide range of

applications from image analysis to biomedical signals. First, we analyze an

empirical time series of tidal gauge from the tsunami event of 27 February 2010

in Chile. Then, we study a numerical solution of the driven-damped regularized

long-wave equation (RLWE) which displays on-off intermittency. Both time series

are characterized by a sudden change between two sharply distinct dynamical

states. Our analysis suggests a correspondence between the pre- and post-tsunami

states (ocean background) and the on state in the RLWE, and also between the

tsunami state (disturbed ocean) and the off state in the RLWE. A qualitative

similarity in their singularity spectra is observed, and since the RLWE is used

to model shallow water dynamics, this result could imply an underlying dynamical


PMID: 23496582 [PubMed - indexed for MEDLINE]

38. Opt Lett. 2013 Jan 15;38(2):211-3. doi: 10.1364/OL.38.000211.

Probing multiFRACTALity in tissue refractive index: prospects for precancer


Das N(1), Chatterjee S, Soni J, Jagtap J, Pradhan A, Sengupta TK, Panigrahi PK,

Vitkin IA, Ghosh N.

Author information:

(1)IISER-Kolkata, BCKV Main Campus, Mohanpur, Nadia, West Bengal, India.

Multiresolution analysis on the spatial refractive index inhomogeneities in the

epithelium and connective tissue regions of a human cervix reveals a clear

signature of multiFRACTALity. Importantly, the derived multiFRACTAL parameters,

namely, the generalized Hurst exponent and the width of the singularity spectrum,

derived via multiFRACTAL detrended fluctuation analysis, shows interesting

differences between tissues having different grades of precancers. The

refractive-index fluctuations are found to be more anticorrelated, and the

strength of multiFRACTALity is observed to be considerably stronger in the higher

grades of precancers. These observations on the multiFRACTAL nature of tissue

refractive-index variations may prove to be valuable for developing

light-scattering approaches for noninvasive diagnosis of precancer and

early-stage cancer.

PMID: 23454965 [PubMed - indexed for MEDLINE]

39. Oftalmologia. 2012;56(2):63-71.

[MultiFRACTAL characterisation of human retinal blood vessels].

[Article in Romanian]

Tălu S.

Author information:

Facultatea de Mecanică, Disciplina De Geometrie Descriptivă şi Grafică

Inginerească, Universitatea Tehnică Din Cluj-Napoca. STEFAN_TA@YAHOO.COM

PURPOSE: The objective of this study is to describe the microvascular network of

the normal human retina the d using multiFRACTAL geometry.

MATERIALS AND METHOD: The multiFRACTAL analysis of five digitized retinal images

was made with the Image J software, exprf applying the standard box-counting


RESULTS: The human retinal microvascular network has a multiFRACTAL geometry. The

generalized FRACTAL dimensions Dq were expressed by the mean value and standard

deviation. A comparison with the data from studies performed in the

ophthalmologic literature was made.

CONCLUSIONS: MultiFRACTAL characterization of human retinal microvascular

network, as a non-invasive technique for the analysis of various aspects of

retinal vascular topography can be used as a potential marker for early detection

of patients with retinal diseases.

PMID: 23424766 [PubMed - indexed for MEDLINE]

40. Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Jan;87(1):012921. Epub 2013 Jan 31.

Relationships of exponents in two-dimensional multiFRACTAL detrended fluctuation


Zhou Y(1), Leung Y, Yu ZG.

Author information:

(1)Department of Geography and Resource Management, The Chinese University of Hong

Kong, Hong Kong, China.

MultiFRACTAL detrended fluctuation analysis (MF-DFA) is a generalization of the

conventional multiFRACTAL analysis. It is extended from the detrended fluctuation

analysis (DFA) which is developed for the purpose of detecting long-range

correlation and FRACTAL property in stationary and nonstationary time series. The

MF-DFA and some corresponding relationships of the exponents have been

subsequently extended to the two-dimensional space. We reexamine two extended

relationships in this study and demonstrate that: (i) The invalidity of the

relationship h(q)≡H for two-dimensional fractional Brownian motion, and h(q=2)≡H

between the Hurst exponent H and the generalized Hurst exponent h(q) in the

two-dimensional case. Two more logical relationships are proposed instead as

h(q=2)=H for the stationary surface and h(q=2)=H+2 for the nonstationary signal.

(ii) The invalidity of the expression τ(q)=qh(q)-D(f) stipulating the

relationship between the standard partition-function-based multiFRACTAL exponent

τ(q) and the generalized Hurst exponent h(q) in the two-dimensional case. Reasons

for its invalidity are given from two perspectives.

PMID: 23410418 [PubMed - indexed for MEDLINE]

41. Med Phys. 2013 Feb;40(2):020702. doi: 10.1118/1.4774362.

MultiFRACTAL analysis of laser Doppler flowmetry signals before and after

arm-cranking exercise in an older healthy population.

Klonizakis M(1), Humeau-Heurtier A.

Author information:

(1)School of Postgraduate Medicine, University of Hertfordshire, Hatfield, UK.

PURPOSE: There is a lot of speculation about the role of nitric-oxide (NO) in the

improvement usually noticed in microcirculatory function, following exercise. The

knowledge of the underlying mechanisms leading to such an improvement is

important as it may help in targeting and implementing therapies for

microcirculatory diseases. Through a laser Doppler flowmetry (LDF) signal

processing study, the authors' goal is to compare multiFRACTAL spectra of LDF

data recorded in both lower leg and forearm, during different exercise

conditions, in an older, untrained but healthy population.

METHODS: Using the method suggested by Halsey et al. [Phys. Rev. A 33, 1141-1151

(1986)], multiFRACTAL spectra of LDF signals recorded on lower leg and forearm

before and after exercise (arm-cranking), before and after acetylcholine (ACh)

iontophoresis, were determined on scales in relation with the NO-dependent

endothelial activity. The width of each multiFRACTAL spectrum was then computed

through the maximum and minimum Hölder exponent values for which the

multiFRACTAL spectrum reaches its minimal values. The results were then compared.

RESULTS: Following exercise and on the scales studied, the average width of the

multiFRACTAL spectra in both lower leg and forearm does not vary significantly

before and after ACh iontophoresis. Similarly, following ACh iontophoresis and

exercise, the average width of multiFRACTAL spectra remains statistically

unchanged, when compared to that measured prior to exercise, in both upper and

lower body, although negative trends can be observed.

CONCLUSIONS: For the authors' population and for the type of exercise that the

authors have chosen, the authors showed that the width of the multiFRACTAL

spectra of LDF signals does not change significantly on scales in relation with

the NO-dependent endothelial activity. Future studies may involve comparisons

with signals obtained in patient populations.

PMID: 23387723 [PubMed - indexed for MEDLINE]

42. Front Cell Neurosci. 2013 Jan 30;7:3. doi: 10.3389/fncel.2013.00003. eCollection


Quantitating the subtleties of microglial morphology with FRACTAL analysis.

Karperien A(1), Ahammer H, Jelinek HF.

Author information:

(1)Centre for Research in Complex Systems, School of Community Health, Charles Sturt

University Albury, NSW, Australia.

It is well established that microglial form and function are inextricably linked.

In recent years, the traditional view that microglial form ranges between

"ramified resting" and "activated amoeboid" has been emphasized through advancing

imaging techniques that point to microglial form being highly dynamic even within

the currently accepted morphological categories. Moreover, microglia adopt

meaningful intermediate forms between categories, with considerable crossover in

function and varying morphologies as they cycle, migrate, wave, phagocytose, and

extend and retract fine and gross processes. From a quantitative perspective, it

is problematic to measure such variability using traditional methods, but one way

of quantitating such detail is through FRACTAL analysis. The techniques of

FRACTAL analysis have been used for quantitating microglial morphology, to

categorize gross differences but also to differentiate subtle differences (e.g.,

amongst ramified cells). MultiFRACTAL analysis in particular is one technique of

FRACTAL analysis that may be useful for identifying intermediate forms. Here we

review current trends and methods of FRACTAL analysis, focusing on box counting

analysis, including lacunarity and multiFRACTAL analysis, as applied to

microglial morphology.

PMCID: PMC3558688

PMID: 23386810 [PubMed]

43. IEEE Trans Neural Syst Rehabil Eng. 2013 Mar;21(2):225-32. doi:

10.1109/TNSRE.2012.2236576. Epub 2013 Jan 9.

Real-time mental arithmetic task recognition from EEG signals.

Wang Q(1), Sourina O.

Author information:

(1)School of Electrical and Electronic Engineering, and Institute for Media

Innovation, Nanyang Technological University, 639798, Singapore.

Electroencephalography (EEG)-based monitoring the state of the user's brain

functioning and giving her/him the visual/audio/tactile feedback is called

neurofeedback technique, and it could allow the user to train the corresponding

brain functions. It could provide an alternative way of treatment for some

psychological disorders such as attention deficit hyperactivity disorder (ADHD),

where concentration function deficit exists, autism spectrum disorder (ASD), or

dyscalculia where the difficulty in learning and comprehending the arithmetic

exists. In this paper, a novel method for multiFRACTAL analysis of EEG signals

named generalized Higuchi FRACTAL dimension spectrum (GHFDS) was proposed and

applied in mental arithmetic task recognition from EEG signals. Other features

such as power spectrum density (PSD), autoregressive model (AR), and statistical

features were analyzed as well. The usage of the proposed FRACTAL dimension

spectrum of EEG signal in combination with other features improved the mental

arithmetic task recognition accuracy in both multi-channel and one-channel

subject-dependent algorithms up to 97.87% and 84.15% correspondingly. Based on

the channel ranking, four channels were chosen which gave the accuracy up to

97.11%. Reliable real-time neurofeedback system could be implemented based on the

algorithms proposed in this paper.

PMID: 23314778 [PubMed - indexed for MEDLINE]

44. J Theor Biol. 2013 Mar 21;321:54-62. doi: 10.1016/j.jtbi.2012.12.027. Epub 2013

Jan 10.

Investigation on series of length of coding and non-coding DNA sequences of

bacteria using multiFRACTAL detrended cross-correlation analysis.

Stan C(1), Cristescu MT, Luiza BI, Cristescu CP.

Author information:

(1)Department of Physics, Faculty of Applied Sciences, Politehnica University of

Bucharest, Bucharest, Romania.

In the framework of multiFRACTAL detrended cross-correlation analysis, we

investigate characteristics of series of length of coding and non-coding DNA

sequences of some bacteria and archaea. We propose the use of a multiFRACTAL

cross-correlation series that can be defined for any pair of equal lengths data

sequences (or time series) and that can be characterized by the full set of

parameters that are attributed to any time series. Comparison between

characteristics of series of length of coding and non-coding DNA sequences and of

their associated multiFRACTAL cross-correlation series for selected groups is

used for the identification of class affiliation of certain bacteria and archaea.

The analysis is carried out using the dependence of the generalized Hurst

exponent on the size of fluctuations, the shape of the singularity spectra, the

shape and relative disposition of the curves of the singular measures scaling

exponent and the values of the associated parameters. Empirically, we demonstrate

that the series of lengths of coding and non-coding sequences as well as the

associated multiFRACTAL cross-correlation series can be approximated as universal


Copyright © 2013 Elsevier Ltd. All rights reserved.

PMID: 23313335 [PubMed - indexed for MEDLINE]

45. Ann Biomed Eng. 2013 Aug;41(8):1635-45. doi: 10.1007/s10439-012-0724-z. Epub 2012

Dec 18.

Identifying multiplicative interactions between temporal scales of human movement


Ihlen EA(1), Vereijken B.

Author information:

(1)Department of Neuroscience, Norwegian University of Science and Technology,

Trondheim, Norway.

Conventional scaling analyses of human movement variability such as detrended

fluctuation analyses assume that the movement variable can be decomposed into

scale-dependent variation. However, these conventional scaling analyses are

insensitive to multiplicative interactions within the movement variable.

Multiplicative interactions refer to couplings between the scale-dependent

variations across multiple scales that generate intermittent changes in the human

movement variable. The mathematical concept for intermittent variability

generated by multiplicative interactions is called multiFRACTAL variability.

MultiFRACTAL variability is numerically defined by a spectrum of scaling

exponents (i.e., a multiFRACTAL spectrum) that can be an important feature of

coordinated movements and, consequently, relevant when aiming to identify

movement disorders. In the current study, a new method is introduced based on

detrended fluctuation analysis that can identify the multiFRACTAL spectrum from

the temporal variation of local scaling exponents. The influence of

multiplicative interactions on the local scaling exponents is tested by a Monte

Carlo surrogate test. The methods are validated on multiplicative cascading

processes with known multiplicative interactions. The application of the new

methods is subsequently illustrated on an example of centre of pressure

variations during quiet and relaxed standing. The results show that

multiplicative interactions are present during periods with large movements of

the center of gravity, where the movements of the centre of gravity and centre of

pressure couple into coordinative structures. Further application and

interpretation of the developed method for the study of human movement

variability are discussed.

PMID: 23247986 [PubMed - indexed for MEDLINE]

46. Meat Sci. 2013 Mar;93(3):723-32. doi: 10.1016/j.meatsci.2012.11.015. Epub 2012

Nov 16.

MultiFRACTAL analysis application to the characterization of fatty infiltration

in Iberian and White pork sirloins.

Serrano S(1), Perán F, Jiménez-Hornero FJ, Gutiérrez de Ravé E.

Author information:

(1)Department of Food Hygiene and Technology, University of Cordoba, Campus

Rabanales, Edif. Darwin, anexo, Cordoba 14071, Spain.

This paper applies the multiFRACTAL analysis based on the sandbox method to

describe the distribution of fatty infiltration in Iberian and White pork meat

with the aim of characterization and classification. This work was carried out by

making photographs of sirloin cuts of both breeds and then treated with image

analysis software. The obtained image data were stored in text format and

constituted the input for multiFRACTAL analysis. The results obtained show that

pork sirloin connective fatty tissue exhibits a multiFRACTAL type of scaling.

Significant correlations were found between some of the parameters governing the

multiFRACTAL behavior and fat percentage, especially in the case of Iberian

sirloin. The differences found for the relationships between the generalized

FRACTAL dimensions and fat percentage provide information for the categorization

of the studied meat pieces.

Copyright © 2012 Elsevier Ltd. All rights reserved.

PMID: 23247059 [PubMed - indexed for MEDLINE]

47. Front Physiol. 2012 Nov 15;3:417. doi: 10.3389/fphys.2012.00417. eCollection


Pitfalls in FRACTAL Time Series Analysis: fMRI BOLD as an Exemplary Case.

Eke A(1), Herman P, Sanganahalli BG, Hyder F, Mukli P, Nagy Z.

Author information:

(1)Institute of Human Physiology and Clinical Experimental Research, Semmelweis

University Budapest, Hungary ; Diagnostic Radiology, Yale University New Haven,


This article will be positioned on our previous work demonstrating the importance

of adhering to a carefully selected set of criteria when choosing the suitable

method from those available ensuring its adequate performance when applied to

real temporal signals, such as fMRI BOLD, to evaluate one important facet of

their behavior, FRACTALity. Earlier, we have reviewed on a range of monoFRACTAL

tools and evaluated their performance. Given the advance in the FRACTAL field, in

this article we will discuss the most widely used implementations of multiFRACTAL

analyses, too. Our recommended flowchart for the FRACTAL characterization of

spontaneous, low frequency fluctuations in fMRI BOLD will be used as the

framework for this article to make certain that it will provide a hands-on

experience for the reader in handling the perplexed issues of FRACTAL analysis.

The reason why this particular signal modality and its FRACTAL analysis has been

chosen was due to its high impact on today's neuroscience given it had powerfully

emerged as a new way of interpreting the complex functioning of the brain (see

"intrinsic activity"). The reader will first be presented with the basic concepts

of mono and multiFRACTAL time series analyses, followed by some of the most

relevant implementations, characterization by numerical approaches. The notion of

the dichotomy of fractional Gaussian noise and fractional Brownian motion signal

classes and their impact on FRACTAL time series analyses will be thoroughly

discussed as the central theme of our application strategy. Sources of pitfalls

and way how to avoid them will be identified followed by a demonstration on

FRACTAL studies of fMRI BOLD taken from the literature and that of our own in an

attempt to consolidate the best practice in FRACTAL analysis of empirical fMRI

BOLD signals mapped throughout the brain as an exemplary case of potentially wide


PMCID: PMC3513686

PMID: 23227008 [PubMed]

48. Med Eng Phys. 2013 Aug;35(8):1070-8. doi: 10.1016/j.medengphy.2012.11.004. Epub

2012 Nov 30.

Complexity of the autonomic heart rate control in coronary artery occlusion in

patients with and without prior myocardial infarction.

Magrans R(1), Gomis P, Caminal P, Wagner GS.

Author information:

(1)Departament d'Enginyeria de Sistemas, Automàtica i Informàtica Industrial,

Universitat Politècnica de Catalunya, Barcelona, Spain.

Autonomic nervous system (ANS) is governed by complex interactions arising from

feedback loops of nonlinear systems that operate over a wide range of temporal

and spatial scales, enabling the organism to adapt to stress, metabolic changes

and diseases. This study is aimed to assess multiFRACTAL and nonlinear

characteristics of the ANS during ischemic events provoked by a prolonged

percutaneous coronary intervention (PCI) procedure. Eighty-seven patients from

the STAFF III database were used. Patients were classified into 2 groups: (1)

with prior myocardial infarction (MI) and (2) without MI (noMI). R-R signals

during three 3-min stages of the procedures were analyzed using multiFRACTAL and

surrogate data techniques. MultiFRACTAL indices increased significantly from the

pre-inflation stage to the post-deflation stage. These variations were more

marked for the noMI group. MultiFRACTAL changes significantly correlated with

both the decreased parasympathetic and the increased sympathetic modulations

accounted by classical linear indices. MultiFRACTAL measures resulted to be a

more powerful indicator than linear HRV indices in quantifying the

ischemia-induced changes. Right coronary artery (RCA) occlusions provoke greater

multiFRACTAL reactions throughout the PCI procedure. Our findings suggest reduced

complex multiFRACTAL and nonlinear reactions of ANS activity in patients with

prior MI in comparison to the noMI group, possibly due to degradation in the

complexity of control mechanism of heart rate generation.

Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

PMID: 23201277 [PubMed - indexed for MEDLINE]

49. Comput Med Imaging Graph. 2013 Jan;37(1):61-71. doi:

10.1016/j.compmedimag.2012.10.001. Epub 2012 Nov 9.

Computational grading of hepatocellular carcinoma using multiFRACTAL feature


Atupelage C(1), Nagahashi H, Yamaguchi M, Abe T, Hashiguchi A, Sakamoto M.

Author information:

(1)Department of Computational Intelligence and Systems Science, Tokyo Institute of

Technology, Japan.

Cancer grading has become an important topic in the field of image

interpretation-based computer aided diagnosis systems. This paper proposes a

novel feature descriptor to observe the characteristics of histopathological

textures in a discriminative manner. The proposed feature descriptor utilizes

FRACTAL geometric analysis with four multiFRACTAL measures to construct an eight

dimensional feature space. The proposed method employed a bag-of-feature-based

classification model to discriminate a set of hepatocellular carcinoma images

into five categories according to Edmondson and Steiner's grading system. Three

feature selection methods were utilized to obtain the most discriminative

features of codeword dictionary (codebook). Furthermore, we incorporated four

other textural feature descriptors: Gabor-filters, LM-filters, local binary

patterns, and Haralick, to obtain a benchmark of the accuracy of the

classification. Two experiments were performed: (i) classifying non-neoplastic

tissues and tumors and (ii) grading the hepatocellular carcinoma images into five

classes. Experimental results indicated the significance of the multiFRACTAL

features for describing the histopathological image texture because it

outperformed other four feature descriptors. We graded a given ROI image by

defining a threshold-based majority-voting rule and obtained an average correct

classification rate around 95% for five classes classification.

Copyright © 2012 Elsevier Ltd. All rights reserved.

PMID: 23141965 [PubMed - indexed for MEDLINE]

50. Med Biol Eng Comput. 2013 Mar;51(3):277-84. doi: 10.1007/s11517-012-0990-9. Epub

2012 Nov 7.

Classification of surface electromyographic signals by means of multiFRACTAL

singularity spectrum.

Wang G(1), Ren D.

Author information:

(1)Key Laboratory of Biomedical Information Engineering of Ministry of Education,

Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an

Jiaotong University, 28 Xianning West Road, Xi'an, 710049, China.

In order to effectively control a prosthetic system, considerable attempts have

been made in recent years to improve the classification accuracy of surface

electromyographic (SEMG) signals. However, the extraction of effective features

is still a primary challenge for the classification of SEMG signals. This study

tried to solve the problem by applying the multiFRACTAL analysis. It was found

that the SEMG signals were characterized by multiFRACTALity during forearm

movements and different types of forearm movements were related to different

multiFRACTAL singularity spectra. To quantitatively evaluate the multiFRACTAL

singularity spectra of the SEMG signals, the areas of the singularity spectrum

curves were calculated by integrating the spectrum curves with respect to the

singularity strengths. Our results showed that there were several separate

clusters resulting from singularity spectrum areas of different forearm movements

when two channels of SEMG signals were used in this experimental research, which

demonstrated that the multiFRACTAL analysis approach was suitable for identifying

different types of forearm movements. By comparing with other feature extraction

techniques, the multiFRACTAL singularity spectrum approach provided higher

classification accuracy in terms of the classification of SEMG signals.

PMID: 23132526 [PubMed - indexed for MEDLINE]

51. Med Phys. 2012 Oct;39(10):5849-56. doi: 10.1118/1.4748506.

Laser speckle contrast imaging: multiFRACTAL analysis of data recorded in healthy


Humeau-Heurtier A(1), Mahe G, Durand S, Henrion D, Abraham P.

Author information:

(1)Université d'Angers, Laboratoire d'Ingénierie des Systèmes Automatisés,

Angers, France.

PURPOSE: The monitoring of microvascular blood flow can now be performed with

laser speckle contrast imaging (LSCI), a new noninvasive laser-based technique.

LSCI images have good spatial and temporal resolutions. Nevertheless, from now,

few processing of these data have been performed to have a better knowledge on

their properties. We herein propose a multiFRACTAL analysis of LSCI data recorded

in the forearm of healthy subjects, based on the method from Halsey et al., one

of the popular methods using the box-counting technique.

METHODS: In laser speckle contrast image time sequences, we studied time

evolution of pixel values, as well as time evolution of pixel values averaged in

regions of interest (ROI) of different sizes. The results are compared with the

ones obtained with single-point laser Doppler flowmetry (LDF) signals recorded

simultaneously to LSCI images.

RESULTS: Our work shows that, for the range of scales studied and with the method

from Halsey et al., time evolution of pixel values present narrow multiFRACTAL

spectra, reminding the ones of monoFRACTAL data. However, we observe that when

LSCI pixel values are averaged in ROI large enough and followed with time, the

multiFRACTAL spectra become larger and closer to the ones of LDF signals.

CONCLUSIONS: Single pixels from laser speckle contrast images may not possess the

same multiFRACTAL properties as LDF signals. These findings could now be compared

with the ones obtained with other ranges of scales and with data recorded from

pathological subjects.

PMID: 23039623 [PubMed - indexed for MEDLINE]

52. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jul;86(1 Pt 1):011924. Epub 2012

Jul 24.

MultiFRACTAL dynamics of turbulent flows in swimming bacterial suspensions.

Liu KA(1), I L.

Author information:

(1)Department of Physics and Center for Complex Systems, National Central

University, Jhongli, Taiwan 32001, Republic of China.

Erratum in

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Oct;86(4 Pt 2):049905.

We experimentally investigate the self-propelled two-dimensional turbulent flows

of Escherichia coli suspensions in thin liquid films at two different cell

concentrations. It is found that the flow has fluctuating vortices with a broad

range of scales and intensities through the nonlinear interaction of the swimming

bacteria. Increasing cell concentration increases the total propelling power and

the nonlinear interaction. It causes the generation of vortices with larger

scale, lower frequency, and higher intensity. It also widens the histograms of

the flow velocity and the velocity increment between two spatially separated

points with more stretched non-Gaussian tails. From the scaling analysis of the

structure function S(q)(r) of the qth moment of the velocity increment between

two points with spatial separation r, nonlinear relations between the scaling

exponent ζ(q) of S(q)(r) and q are found for both cell concentrations, which

manifests the multiFRACTAL dynamics. The multiFRACTALity can be enhanced by

increasing cell concentration.

PMID: 23005469 [PubMed - indexed for MEDLINE]

53. J Neural Eng. 2012 Oct;9(5):056008. Epub 2012 Aug 28.

Complexity and multiFRACTALity of neuronal noise in mouse and human hippocampal

epileptiform dynamics.

Serletis D(1), Bardakjian BL, Valiante TA, Carlen PL.

Author information:

(1)Neurological Institute, Epilepsy Center, Cleveland Clinic, OH 44195, USA.

FRACTAL methods offer an invaluable means of investigating turbulent nonlinearity

in non-stationary biomedical recordings from the brain. Here, we investigate

properties of complexity (i.e. the correlation dimension, maximum Lyapunov

exponent, 1/f(γ) noise and approximate entropy) and multiFRACTALity in background

neuronal noise-like activity underlying epileptiform transitions recorded at the

intracellular and local network scales from two in vitro models: the whole-intact

mouse hippocampus and lesional human hippocampal slices. Our results show

evidence for reduced dynamical complexity and multiFRACTAL signal features

following transition to the ictal epileptiform state. These findings suggest that

pathological breakdown in multiFRACTAL complexity coincides with loss of signal

variability or heterogeneity, consistent with an unhealthy ictal state that is

far from the equilibrium of turbulent yet healthy FRACTAL dynamics in the brain.

Thus, it appears that background noise-like activity successfully captures

complex and multiFRACTAL signal features that may, at least in part, be used to

classify and identify brain state transitions in the healthy and epileptic brain,

offering potential promise for therapeutic neuromodulatory strategies for

afflicted patients suffering from epilepsy and other related neurological


PMID: 22929878 [PubMed - indexed for MEDLINE]

54. Anesthesiology. 2012 Oct;117(4):810-21.

MultiFRACTAL analysis of hemodynamic behavior: intraoperative instability and its

pharmacological manipulation.

Bishop SM(1), Yarham SI, Navapurkar VU, Menon DK, Ercole A.

Author information:

(1)Division of Anaesthesia, School of Clinical Medicine, University of Cambridge,

Cambridge, United Kingdom.

Comment in

Anesthesiology. 2012 Oct;117(4):699-700.

BACKGROUND: Physiologic instability is a common clinical problem in the

critically ill. Many natural feedback systems are nonlinear, and seemingly random

fluctuations may result from the amplification of external perturbations or even

arise de novo as a consequence of their underlying dynamics. Characterization of

the underlying nonlinear state may be of clinical importance, providing a

technique to monitor complex physiology in real-time, guiding patient care and

improving outcomes.

METHODS: We employ the wavelet modulus maxima technique to characterize the

multiFRACTAL properties of heart rate and mean arterial pressure physiology

retrospectively for four patients during open abdominal aortic aneurysm repair.

We calculated point-estimates for the dominant Hölder exponent (hm, hm) and

multiFRACTAL spectrum width-at-half-height for both heart rate and mean arterial

pressure signals. We investigated how these parameters changed with the

administration of an intravenous vasoconstrictor and examined how this varied

with atropine pretreatment.

RESULTS: Hypotensive patients showed lower values of hm, consistent with a more

highly fluctuating and complex behavior. Treatment with a vasoconstrictor led to

a transient increase in hm, revealing the appearance of longer-range

correlations, but did not impact hm. On the other hand, prior treatment with

atropine had no effect on hm behavior but did tend to increase hm.

CONCLUSIONS: Hypotension leads to a reduction in dominant Hölder exponents for

mean arterial pressure, demonstrating an increasing signal complexity consistent

with the activation of important homeokinetic processes. Conversely,

pharmacological interventions may also alter the underlying dynamics.

Pharmacological restoration of homeostasis leads to system decomplexification,

suggesting that homeokinetic mechanisms are derecruited as homeostasis is


PMID: 22913922 [PubMed - indexed for MEDLINE]

55. IEEE Trans Image Process. 2013 Jan;22(1):286-99. doi: 10.1109/TIP.2012.2214040.

Epub 2012 Aug 17.

Wavelet domain multiFRACTAL analysis for static and dynamic texture


Ji H(1), Yang X, Ling H, Xu Y.

Author information:

(1)Department of Mathematics, National University of Singapore, Singapore.

In this paper, we propose a new texture descriptor for both static and dynamic

textures. The new descriptor is built on the wavelet-based spatial-frequency

analysis of two complementary wavelet pyramids: standard multiscale and wavelet

leader. These wavelet pyramids essentially capture the local texture responses in

multiple high-pass channels in a multiscale and multiorientation fashion, in

which there exists a strong power-law relationship for natural images. Such a

power-law relationship is characterized by the so-called multiFRACTAL analysis.

In addition, two more techniques, scale normalization and multiorientation image

averaging, are introduced to further improve the robustness of the proposed

descriptor. Combining these techniques, the proposed descriptor enjoys both high

discriminative power and robustness against many environmental changes. We apply

the descriptor for classifying both static and dynamic textures. Our method has

demonstrated excellent performance in comparison with the state-of-the-art

approaches in several public benchmark datasets.

PMID: 22910109 [PubMed - indexed for MEDLINE]

56. Izv Akad Nauk Ser Biol. 2012 May-Jun;(3):327-35.

[MultiFRACTAL analysis of the species structure of freshwater hydrobiocenoses].

[Article in Russian]

Gelashvili DB, Iudin DI, Iakimov VN, Solntsev LA, Rozenberg GS, Shurganova GV,

Okhapkin AG, Startseva NA, Pukhnarevich DA, Snegireva MS.

The principles and methods of FRACTAL analysis of the species structure of

freshwater phytoplankton, zooplankton, and macrozoobenthos communities of plain

water reservoirs and urban waterbodies are discussed. The theoretical foundation

and experimental verification are provided for the authors' concept of

self-similar (quasi-FRACTAL) nature of the species structure of communities.

According to this concept, the adequate mathematical image of species richness

accumulation with growing sampling effort is quasi-monoFRACTALs, while the

generalized geometric image of the species structure of the community is a

multiFRACTAL spectrum.

PMID: 22834317 [PubMed - indexed for MEDLINE]

57. Fiziol Cheloveka. 2012 May-Jun;38(3):30-6.

[FRACTAL characteristics of the functional state of the brain in patients with

anxious phobic disorders].

[Article in Russian]

Dik OE, Sviatogor IA, Ishinova VA, Nozdrachev AD.

The task of estimation of the functional state of the human brain during

psychotherapeutic treatment of psychogenic pain in patients with anxious phobic

disorders is examined. For solving the task the methods of spectral and

multiFRACTAL analyses of EEG fragments are applied during the perception of

psychogenic pain and its removal by the psychorelaxation technique. Contrary to

power spectra singularity spectra allow to distinguish EEGs quanitatively in the

examined functional states of the human brain. The pain suppression in patients

with anxious phobic disorders during psychorelaxation is accompanied by changing

the width of the singularity spectrum and approximation of this multiFRACTAL

partameter to the value corresponding to a healthy subject.

PMID: 22830241 [PubMed - indexed for MEDLINE]

58. PLoS One. 2012;7(7):e41148. doi: 10.1371/journal.pone.0041148. Epub 2012 Jul 18.

FRACTAL dimension and vessel complexity in patients with cerebral arteriovenous


Reishofer G(1), Koschutnig K, Enzinger C, Ebner F, Ahammer H.

Author information:

(1)Department of Radiology, MR-Physics, Medical University of Graz, Graz, Austria.

The FRACTAL dimension (FD) can be used as a measure for morphological complexity

in biological systems. The aim of this study was to test the usefulness of this

quantitative parameter in the context of cerebral vascular complexity. FRACTAL

analysis was applied on ten patients with cerebral arteriovenous malformations

(AVM) and ten healthy controls. Maximum intensity projections from Time-of-Flight

MRI scans were analyzed using different measurements of FD, the Box-counting

dimension, the Minkowski dimension and generalized dimensions evaluated by means

of multiFRACTAL analysis. The physiological significance of this parameter was

investigated by comparing values of FD first, with the maximum slope of contrast

media transit obtained from dynamic contrast-enhanced MRI data and second, with

the nidus size obtained from X-ray angiography data. We found that for all

methods, the Box-counting dimension, the Minkowski dimension and the generalized

dimensions FD was significantly higher in the hemisphere with AVM compared to the

hemisphere without AVM indicating that FD is a sensitive parameter to capture

vascular complexity. Furthermore we found a high correlation between FD and the

maximum slope of contrast media transit and between FD and the size of the

central nidus pointing out the physiological relevance of FD. The proposed method

may therefore serve as an additional objective parameter, which can be assessed

automatically and might assist in the complex workup of AVMs.

PMCID: PMC3399805

PMID: 22815946 [PubMed - indexed for MEDLINE]

59. PLoS One. 2012;7(7):e40693. doi: 10.1371/journal.pone.0040693. Epub 2012 Jul 17.

Evidence of multiFRACTALity from emerging European stock markets.

Caraiani P.

Author information:

Institute for Economic Forecasting, Romanian Academy, Bucharest, Romania.

We test for the presence of multiFRACTALity in the daily returns of the three

most important stock market indices from Central and Eastern Europe, Czech PX,

Hungarian BUX and Polish WIG using the Empirical Mode Decomposition based

MultiFRACTAL Detrended Fluctuation Analysis. We found that the global Hurst

coefficient varies with the q coefficient and that there is multiFRACTALity

evidenced through the multiFRACTAL spectrum. The exercise is replicated for the

sample around the high volatility period corresponding to the last global

financial crisis. Although no direct link has been found between the crisis and

the multiFRACTAL spectrum, the crisis was found to influence the overall shape as

quantified through the norm of the multiFRACTAL spectrum.

PMCID: PMC3398935

PMID: 22815792 [PubMed - indexed for MEDLINE]

60. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Apr;85(4 Pt 2):046208. Epub 2012

Apr 12.

MultiFRACTAL dimensions for all moments for certain critical random-matrix

ensembles in the strong multiFRACTALity regime.

Bogomolny E(1), Giraud O.

Author information:

(1)Université Paris-Sud, CNRS, LPTMS, UMR8626, Orsay, France.

We construct perturbation series for the qth moment of eigenfunctions of various

critical random-matrix ensembles in the strong multiFRACTALity regime close to

localization. Contrary to previous investigations, our results are valid in the

region q<1/2. Our findings allow one to verify, at first leading orders in the

strong multiFRACTALity limit, the symmetry relation for anomalous FRACTAL

dimensions Δ(q)=Δ(1-q), recently conjectured for critical models where an analog

of the metal-insulator transition takes place. It is known that this relation is

verified at leading order in the weak multiFRACTALity regime. Our results thus

indicate that this symmetry holds in both limits of small and large coupling

constant. For general values of the coupling constant we present careful

numerical verifications of this symmetry relation for different critical

random-matrix ensembles. We also present an example of a system closely related

to one of these critical ensembles, but where the symmetry relation, at least

numerically, is not fulfilled.

PMID: 22680557 [PubMed]

61. Front Physiol. 2012 Jun 4;3:141. doi: 10.3389/fphys.2012.00141. eCollection 2012.

Introduction to multiFRACTAL detrended fluctuation analysis in matlab.

Ihlen EA.

Author information:

Department of Neuroscience, Norwegian University of Science and Technology

Trondheim, Norway.

FRACTAL structures are found in biomedical time series from a wide range of

physiological phenomena. The multiFRACTAL spectrum identifies the deviations in

FRACTAL structure within time periods with large and small fluctuations. The

present tutorial is an introduction to multiFRACTAL detrended fluctuation

analysis (MFDFA) that estimates the multiFRACTAL spectrum of biomedical time

series. The tutorial presents MFDFA step-by-step in an interactive Matlab

session. All Matlab tools needed are available in Introduction to MFDFA folder at

the website MFDFA are introduced in Matlab code

boxes where the reader can employ pieces of, or the entire MFDFA to example time

series. After introducing MFDFA, the tutorial discusses the best practice of

MFDFA in biomedical signal processing. The main aim of the tutorial is to give

the reader a simple self-sustained guide to the implementation of MFDFA and

interpretation of the resulting multiFRACTAL spectra.

PMCID: PMC3366552

PMID: 22675302 [PubMed]

62. Microcirculation. 2012 Oct;19(7):652-63. doi: 10.1111/j.1549-8719.2012.00200.x.

Skin graft vascular maturation and remodeling: a multiFRACTAL approach to

morphological quantification.

Gould DJ(1), Reece GP.

Author information:

(1)Medical Scientist Training Program, Baylor College of Medicine, Houston, Texas

77030, USA.

OBJECTIVE: One important contributor to tissue graft viability is angiogenic

maturation of the graft tissue bed. This study uses scale-invariant microvascular

morphological quantification to track vessel maturation and remodeling in a

split-thickness skin-grafting model over 21 days, comparing the results to

classical techniques.

METHODS: Images from a previous study of split-thickness skin grafting in rats

were analyzed. Microvascular morphology (FRACTAL and multiFRACTAL dimensions,

lacunarity, and vessel density) within fibrin interfaces of samples over time was

quantified using classical semi-automated methods and automated multiFRACTAL and

lacunarity analyses.

RESULTS: Microvessel morphology increased in density and complexity, from three

to seven days after engraftment and then regressed by 21 days. Vessel density

increased from 0.07 on day 3 to 0.20 on day 7 and then decreased to 0.06 on day

21. A similar trend was seen for the FRACTAL dimension that increased from 1.56

at three days to 1.77 at seven days then decreased to 1.57 by 21 days. Vessel

diameters did not change whereas complexity and density did, signaling


CONCLUSIONS: This new automated analysis identified design parameters for tissue

engraftment and could be used in other models of graft vessel biology to track

proliferation and pruning of complex vessel beds.

© 2012 John Wiley & Sons Ltd.

PMCID: PMC3467318

PMID: 22672367 [PubMed - indexed for MEDLINE]

63. Anal Quant Cytol Histol. 2012 Apr;34(2):105-8.

MultiFRACTAL spectrum differentiation of well-differentiated adenocarcinoma from

complex atypical hyperplasia of the uterus.

Barwad A(1), Dey P.

Author information:

(1)Department of Cytopathology and Gynecological Pathology, Postgraduate Institute

of Medical Education and Research, Chandigarh, India.

OBJECTIVE: To introduce a new field of multiFRACTAL spectrum in distinguishing

between endometrial well-differentiated adenocarcinoma (WDAC) and complex

atypical hyperplasia (CAH).

STUDY DESIGN: Thirteen cases of CAH and 16 of WDAC were selected from radical

hysterectomy specimens, and multiFRACTAL spectrum was measured from at least 4-5

representative digitized images of each case. The data were collected from

f(alpha) vs. alpha curves. The values of alpha max, alpha min, and their

difference delta alpha (alpha max-alpha min) were recorded and the data compared.

RESULTS: The mean +/- SD of alpha max, alpha min, and delta alpha of CAH were

2.36357 +/- 0.111623, 1.71357 +/- 0.032160, and 0.64214 +/- 0.094248,

respectively. The mean +/- SD of alpha max, alpha min, and delta of WDAC were

2.50640 +/- 0.104545, 1.72100 +/- 0.036436, and 0.77620 +/- 0.108268,

respectively. The mean of alpha max, alpha min, and delta alpha of WDAC were

higher than in CAH. Mann-Whitney U test showed significant difference (p <

0.0001) of alpha max and delta alpja of WDAC and CAH.

CONCLUSION: MultiFRACTAL dimension is significantly different in WDAC and CAH.

The multiFRACTAL dimension is a new area in pathology. This study demonstrates

the potential usefulness of multiFRACTAL analysis in histopathology.

PMID: 22611766 [PubMed - indexed for MEDLINE]

64. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Mar;85(3 Pt 1):031142. Epub 2012

Mar 28.

Markov-switching multiFRACTAL models as another class of random-energy-like

models in one-dimensional space.

Saakian DB.

Author information:

Institute of Physics, Academia Sinica, Nankang, Taipei 11529, Taiwan.

We map the Markov-switching multiFRACTAL model (MSM) onto the random energy model

(REM). The MSM is, like the REM, an exactly solvable model in one-dimensional

space with nontrivial correlation functions. According to our results, four

different statistical physics phases are possible in random walks with

multiFRACTAL behavior. We also introduce the continuous branching version of the

model, calculate the moments, and prove multiscaling behavior. Different phases

have different multiscaling properties.

PMID: 22587073 [PubMed - indexed for MEDLINE]

65. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Mar;85(3 Pt 1):031113. Epub 2012

Mar 13.

Geometrical exponents of contour loops on synthetic multiFRACTAL rough surfaces:

multiplicative hierarchical cascade p model.

Hosseinabadi S(1), Rajabpour MA, Movahed MS, Allaei SM.

Author information:

(1)Department of Physics, Alzahra University, Tehran, Iran.

In this paper, we study many geometrical properties of contour loops to

characterize the morphology of synthetic multiFRACTAL rough surfaces, which are

generated by multiplicative hierarchical cascading processes. To this end, two

different classes of multiFRACTAL rough surfaces are numerically simulated. As

the first group, singular measure multiFRACTAL rough surfaces are generated by

using the p model. The smoothened multiFRACTAL rough surface then is simulated by

convolving the first group with a so-called Hurst exponent, H*. The generalized

multiFRACTAL dimension of isoheight lines (contours), D(q), correlation exponent

of contours, x(l), cumulative distributions of areas, ξ, and perimeters, η, are

calculated for both synthetic multiFRACTAL rough surfaces. Our results show that

for both mentioned classes, hyperscaling relations for contour loops are the same

as that of monoFRACTAL systems. In contrast to singular measure multiFRACTAL

rough surfaces, H* plays a leading role in smoothened multiFRACTAL rough

surfaces. All computed geometrical exponents for the first class depend not only

on its Hurst exponent but also on the set of p values. But in spite of

multiFRACTAL nature of smoothened surfaces (second class), the corresponding

geometrical exponents are controlled by H*, the same as what happens for

monoFRACTAL rough surfaces.

PMID: 22587044 [PubMed - indexed for MEDLINE]

66. Phys Rev Lett. 2012 Mar 30;108(13):134502. Epub 2012 Mar 28.

Distribution of particles and bubbles in turbulence at a small Stokes number.

Fouxon I.

Author information:

Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University,

Tel-Aviv 69978, Israel.

The inertia of particles driven by the turbulent flow of the surrounding fluid

makes them prefer certain regions of the flow. The heavy particles lag behind the

flow and tend to accumulate in the regions with less vorticity, while the light

particles do the opposite. As a result of the long-time evolution, the particles

distribute over a multiFRACTAL attractor in space. We consider this distribution

using our recent results on the steady states of chaotic dynamics. We describe

the preferential concentration analytically and derive the correlation functions

of density and the FRACTAL dimensions of the attractor. The results are obtained

for real turbulence and are testable experimentally.

PMID: 22540704 [PubMed]

67. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Feb;85(2 Pt 1):021915. Epub 2012

Feb 17.

Multiscale multiFRACTAL analysis of heart rate variability recordings with a

large number of occurrences of arrhythmia.

Gierałtowski J(1), Żebrowski JJ, Baranowski R.

Author information:

(1)Faculty of Physics, Warsaw University of Technology, Warsaw, Poland.

Human heart rate variability, in the form of time series of intervals between

heart beats, shows complex, FRACTAL properties. Recently, it was demonstrated

many times that the FRACTAL properties vary from point to point along the series,

leading to multiFRACTALity. In this paper, we concentrate not only on the fact

that the human heart rate has multiFRACTAL properties but also that these

properties depend on the time scale in which the multiFRACTALity is measured.

This time scale is related to the frequency band of the signal. We find that

human heart rate variability appears to be far more complex than hitherto

reported in the studies using a fixed time scale. We introduce a method called

multiscale multiFRACTAL analysis (MMA), which allows us to extend the description

of heart rate variability to include the dependence on the magnitude of the

variability and time scale (or frequency band). MMA is relatively immune to

additive noise and nonstationarity, including the nonstationarity due to

inclusions into the time series of events of a different dynamics (e.g.,

arrhythmic events in sinus rhythm). The MMA method may provide new ways of

measuring the nonlinearity of a signal, and it may help to develop new methods of

medical diagnostics.

© 2012 American Physical Society

PMID: 22463252 [PubMed - indexed for MEDLINE]

68. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Feb;85(2 Pt 1):021407. Epub 2012

Feb 27.

MultiFRACTAL analysis of the branch structure of diffusion-limited aggregates.

Hanan WG(1), Heffernan DM.

Author information:

(1)Department of Mathematical Physics, National University of Ireland Maynooth,

County Kildare, Ireland.

We examine the branch structure of radial diffusion-limited aggregation (DLA)

clusters for evidence of multiFRACTALity. The lacunarity of DLA clusters is

measured and the generalized dimensions D(q) of their mass distribution is

estimated using the sandbox method. We find that the global n-fold symmetry of

the aggregates can induce anomalous scaling behavior into these measurements.

However, negating the effects of this symmetry, standard scaling is recovered.

© 2012 American Physical Society

PMID: 22463212 [PubMed - indexed for MEDLINE]

69. Comput Methods Programs Biomed. 2012 Oct;108(1):176-85. doi:

10.1016/j.cmpb.2012.02.014. Epub 2012 Mar 27.

MultiFRACTAL characterisation of electrocardiographic RR and QT time-series

before and after progressive exercise.

Lewis MJ(1), Short AL, Suckling J.

Author information:

(1)College of Engineering, Swansea University, Swansea, UK.

The scaling (FRACTAL) characteristics of electrocardiograms (ECG) provide

information complementary to traditional linear measurements (heart rate,

repolarisation rate etc.) allowing them to discriminate signal changes induced

pathologically or pharmacologically. Under such interventions scaling behaviour

is described by multiple local scaling exponents and the signal is termed

multiFRACTAL. Exercise testing is used extensively to quantify and monitor

cardiorespiratory health, yet to our knowledge there has been no previous

multiFRACTAL investigation of exercise-induced changes in heart rate dynamics.

Ambulatory ECGs were acquired from eight healthy participants. Linear descriptive

statistics and a parameterisation of multiFRACTAL singularity spectra were

determined for inter-beat (RR) and intra-beat (QT) time-series before and after

exercise. Multivariate analyses of both linear and multiFRACTAL measures

discriminated between pre- and post-exercise periods and proportionally more

significant correlations were observed between linear than between multiFRACTAL

measures. Variance was more uniformly distributed over the first three principal

components for multiFRACTAL measures and the two classes of measures were

uncorrelated. Order and phase randomisation of the time-series indicated that

both sample distribution and correlation properties contribute to

multiFRACTALilty. This exploratory study indicates the possibility of using

physical exercise in conjunction with multiFRACTAL methodology as an adjunctive

description of autonomically mediated modulation of heart rate.

Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

PMID: 22459102 [PubMed - indexed for MEDLINE]

70. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jan;85(1 Pt 1):011123. Epub 2012

Jan 13.

Linear polymers in disordered media: the shortest, the longest, and the mean

self-avoiding walk on percolation clusters.

Janssen HK(1), Stenull O.

Author information:

(1)Institut für Theoretische Physik III, Heinrich-Heine-Universität, D-40225

Düsseldorf, Germany.

Long linear polymers in strongly disordered media are well described by

self-avoiding walks (SAWs) on percolation clusters and a lot can be learned about

the statistics of these polymers by studying the length distribution of SAWs on

percolation clusters. This distribution encompasses 2 distinct averages, viz.,

the average over the conformations of the underlying cluster and the SAW

conformations. For the latter average, there are two basic options, one being

static and one being kinetic. It is well known for static averaging that if the

disorder of the underlying medium is weak, this disorder is redundant in the

sense the renormalization group; i.e., differences to the ordered case appear

merely in nonuniversal quantities. Using dynamical field theory, we show that the

same holds true for kinetic averaging. Our main focus, however, lies on strong

disorder, i.e., the medium being close to the percolation point, where disorder

is relevant. Employing a field theory for the nonlinear random resistor network

in conjunction with a real-world interpretation of the corresponding Feynman

diagrams, we calculate the scaling exponents for the shortest, the longest, and

the mean or average SAW to 2-loop order. In addition, we calculate to 2-loop

order the entire family of multiFRACTAL exponents that governs the moments of the

the statistical weights of the elementary constituents (bonds or sites of the

underlying FRACTAL cluster) contributing to the SAWs. Our RG analysis reveals

that kinetic averaging leads to renormalizability whereas static averaging does

not, and hence, we argue that the latter does not lead to a well-defined scaling

limit. We discuss the possible implications of this finding for experiments and

numerical simulations which have produced widespread results for the exponent of

the average SAW. To corroborate our results, we also study the well-known

Meir-Harris model for SAWs on percolation clusters. We demonstrate that the

Meir-Harris model leads back up to 2-loop order to the renormalizable real-world

formulation with kinetic averaging if the replica limit is consistently performed

at the first possible instant in the course of the calculation.

© 2012 American Physical Society

PMID: 22400528 [PubMed - indexed for MEDLINE]

71. Biomed Microdevices. 2012 Jun;14(3):541-8. doi: 10.1007/s10544-012-9631-1.

Application of multiFRACTAL analysis on microscopic images in the classification

of metastatic bone disease.

Vasiljevic J(1), Reljin B, Sopta J, Mijucic V, Tulic G, Reljin I.

Author information:

(1)Institute "Mihajlo Pupin", University of Belgrade, Volgina 15, Belgrade, Serbia.

The paper considers the method, based on multiFRACTAL (MF) analysis, for

classifying the shape of tissue cells from microscopis images, identifying the

primary cancer in cases of metastasis bone disease. Diagnosis of primary cancer

is of great importance, because further treatment depends on how successful and

accurate that diagnosis is. This method can be applied as an additional and

objective tool in primary cancer diagnosis, as well as in decreasing of the

subjective factor and error probability. The method is tested over a large number

(1050) of clinical cases from the Institute of Pathology, University of Belgrade.

The results of computer-aided analysis of images have been presented and


PMID: 22327812 [PubMed - indexed for MEDLINE]

72. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 2):066123. Epub 2011

Dec 27.

MonoFRACTAL and multiFRACTAL analysis of the spatial distribution of earthquakes

in the central zone of Chile.

Pastén D(1), Muñoz V, Cisternas A, Rogan J, Valdivia JA.

Author information:

(1)Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653,

Santiago, Chile.

Statistical and FRACTAL properties of the spatial distribution of earthquakes in

the central zone of Chile are studied. In particular, data are shown to behave

according to the well-known Gutenberg-Richter law. The FRACTAL structure is

evident for epicenters, not for hypocenters. The multiFRACTAL spectrum is also

determined, both for the spatial distribution of epicenters and hypocenters. For

negative values of the index of multiFRACTAL measure q, the multiFRACTAL

spectrum, which usually cannot be reliably found from data, is calculated from a

generalized Cantor-set model, which fits the multiFRACTAL spectrum for q > 0, a

technique which has been previously applied for analysis of solar wind data.

PMID: 22304171 [PubMed]

73. Top Cogn Sci. 2012 Jan;4(1):87-93; discussion 94-102. doi:

10.1111/j.1756-8765.2011.01164.x. Epub 2011 Oct 24.

Abstract concepts require concrete models: why cognitive scientists have not yet

embraced nonlinearly coupled, dynamical, self-organized critical, synergistic,

scale-free, exquisitely context-sensitive, interaction-dominant, multiFRACTAL,

interdependent brain-body-niche systems.

Wagenmakers EJ(1), van der Maas HL, Farrell S.

Author information:

(1)Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.

Comment on

Top Cogn Sci. 2012 Jan;4(1):7-20.

Top Cogn Sci. 2012 Jan;4(1):35-50.

Top Cogn Sci. 2012 Jan;4(1):21-34.

Top Cogn Sci. 2012 Jan;4(1):51-62.

After more than 15 years of study, the 1/f noise or complex-systems approach to

cognitive science has delivered promises of progress, colorful verbiage, and

statistical analyses of phenomena whose relevance for cognition remains unclear.

What the complex-systems approach has arguably failed to deliver are concrete

insights about how people perceive, think, decide, and act. Without formal models

that implement the proposed abstract concepts, the complex-systems approach to

cognitive science runs the danger of becoming a philosophical exercise in

futility. The complex-systems approach can be informative and innovative, but

only if it is implemented as a formal model that allows concrete prediction,

falsification, and comparison against more traditional approaches.

Copyright © 2011 Cognitive Science Society, Inc.

PMID: 22253182 [PubMed - indexed for MEDLINE]

74. Top Cogn Sci. 2012 Jan;4(1):51-62. doi: 10.1111/j.1756-8765.2011.01162.x. Epub

2011 Oct 24.

MultiFRACTAL dynamics in the emergence of cognitive structure.

Dixon JA(1), Holden JG, Mirman D, Stephen DG.

Author information:

(1)Department of Psychology, University of Connecticut, USA.

Comment in

Top Cogn Sci. 2012 Jan;4(1):72-7; discussion 94-102.

Top Cogn Sci. 2012 Jan;4(1):87-93; discussion 94-102.

Top Cogn Sci. 2012 Jan;4(1):63-71; discussion 94-102.

Top Cogn Sci. 2012 Jan;4(1):84-6; discussion 94-102.

Top Cogn Sci. 2012 Jan;4(1):78-83; discussion 94-102.

The complex-systems approach to cognitive science seeks to move beyond the

formalism of information exchange and to situate cognition within the broader

formalism of energy flow. Changes in cognitive performance exhibit a FRACTAL

(i.e., power-law) relationship between size and time scale. These FRACTAL

fluctuations reflect the flow of energy at all scales governing cognition.

Information transfer, as traditionally understood in the cognitive sciences, may

be a subset of this multiscale energy flow. The cognitive system exhibits not

just a single power-law relationship between fluctuation size and time scale but

actually exhibits many power-law relationships, whether over time or space. This

change in FRACTAL scaling, that is, multiFRACTALity, provides new insights into

changes in energy flow through the cognitive system. We survey recent findings

demonstrating the role of multiFRACTALity in (a) understanding atypical

developmental outcomes, and (b) predicting cognitive change. We propose that

multiFRACTALity provides insights into energy flows driving the emergence of

cognitive structure.

Copyright © 2011 Cognitive Science Society, Inc.

PMID: 22253177 [PubMed - indexed for MEDLINE]

75. PLoS One. 2012;7(1):e29956. doi: 10.1371/journal.pone.0029956. Epub 2012 Jan 6.

Comparing monoFRACTAL and multiFRACTAL analysis of corrosion damage evolution in

reinforcing bars.

Xu Y(1), Qian C, Pan L, Wang B, Lou C.

Author information:

(1)School of Materials Science and Engineering, Southeast University, Nanjing,

Jiangsu, People's Republic of China.

Based on FRACTAL theory and damage mechanics, the aim of this paper is to

describe the monoFRACTAL and multiFRACTAL characteristics of corrosion morphology

and develop a new approach to characterize the nonuniform corrosion degree of

reinforcing bars. The relationship between FRACTAL parameters and tensile

strength of reinforcing bars are discussed. The results showed that corrosion

mass loss ratio of a bar cannot accurately reflect the damage degree of the bar.

The corrosion morphology of reinforcing bars exhibits both monoFRACTAL and

multiFRACTAL features. The FRACTAL dimension and the tensile strength of corroded

steel bars exhibit a power function relationship, while the width of multiFRACTAL

spectrum and tensile strength of corroded steel bars exhibit a linear

relationship. By comparison, using width of multiFRACTAL spectrum as multiFRACTAL

damage variable not only reflects the distribution of corrosion damage in

reinforcing bars, but also reveals the influence of nonuniform corrosion on the

mechanical properties of reinforcing bars. The present research provides a new

approach for the establishment of corrosion damage constitutive models of

reinforcing bars.

PMCID: PMC3253123

PMID: 22238682 [PubMed - indexed for MEDLINE]

76. Anal Cell Pathol (Amst). 2012;35(2):123-6. doi: 10.3233/ACP-2011-0045.

MultiFRACTAL feature descriptor for histopathology.

Atupelage C(1), Nagahashi H, Yamaguchi M, Sakamoto M, Hashiguchi A.

Author information:

(1)Department of Computational Intelligence and Systems Science, Tokyo Institute of

Technology, Tokyo, Japan.

BACKGROUND: Histologic image analysis plays an important role in cancer

diagnosis. It describes the structure of the body tissues and abnormal structure

gives the suspicion of the cancer or some other diseases. Observing the

structural changes of these chaotic textures from the human eye is challenging

process. However, the challenge can be defeat by forming mathematical descriptor

to represent the histologic texture and classify the structural changes via a

sophisticated computational method.

OBJECTIVE: In this paper, we propose a texture descriptor to observe the

histologic texture into highly discriminative feature space.

METHOD: FRACTAL dimension describes the self-similar structures in different and

more accurate manner than topological dimension. Further, the FRACTAL phenomenon

has been extended to natural structures (images) as multiFRACTAL dimension. We

exploited the multiFRACTAL analysis to represent the histologic texture, which

derive more discriminative feature space for classification.

RESULTS: We utilized a set of histologic images (belongs to liver and prostate

specimens) to assess the discriminative power of the multiFRACTAL features. The

experiment was organized to classify the given histologic texture as cancer and

non-cancer. The results show the discrimination capability of multiFRACTAL

features by achieving approximately 95% of correct classification rate.

CONCLUSION: MultiFRACTAL features are more effective to describe the histologic

texture. The proposed feature descriptor showed high classification rate for both

liver and prostate data sample datasets.

PMID: 22101185 [PubMed - indexed for MEDLINE]

77. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Sep;84(3 Pt 2):036212. Epub 2011

Sep 22.

Perturbation approach to multiFRACTAL dimensions for certain critical

random-matrix ensembles.

Bogomolny E(1), Giraud O.

Author information:

(1)Univ. Paris-Sud, CNRS, LPTMS, UMR 8626, Orsay, F-91405, France.

FRACTAL dimensions of eigenfunctions for various critical random matrix ensembles

are investigated in perturbation series in the regimes of strong and weak

multiFRACTALity. In both regimes, we obtain expressions similar to those of the

critical banded random matrix ensemble extensively discussed in the literature.

For certain ensembles, the leading-order term for weak multiFRACTALity can be

calculated within standard perturbation theory. For other models, such a direct

approach requires modifications, which are briefly discussed. Our analytical

formulas are in good agreement with numerical calculations.

PMID: 22060480 [PubMed]

78. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Sep;84(3 Pt 2):036118. Epub 2011

Sep 30.

MultiFRACTALity of complex networks.

Furuya S(1), Yakubo K.

Author information:

(1)Department of Mathematical Informatics, The University of Tokyo, Tokyo 113-8656,


We demonstrate analytically and numerically the possibility that the FRACTAL

property of a scale-free network cannot be characterized by a unique FRACTAL

dimension and the network takes a multiFRACTAL structure. It is found that the

mass exponents τ(q) for several deterministic, stochastic, and real-world FRACTAL

scale-free networks are nonlinear functions of q, which implies that structural

measures of these networks obey the multiFRACTAL scaling. In addition, we give a

general expression of τ(q) for some class of FRACTAL scale-free networks by a

mean-field approximation. The multiFRACTAL property of network structures is a

consequence of large fluctuations of local node density in scale-free networks.

PMID: 22060467 [PubMed]

79. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Sep;84(3 Pt 1):031918. Epub 2011

Sep 19.

MultiFRACTAL analysis of thermal denaturation based on the Peyrard-Bishop-Dauxois


Behnia S(1), Akhshani A, Panahi M, Mobaraki A, Ghaderian M.

Author information:

(1)Department of Physics, Urmia University of Technology, Orumieh, Iran.

The theory of DNA dynamics is exceedingly complex and not easily explained. In

the past two decades, by adapting methods of statistical physics, the dynamics of

DNA in contact with a thermal bath is widely studied. In this paper, the thermal

denaturation of DNA in the framework of the Peyrard-Bishop-Dauxois (PBD) model

through the Rényi dimension is investigated. As a result, the Rényi dimension

spectrum of the melting transition process reveals the multiFRACTAL nature of the

dynamics of the Peyrard-Bishop-Dauxois model. Also, it can be concluded that the

Rényi dimension (D(q)) at negative values of q is the characteristic signature of

pre-melting and thermal denaturation of DNA. Furthermore, this approach is in

excellent agreement with previous experimental studies.

PMID: 22060414 [PubMed - indexed for MEDLINE]

80. Front Integr Neurosci. 2011 Oct 17;5:62. doi: 10.3389/fnint.2011.00062.

eCollection 2011.

Effects of accuracy feedback on FRACTAL characteristics of time estimation.

Kuznetsov NA(1), Wallot S.

Author information:

(1)Perceptual-Motor Dynamics Laboratory, Department of Psychology, CAP Center for

Cognition, Action and Perception, University of Cincinnati Cincinnati, OH, USA.

The current experiment investigated the effect of visual accuracy feedback on the

structure of variability of time interval estimates in the continuation tapping

paradigm. Participants were asked to repeatedly estimate a 1-s interval for a

prolonged period of time by tapping their index finger. In some conditions,

participants received accuracy feedback after every estimate, whereas in other

conditions, no feedback was given. Also, the likelihood of receiving visual

feedback was manipulated by adjusting the tolerance band around the 1-s target

interval so that feedback was displayed only if the temporal estimate deviated

from the target interval by more than 50, 100, or 200 ms respectively. We

analyzed the structure of variability of the inter-tap intervals with FRACTAL and

multiFRACTAL methods that allow for a quantification of complex long-range

correlation patterns in the timing performance. Our results indicate that

feedback changes the long-range correlation structure of time estimates:

Increased amounts of feedback lead to a decrease in FRACTAL long-range

correlations, as well to a decrease in the magnitude of local fluctuations in the

performance. The multiFRACTAL characteristics of the time estimates were not

impacted by the presence of accuracy feedback. Nevertheless, most of the data

sets show significant multiFRACTAL signatures. We interpret these findings as

showing that feedback acts to constrain and possibly reorganize timing

performance. Implications for mechanistic and complex systems-based theories of

timing behavior are discussed.

PMCID: PMC3201842

PMID: 22046149 [PubMed]

81. BMC Genomics. 2011 Oct 14;12:506. doi: 10.1186/1471-2164-12-506.

The human genome: a multiFRACTAL analysis.

Moreno PA(1), Vélez PE, Martínez E, Garreta LE, Díaz N, Amador S, Tischer I,

Gutiérrez JM, Naik AK, Tobar F, García F.

Author information:

(1)Escuela de Ingeniería de Sistemas y Computación, Universidad del Valle, Santiago

de Cali, Colombia.

BACKGROUND: Several studies have shown that genomes can be studied via a

multiFRACTAL formalism. Recently, we used a multiFRACTAL approach to study the

genetic information content of the Caenorhabditis elegans genome. Here we

investigate the possibility that the human genome shows a similar behavior to

that observed in the nematode.

RESULTS: We report here multiFRACTALity in the human genome sequence. This

behavior correlates strongly on the presence of Alu elements and to a lesser

extent on CpG islands and (G+C) content. In contrast, no or low relationship was

found for LINE, MIR, MER, LTRs elements and DNA regions poor in genetic

information. Gene function, cluster of orthologous genes, metabolic pathways, and

exons tended to increase their frequencies with ranges of multiFRACTALity and

large gene families were located in genomic regions with varied multiFRACTALity.

Additionally, a multiFRACTAL map and classification for human chromosomes are


CONCLUSIONS: Based on these findings, we propose a descriptive non-linear model

for the structure of the human genome, with some biological implications. This

model reveals 1) a multiFRACTAL regionalization where many regions coexist that

are far from equilibrium and 2) this non-linear organization has significant

molecular and medical genetic implications for understanding the role of Alu

elements in genome stability and structure of the human genome. Given the role of

Alu sequences in gene regulation, genetic diseases, human genetic diversity,

adaptation and phylogenetic analyses, these quantifications are especially


PMCID: PMC3277318

PMID: 21999602 [PubMed - indexed for MEDLINE]

82. Anal Quant Cytol Histol. 2011 Aug;33(4):211-4.

MultiFRACTAL spectrum of chorionic villi: a novel approach.

Dey P.

Author information:

Department of Cytology, Postgraduate Institute of Medical Education and Research,

Chandigarh, India.

OBJECTIVE: To measure the multiFRACTAL dimension in histopathology sections of

chorionic villi to study its role to distinguish between normal chorionic villi

and hydatidiform mole.

STUDY DESIGN: MultiFRACTAL spectrum was measured in 10 each cases of normal

chorionic villi and hydatidiform mole. The values of alpha max and alpha min and

their difference Delta alpha (alpha max--alpha min) were recorded in each case.

The data for these groups were compared.

RESULTS: The mean +/- SD of alpha max, alpha min, and Delta alpha (alpha

max--alpha min) of normal chorionic villi were 2.6335 +/- 0.16109, 1.6975 +/-

0.04435, and 0.9360 +/- 0.12725, respectively. Whereas the mean +/- SD of alpha

max, alpha min, and Delta of hydatidiform moles were 2.3196 +/- 0.11937, 1.6209

+/- 0.06208, and 0.7000 +/- 0.08350, respectively. The mean alpha max, alpha min,

and Delta alpha of normal chorionic villi were much higher than for hydatidiform

mole. Independent sample t-test shows significant difference (p < 0.001) in alpha

max, alpha min, and Delta alpha of normal chorionic villi and hydatidiform mole.

CONCLUSION: MultiFRACTAL dimension was significantly different in normal

chorionic villi and hydatidiform mole.

PMID: 21980625 [PubMed - indexed for MEDLINE]

83. J Phys Condens Matter. 2011 Oct 19;23(41):415601. doi:


Criticality without self-similarity: a 2D system with random long-range hopping.

Ossipov A(1), Rushkin I, Cuevas E.

Author information:

(1)School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD,


We consider a simple model of quantum disorder in two dimensions, characterized

by a long-range site-to-site hopping. The system undergoes a metal–insulator

transition--its eigenfunctions change from being extended to being localized. We

demonstrate that at the point of the transition the nature of the eigenfunctions

depends crucially on the magnitude of the hopping amplitude. At small amplitudes

they are strongly multiFRACTAL. In the opposite limit of large amplitudes, the

eigenfunctions do not become FRACTAL. Their density moments do not scale as a

power of the system size; instead our result suggests a power of the logarithm of

the system size. In this regard, the transition differs from a similar one in the

one-dimensional version of the same system, as well as from the conventional

Anderson transition in more than two dimensions.

© 2011 IOP Publishing Ltd

PMID: 21959771 [PubMed]

84. J Rehabil Res Dev. 2011;48(7):787-800.

Using multiFRACTAL detrended fluctuation analysis to assess sacral skin blood

flow oscillations in people with spinal cord injury.

Liao F(1), Jan YK.

Author information:

(1)Department of Rehabilitation Sciences, University of Oklahoma Health Sciences

Center, Oklahoma City, 73117, USA.

The purpose of this study was to investigate whether the multiFRACTAL detrended

fluctuation analysis (MDFA) of skin blood flow oscillations (BFO) differed

between nondisabled controls and people with spinal cord injury (SCI). The study

of skin BFO has shown promise for assessing blood flow control mechanisms and

risk for pressure ulcers. We recruited 23 subjects, including 11 people with SCI

and 12 nondisabled controls. Thermally induced maximal sacral skin BFO were

measured by laser Doppler flowmetry. MDFA was used to characterize nonlinear

complexity of metabolic (0.0095 to 0.02 Hz), neurogenic (0.02 to 0.05 Hz), and

myogenic (0.05 to 0.15 Hz) BFO. We found that maximal vasodilation was

significantly smaller in people with SCI than in nondisabled controls (p < 0.05).

MDFA showed that metabolic BFO exhibited less complexity in people with SCI (p <

0.05), neurogenic BFO exhibited less complexity in people with complete SCI (p <

0.05), and myogenic BFO did not show significant differences between people with

SCI and nondisabled controls. This study demonstrated the feasibility of using

the MDFA to characterize nonlinear complexity of BFO, which is related to

vasodilatory functions in people with SCI.

PMID: 21938665 [PubMed - indexed for MEDLINE]

85. Physiol Meas. 2011 Oct;32(10):1681-99. doi: 10.1088/0967-3334/32/10/014. Epub

2011 Sep 19.

Aging in autonomic control by multiFRACTAL studies of cardiac interbeat intervals

in the VLF band.

Makowiec D(1), Rynkiewicz A, Wdowczyk-Szulc J, Zarczyńska-Buchowiecka M, Gałaska

R, Kryszewski S.

Author information:

(1)Institute of Theoretical Physics and Astrophysics, University of Gdańsk, 80-952

Gdańsk, ul Wita Stwosza 57, Poland.

The heart rate responds dynamically to various intrinsic and environmental

stimuli. The autonomic nervous system is said to play a major role in this

response. MultiFRACTAL analysis offers a novel method to assess the response of

cardiac interbeat intervals. Twenty-four hour ECG recordings of RR interbeat

intervals (of 48 elderly volunteers (age 65-94), 40 middle-aged persons (age

45-53) and 36 young adults (age 18-26)) were investigated to study the effect of

aging on autonomic regulation during normal activity in healthy adults. Heart

RR-interval variability in the very low frequency (VLF) band (32-420 RR

intervals) was evaluated by multiFRACTAL tools. The nocturnal and diurnal signals

of 6 h duration were studied separately. For each signal, the analysis was

performed twice: for a given signal and for the integrated signal. A multiFRACTAL

spectrum was quantified by the h(max) value at which a multiFRACTAL spectrum

attained its maximum, width of a spectrum, Hurst exponent, extreme events h(left)

and distance between the maxima of a signal and its integrated counterpart. The

following seven characteristics are suggested as quantifying the age-related

decrease in the autonomic function ('int' refers to the integrated signal): (a)

h(sleep)(max) - h(max)(wake) > 0.05 for a signal; (b) h(int)(max) > 1.15 for

wake; (c) h(int)(max) - h(max) > 0.85 for sleep; (d) Hurst(wake) - Hurst(sleep) <

0.01; (e) width(wake) > 0.07; (f) width(int) < 0.30 for sleep; (g) h(int)(left) >

0.75. Eighty-one percent of elderly people had at least four of these properties,

and ninety-two percent of young people had three or less. This shows that the

multiFRACTAL approach offers a concise and reliable index of healthy aging for

each individual. Additionally, the applied method yielded insights into dynamical

changes in the autonomic regulation due to the circadian cycle and aging. Our

observations support the hypothesis that imbalance in the autonomic control due

to healthy aging could be related to changes emerging from the vagal function

(Struzik et al 2006 IEEE Trans. Biomed. Eng. 53 89-94).

PMID: 21926460 [PubMed - indexed for MEDLINE]

86. PLoS One. 2011;6(9):e24331. doi: 10.1371/journal.pone.0024331. Epub 2011 Sep 6.

Facilitating joint chaos and FRACTAL analysis of biosignals through nonlinear

adaptive filtering.

Gao J(1), Hu J, Tung WW.

Author information:

(1)PMB Intelligence LLC, West Lafayette, Indiana, United States of America.

BACKGROUND: Chaos and random FRACTAL theories are among the most important for

fully characterizing nonlinear dynamics of complicated multiscale biosignals.

Chaos analysis requires that signals be relatively noise-free and stationary,

while FRACTAL analysis demands signals to be non-rhythmic and scale-free.

METHODOLOGY/PRINCIPAL FINDINGS: To facilitate joint chaos and FRACTAL analysis of

biosignals, we present an adaptive algorithm, which: (1) can readily remove

nonstationarities from the signal, (2) can more effectively reduce noise in the

signals than linear filters, wavelet denoising, and chaos-based noise reduction

techniques; (3) can readily decompose a multiscale biosignal into a series of

intrinsically bandlimited functions; and (4) offers a new formulation of FRACTAL

and multiFRACTAL analysis that is better than existing methods when a biosignal

contains a strong oscillatory component.

CONCLUSIONS: The presented approach is a valuable, versatile tool for the

analysis of various types of biological signals. Its effectiveness is

demonstrated by offering new important insights into brainwave dynamics and the

very high accuracy in automatically detecting epileptic seizures from EEG


PMCID: PMC3167840

PMID: 21915312 [PubMed - indexed for MEDLINE]

87. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jul;84(1 Pt 2):016208. Epub 2011

Jul 14.

Arbitrary-order Hilbert spectral analysis for time series possessing scaling

statistics: comparison study with detrended fluctuation analysis and wavelet


Huang YX(1), Schmitt FG, Hermand JP, Gagne Y, Lu ZM, Liu YL.

Author information:

(1)Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University,

Shanghai, China.

In this paper we present an extended version of Hilbert-Huang transform, namely

arbitrary-order Hilbert spectral analysis, to characterize the scale-invariant

properties of a time series directly in an amplitude-frequency space. We first

show numerically that due to a nonlinear distortion, traditional methods require

high-order harmonic components to represent nonlinear processes, except for the

Hilbert-based method. This will lead to an artificial energy flux from the

low-frequency (large scale) to the high-frequency (small scale) part. Thus the

power law, if it exists, is contaminated. We then compare the Hilbert method with

structure functions (SF), detrended fluctuation analysis (DFA), and wavelet

leader (WL) by analyzing fractional Brownian motion and synthesized multiFRACTAL

time series. For the former simulation, we find that all methods provide

comparable results. For the latter simulation, we perform simulations with an

intermittent parameter μ=0.15. We find that the SF underestimates scaling

exponent when q>3. The Hilbert method provides a slight underestimation when q>5.

However, both DFA and WL overestimate the scaling exponents when q>5. It seems

that Hilbert and DFA methods provide better singularity spectra than SF and WL.

We finally apply all methods to a passive scalar (temperature) data obtained from

a jet experiment with a Taylor's microscale Reynolds number Re(λ)≃250. Due to the

presence of strong ramp-cliff structures, the SF fails to detect the power law

behavior. For the traditional method, the ramp-cliff structure causes a serious

artificial energy flux from the low-frequency (large scale) to the high-frequency

(small scale) part. Thus DFA and WL underestimate the scaling exponents. However,

the Hilbert method provides scaling exponents ξ(θ)(q) quite close to the one for

longitudinal velocity, indicating a less intermittent passive scalar field than

what was believed before.

PMID: 21867274 [PubMed - indexed for MEDLINE]

88. Phys Rev Lett. 2011 Jul 8;107(2):028101. Epub 2011 Jul 8.

Cell surface as a FRACTAL: normal and cancerous cervical cells demonstrate

different FRACTAL behavior of surface adhesion maps at the nanoscale.

Dokukin ME(1), Guz NV, Gaikwad RM, Woodworth CD, Sokolov I.

Author information:

(1)Department of Physics, Clarkson University, Potsdam, New York 13699-5820, USA.

Here we show that the surface of human cervical epithelial cells demonstrates

substantially different FRACTAL behavior when the cell becomes cancerous.

Analyzing the adhesion maps of individual cervical cells, which were obtained

using the atomic force microscopy operating in the HarmoniX mode, we found that

cancerous cells demonstrate simple FRACTAL behavior, whereas normal cells can

only be approximated at best as multiFRACTAL. Tested on ~300 cells collected from

12 humans, the FRACTAL dimensionality of cancerous cells is found to be

unambiguously higher than that for normal cells.

PMID: 21797643 [PubMed - indexed for MEDLINE]

89. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jun;83(6 Pt 2):066210. Epub 2011

Jun 22.

MultiFRACTAL analysis of nonhyperbolic coupled map lattices: application to

genomic sequences.

Provata A(1), Beck C.

Author information:

(1)Institute of Physical Chemistry, National Center for Scientific Research

Demokritos, GR-15310 Athens, Greece.

Symbolic sequences generated by coupled map lattices (CMLs) can be used to model

the chaotic-like structure of genomic sequences. In this study it is shown that

diffusively coupled Chebyshev maps of order 4 (corresponding to a shift of four

symbols) very closely reproduce the multiFRACTAL spectrum D(q) of human genomic

sequences for coupling constant α = 0.35 ± 0.01 if q > 0. The presence of rare

configurations causes deviations for q < 0, which disappear if the rare event

statistics of the CML is modified. Such rare configurations are known to play

specific functional roles in genomic sequences serving as promoters or regulatory


PMID: 21797464 [PubMed - indexed for MEDLINE]

90. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Mar;83(3 Pt 1):031801. Epub 2011

Mar 2.

Density fluctuations of polymers in disordered media.

Deutsch JM(1), de la Cruz MO.

Author information:

(1)Department of Physics, University of California, Santa Cruz, California 95064,


We study self-avoiding random walks in an environment where sites are excluded

randomly, in two and three dimensions. For a single polymer chain, we study the

statistics of the time averaged monomer density and show that these are well

described by multiFRACTAL statistics. This is true even far from the percolation

transition of the disordered medium. We investigate solutions of chains in a

disordered environment and show that the statistics cease to be multiFRACTAL

beyond the screening length of the solution.

PMID: 21517516 [PubMed - indexed for MEDLINE]

91. Guang Pu Xue Yu Guang Pu Fen Xi. 2011 Feb;31(2):473-7.

[FRACTAL characteristics of visible spectra across a hilly area].

[Article in Chinese]

Zhang FS(1), Liu ZX, Wan HL, Liu M.

Author information:

(1)Institute of Applied Ecology, Chinese Academy of Sciences, Key Laboratory of

Liaoning Water-Saving Agriculture, Shenyang 110016, China.

The spectral characteristic of remotely sensed image is mainly the results of

integrative effects on spectrum from heterogeneous ground reflectors.

Investigating its spatial distribution characteristics may be helpful for image

interpreting and modeling based on remote sensing technique. In the present

study, spatial heterogeneity of remotely sensed multispectral TM image across a

hilly area in late October was studied by the combination of statistical method

and multiFRACTAL analysis. The results showed that distribution of digital number

(DN) values of visible spectra (0.45-0.69 microm) had statistical

scale-invariance. The generalized FRACTAL dimension function D(q) suggested that

distribution of TM 2 (0.52-0.60 microm) DN values was monoFRACTAL type, whereas

DN values of TM 1 (0.45-0.52 microm) and TM 3 (0.63-0.69 microm) had multiFRACTAL

distribution characteristics. The parameters (alpha(max)-alpha(min)) and

[f(a(max))-f(alpha(min))] of multiFRACTAL spectra further indicated that TM 3 DN

values had the high est spatial heterogeneity and most abundant information,

followed by TM 1, while the extremely narrow spectrum of TM 2 DN values showed

its relatively low spatial heterogeneity and information capacity.

PMID: 21510407 [PubMed]

92. Med Biol Eng Comput. 2011 Aug;49(8):925-34. doi: 10.1007/s11517-011-0775-6. Epub

2011 Apr 13.

MultiFRACTAL analysis of nonlinear complexity of sacral skin blood flow

oscillations in older adults.

Liao F(1), Struck BD, Macrobert M, Jan YK.

Author information:

(1)Department of Rehabilitation Sciences, University of Oklahoma Health Sciences

Center, Oklahoma City, OK, USA.

The objective of this study was to investigate the relationship between cutaneous

vasodilatory function and nonlinear complexity of blood flow oscillations (BFO)

in older people. A non-painful fast local heating protocol was applied to the

sacral skin in 20 older subjects with various vasodilatory functions. Laser

Doppler flowmetry was used to measure skin blood oscillations. The complexity of

the characteristic frequencies (i.e., metabolic (0.0095-0.02 Hz), neurogenic

(0.02-0.05 Hz), myogenic (0.05-0.15 Hz), respiratory (0.15-0.4 Hz), and cardiac

(0.4-2 Hz)) of BFO was quantified using the multiFRACTAL detrended fluctuation

analysis. Compared with the 65-75 years group, the complexity of metabolic BFO in

the 75-85 years group was significantly lower at the baseline (P < 0.05) and the

second peak (P < 0.001). Compared with baseline BFO, subjects in the 65-75 years

group had a significant increase in the complexity of metabolic BFO (P < 0.01) in

response to local heating; while subjects in the 75-85 years group did not. Our

findings support the use of multiFRACTAL analysis to assess aging-related

microvascular dysfunction.

PMCID: PMC3140590

PMID: 21487818 [PubMed - indexed for MEDLINE]

93. Med Phys. 2011 Jan;38(1):83-95.

Prostate cancer characterization on MR images using FRACTAL features.

Lopes R(1), Ayache A, Makni N, Puech P, Villers A, Mordon S, Betrouni N.

Author information:

(1)Inserm, U703, Université Nord de France, 152 rue du Docteur Yersin, 59120 Loos,

CHRU Lille, France.

PURPOSE: Computerized detection of prostate cancer on T2-weighted MR images.

METHODS: The authors combined FRACTAL and multiFRACTAL features to perform

textural analysis of the images. The FRACTAL dimension was computed using the

Variance method; the multiFRACTAL spectrum was estimated by an adaptation of a

multifractional Brownian motion model. Voxels were labeled as tumor/nontumor via

nonlinear supervised classification. Two classification algorithms were tested:

Support vector machine (SVM) and AdaBoost.

RESULTS: Experiments were performed on images from 17 patients. Ground truth was

available from histological images. Detection and classification results

(sensitivity, specificity) were (83%, 91%) and (85%, 93%) for SVM and AdaBoost,


CONCLUSIONS: Classification using the authors' model combining FRACTAL and

multiFRACTAL features was more accurate than classification using classical

texture features (such as Haralick, wavelet, and Gabor filters). Moreover, the

method was more robust against signal intensity variations. Although the method

was only applied to T2 images, it could be extended to multispectral MR.

PMID: 21361178 [PubMed - indexed for MEDLINE]

94. Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Nov;82(5 Pt 1):051133. Epub 2010

Nov 29.

MultiFRACTALity of instantaneous normal modes at mobility edges.

Huang BJ(1), Wu TM.

Author information:

(1)Institute of Physics, National Chiao-Tung University, HsinChu, Taiwan 300,

Republic of China.

In terms of the multiFRACTAL analysis, we investigate the characteristics of the

instantaneous normal modes (INMs) at two mobility edges (MEs) of a simple fluid,

where the locations of the MEs in the INM spectrum were identified in a previous

work [B. J. Huang and T. M. Wu, Phys. Rev. E 79, 041105 (2009)]. The mass

exponents and the singularity spectrum of the INMs are obtained by the box-size

and system-size scalings under the typical average. The INM eigenvectors at a ME

exhibit a multiFRACTAL nature and the multiFRACTAL INMs at each ME yield the same

results in generalized FRACTAL dimensions and singularity spectrum. Our results

indicate that the singularity spectrum of the multiFRACTAL INMs agrees well with

that of the Anderson model at the critical disorder. This good agreement provides

numerical evidence for the universal multiFRACTALity at the

localization-delocalization transition. For the multiFRACTAL INMs, the

probability density function and the spatial correlation function of the squared

vibrational amplitudes are also calculated. The relation between the probability

density function and the singularity spectrum is examined numerically, so are the

relations between the critical exponents of the spatial correlation function and

the mass exponents of the multiFRACTAL INMs.

PMID: 21230463 [PubMed]

95. Front Physiol. 2012 Feb 7;2:123. doi: 10.3389/fphys.2011.00123. eCollection 2011.

Integrated central-autonomic multiFRACTAL complexity in the heart rate

variability of healthy humans.

Lin DC(1), Sharif A.

Author information:

(1)Department of Mechanical and Industrial Engineering, Ryerson University Toronto,

ON, Canada.

PURPOSE OF STUDY: The aim of this study was to characterize the central-autonomic

interaction underlying the multiFRACTALity in heart rate variability (HRV) of

healthy humans.

MATERIALS AND METHODS: Eleven young healthy subjects participated in two separate

~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt

(HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG)

and electrocardiogram (ECG) were collected and FRACTAL correlation of brain and

heart rate data was analyzed based on the idea of relative multiFRACTALity. The

FRACTAL correlation was further examined with the EEG, HRV spectral measures

using linear regression of two variables and principal component analysis (PCA)

to find clues for the physiological processing underlying the central influence


RESULTS: We report evidence of a central-autonomic FRACTAL correlation (CAFC)

where the HRV multiFRACTAL complexity varies significantly with the FRACTAL

correlation between the heart rate and brain data (P = 0.003). The linear

regression shows significant correlation between CAFC measure and EEG Beta band

spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is

significant correlation between CAFC measure and HRV LF component in the SUP

position (P = 0.04), whereas the correlation with the HRV HF component approaches

significance (P = 0.07). The correlation between CAFC measure and HRV spectral

measures in the UPR position is weak. The PCA results confirm these findings and

further imply multiple physiological processes underlying CAFC, highlighting the

importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in

the supine position.

DISCUSSION AND CONCLUSION: The findings of this work can be summarized into three

points: (i) Similar FRACTAL characteristics exist in the brain and heart rate

fluctuation and the change toward stronger FRACTAL correlation implies the change

toward more complex HRV multiFRACTALity. (ii) CAFC is likely contributed by

multiple physiological mechanisms, with its central elements mainly derived from

the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is

qualitatively different, with a more predominant central influence in the FRACTAL

HRV of the UPR position.

PMCID: PMC3277279

PMID: 22403548 [PubMed]

96. Microcirculation. 2011 Feb;18(2):136-51. doi: 10.1111/j.1549-8719.2010.00075.x.

MultiFRACTAL and lacunarity analysis of microvascular morphology and remodeling.

Gould DJ(1), Vadakkan TJ, Poché RA, Dickinson ME.

Author information:

(1)Department of Bioengineering, Rice University, Houston, Texas, USA.

OBJECTIVE: Classical measures of vessel morphology, including diameter and

density, are employed to study microvasculature in endothelial membrane labeled

mice. These measurements prove sufficient for some studies; however, they are

less well suited for quantifying changes in microcirculatory networks lacking

hierarchical structure. We demonstrate that automated multiFRACTAL analysis and

lacunarity may be used with classical methods to quantify microvascular


METHODS: Using multiFRACTAL analysis and lacunarity, we present an automated

extraction tool with a processing pipeline to characterize 2D representations of

3D microvasculature. We apply our analysis on four tissues and the hyaloid

vasculature during remodeling.

RESULTS: We found that the vessel networks analyzed have multiFRACTAL geometries

and that kidney microvasculature has the largest FRACTAL dimension and the lowest

lacunarity compared to microvasculature networks in the cortex, skin, and thigh

muscle. Also, we found that, during hyaloid remodeling, there were differences in

multiFRACTAL spectra reflecting the functional transition from a space filling

vasculature which nurtures the lens to a less dense vasculature as it regresses,

permitting unobstructed vision.

CONCLUSION: MultiFRACTAL analysis and lacunarity are valuable additions to

classical measures of vascular morphology and will have utility in future studies

of normal, developing, and pathological tissues.

© 2011 John Wiley & Sons Ltd.

PMCID: PMC3049800

PMID: 21166933 [PubMed - indexed for MEDLINE]

97. Brain Res Bull. 2011 Apr 5;84(6):359-75. doi: 10.1016/j.brainresbull.2010.12.005.

Epub 2010 Dec 13.

Comparison of FRACTAL and power spectral EEG features: effects of topography and

sleep stages.

Weiss B(1), Clemens Z, Bódizs R, Halász P.

Author information:

(1)Faculty of Information Technology, Pázmány Péter Catholic University, Práter u.

50/a, Budapest, Hungary.

FRACTAL nature of the human sleep EEG was revealed recently. In the literature

there are some attempts to relate FRACTAL features to spectral properties.

However, a comprehensive assessment of the relationship between FRACTAL and power

spectral measures is still missing. Therefore, in the present study we

investigated the relationship of monoFRACTAL and multiFRACTAL EEG measures (H and

ΔD) with relative band powers and spectral edge frequency across different sleep

stages and topographic locations. In addition we tested sleep stage

classification capability of these measures according to different channels. We

found that cross-correlations between FRACTAL and spectral measures as well as

between H and ΔD exhibit specific topographic and sleep stage-related

characteristics. Best sleep stage classifications were achieved by estimating

measure ΔD in temporal EEG channels both at group and individual levels,

suggesting that assessing multiFRACTALity might be an adequate approach for

compact modeling of brain activities.

Copyright © 2010 Elsevier Inc. All rights reserved.

PMID: 21147200 [PubMed - indexed for MEDLINE]

98. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:110-3. doi:


Wavelet leader based multiFRACTAL analysis of heart rate variability during

myocardial ischaemia.

Leonarduzzi RF(1), Schlotthauer G, Torres ME.

Author information:

(1)Lab. Signals and Nonlinear Dynamics, Faculty of Engineering, Universidad Nacional

de Entre Ríos, Argentina.

Heart rate variability is a non invasive and indirect measure of the autonomic

control of the heart. Therefore, alterations to this control system caused by

myocardial ischaemia are reflected in changes in the complex and irregular

fluctuations of this signal. MultiFRACTAL analysis is a well suited tool for the

analysis of this kind of fluctuations, since it gives a description of the

singular behavior of a signal. Recently, a new approach for multiFRACTAL analysis

was proposed, the wavelet leader based multiFRACTAL formalism, which shows

remarkable improvements over previous methods. In order to characterize and

detect ischaemic episodes, in this work we propose to perform a short-time

windowed wavelet leader based multiFRACTAL analysis. Our results suggest that

this new method provides appropriate indexes that could be used as a tool for the

detection of myocardial ischaemia.

PMID: 21095648 [PubMed - indexed for MEDLINE]

99. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:106-9. doi:


Methodology for multiFRACTAL analysis of heart rate variability: from LF/HF ratio

to wavelet leaders.

Abry P, Wendt H, Jaffard S, Helgason H, Goncalves P, Pereira E, Gharib C,

Gaucherand P, Doret M.

The present contribution aims at proposing a comprehensive and tutorial

introduction to the practical use of wavelet Leader based multiFRACTAL analysis

to study heart rate variability. First, the theoretical background is recalled.

Second, practical issues and pitfalls related to the selection of the scaling

range or statistical orders, minimal regularity, parabolic approximation of

spectrum and parameter estimation, are discussed. Third, multiFRACTAL analysis is

connected explicitly to other standard characterizations of heart rate

variability: (mono)FRACTAL analysis, Hurst exponent, spectral analysis and the

HF/LF ratio. This review is illustrated on real per partum fetal ECG data,

collected at an academic French public hospital, for both healthy fetuses and

fetuses suffering from acidosis.

PMID: 21095647 [PubMed - indexed for MEDLINE]

100. Am J Perinatol. 2011 Apr;28(4):259-66. doi: 10.1055/s-0030-1268713. Epub 2010 Nov


MultiFRACTAL analysis of fetal heart rate variability in fetuses with and without

severe acidosis during labor.

Doret M(1), Helgason H, Abry P, Goncalves P, Gharib C, Gaucherand P.

Author information:

(1)Hospices Civils de Lyon, Hôpital Femme-Mère-Enfant, service de

gynécologie-obstétrique, Bron, France.

We performed multiFRACTAL analysis of fetal heart rate (FHR) variability in

fetuses with and without acidosis during labor. MultiFRACTAL analysis was

performed on fetal electrocardiograms in 10-minute sliding windows within the

last 2 hours before delivery in 45 term fetuses divided in three groups according

to umbilical arterial pH and FHR pattern: group A had pH ≥7.30 and normal FHR,

group B had pH ≥7.30 and intermediate or abnormal FHR, and group C had acidosis

(pH ≤7.05) and intermediate or abnormal FHR. Six multiFRACTAL parameters were

compared using Wilcoxon rank sum test. MultiFRACTAL parameters were significantly

different between the three groups in the last 10 minutes before delivery (P

<0.05). Two parameters (H(min), zeta(2)) exhibited a significant difference 70

minutes before delivery, and one parameter (C(2)) was different 10 minutes before

birth (P <0.05). MultiFRACTAL parameters were significantly different in acidotic

and nonacidotic fetuses, independently from FHR pattern.

© Thieme Medical Publishers.

PMID: 21089007 [PubMed - indexed for MEDLINE]

101. Phys Med Biol. 2010 Oct 21;55(20):6279-97. doi: 10.1088/0031-9155/55/20/015. Epub

2010 Oct 6.

MultiFRACTAL analysis of heart rate variability and laser Doppler flowmetry

fluctuations:comparison of results from different numerical methods.

Humeau A(1), Buard B, Mahé G, Chapeau-Blondeau F, Rousseau D, Abraham P.

Author information:

(1)Laboratoire d'Ingénierie des Systèmes Automatisés, Université d'Angers, 62 avenue

Notre Dame du Lac, 49000 Angers, France.

To contribute to the understanding of the complex dynamics in the cardiovascular

system (CVS), the central CVS has previously been analyzed through multiFRACTAL

analyses of heart rate variability (HRV) signals that were shown to bring useful

contributions. Similar approaches for the peripheral CVS through the analysis of

laser Doppler flowmetry (LDF) signals are comparatively very recent. In this

direction, we propose here a study of the peripheral CVS through a multiFRACTAL

analysis of LDF fluctuations, together with a comparison of the results with

those obtained on HRV fluctuations simultaneously recorded. To perform these

investigations concerning the biophysics of the CVS, first we have to address the

problem of selecting a suitable methodology for multiFRACTAL analysis, allowing

us to extract meaningful interpretations on biophysical signals. For this

purpose, we test four existing methodologies of multiFRACTAL analysis. We also

present a comparison of their applicability and interpretability when implemented

on both simulated multiFRACTAL signals of reference and on experimental signals

from the CVS. One essential outcome of the study is that the multiFRACTAL

properties observed from both the LDF fluctuations (peripheral CVS) and the HRV

fluctuations (central CVS) appear very close and similar over the studied range

of scales relevant to physiology.

PMID: 20924134 [PubMed - indexed for MEDLINE]

102. J Chem Phys. 2010 Sep 28;133(12):124505. doi: 10.1063/1.3481099.

Molecular dynamics studies of ionically conducting glasses and ionic liquids:

wave number dependence of intermediate scattering function.

Habasaki J(1), Ngai KL.

Author information:

(1)Tokyo Institute of Technology, 4259 Nagatsuta-cho, Yokohama 226-8502, Japan.

Dynamical heterogeneity is a key feature to characterize both acceleration and

slowing down of the dynamics in interacting disordered materials. In the present

work, the heterogeneous ion dynamics in both ionically conducting glass and in

room temperature ionic liquids are characterized by the combination of the

concepts of Lévy distribution and multiFRACTALity. Molecular dynamics simulation

data of both systems are analyzed to obtain the fractional power law of the

k-dependence of the dynamics, which implies the Lévy distribution of length

scale. The multiFRACTALity of the motion and structures makes the system more

complex. Both contributions in the dynamics become separable by using g(k,t)

derived from the intermediate scattering function, F(s)(k,t). When the Lévy index

obtained from F(s)(k,t) is combined with FRACTAL dimension analysis of random

walks and multiFRACTAL analysis, all the spatial exponent controlling both fast

and slow dynamics are clarified. This analysis is generally applicable to other

complex interacting systems and is deemed beneficial for understanding their


PMID: 20886948 [PubMed]

103. Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Jul;82(1 Pt 1):011136. Epub 2010

Jul 27.

Detrending moving average algorithm for multiFRACTALs.

Gu GF(1), Zhou WX.

Author information:

(1)School of Business, East China University of Science and Technology, Shanghai

200237, China.

The detrending moving average (DMA) algorithm is a widely used technique to

quantify the long-term correlations of nonstationary time series and the

long-range correlations of FRACTAL surfaces, which contains a parameter θ

determining the position of the detrending window. We develop multiFRACTAL

detrending moving average (MFDMA) algorithms for the analysis of one-dimensional

multiFRACTAL measures and higher-dimensional multiFRACTALs, which is a

generalization of the DMA method. The performance of the one-dimensional and

two-dimensional MFDMA methods is investigated using synthetic multiFRACTAL

measures with analytical solutions for backward (θ=0), centered (θ=0.5), and

forward (θ=1) detrending windows. We find that the estimated multiFRACTAL scaling

exponent τ(q) and the singularity spectrum f(α) are in good agreement with the

theoretical values. In addition, the backward MFDMA method has the best

performance, which provides the most accurate estimates of the scaling exponents

with lowest error bars, while the centered MFDMA method has the worse

performance. It is found that the backward MFDMA algorithm also outperforms the

multiFRACTAL detrended fluctuation analysis. The one-dimensional backward MFDMA

method is applied to analyzing the time series of Shanghai Stock Exchange

Composite Index and its multiFRACTAL nature is confirmed.

PMID: 20866594 [PubMed]

104. Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Jun;81(6 Pt 2):066212. Epub 2010

Jun 18.

Generating a FRACTAL butterfly Floquet spectrum in a class of driven SU(2)

systems: eigenstate statistics.

Bandyopadhyay JN(1), Wang J, Gong J.

Author information:

(1)Department of Physics and Centre for Computational Science and Engineering,

National University of Singapore, Singapore 117542, Republic of Singapore.

The Floquet spectra of a class of driven SU(2) systems have been shown to display

butterfly patterns with multiFRACTAL properties. The implication of such critical

spectral behavior for the Floquet eigenstate statistics is studied in this work.

Following the methodologies for understanding the FRACTAL behavior of energy

eigenstates of time-independent systems on the Anderson transition point, we

analyze the distribution profile, the mean value, and the variance of the

logarithm of the inverse participation ratio of the Floquet eigenstates

associated with multiFRACTAL Floquet spectra. The results show that the Floquet

eigenstates also display FRACTAL behavior but with features markedly different

from those in time-independent Anderson-transition models. This motivated us to

propose random unitary matrix ensemble, called "power-law random banded unitary

matrix" ensemble, to illuminate the Floquet eigenstate statistics of critical

driven systems. The results based on the proposed random matrix model are

consistent with those obtained from our dynamical examples with or without

time-reversal symmetry.

PMID: 20866506 [PubMed]

105. J Opt Soc Am A Opt Image Sci Vis. 2010 Aug 1;27(8):1851-5. doi:


MultiFRACTAL zone plates.

Giménez F(1), Furlan WD, Calatayud A, Monsoriu JA.

Author information:

(1)I.U. Matemática Pura y Aplicada, Universidad Politécnica de Valencia, E-46022

Valencia, Spain.

We present multiFRACTAL zone plates (MFZPs) as what is to our knowledge a new

family of diffractive lenses whose structure is based on the combination of

FRACTAL zone plates (FZPs) of different orders. The typical result is a composite

of two FZPs with the central one having a first-order focal length f surrounded

by outer zones with a third-order focal length f. The focusing properties of

different members of this family are examined and compared with conventional

composite Fresnel zone plates. It is shown that MFZPs improve the axial

resolution and also give better performance under polychromatic illumination.

PMID: 20686590 [PubMed]

106. J Exp Psychol Gen. 2010 Aug;139(3):436-63. doi: 10.1037/a0019098.

Interaction-dominant dynamics in human cognition: beyond 1/f(alpha) fluctuation.

Ihlen EA(1), Vereijken B.

Author information:

(1)Human Movement Science Programme, Norwegian University of Science and Technology,

Trondheim, Norway.

It has been suggested that human behavior in general and cognitive performance in

particular emerge from coordination between multiple temporal scales. In this

article, we provide quantitative support for such a theory of

interaction-dominant dynamics in human cognition by using wavelet-based

multiFRACTAL analysis and accompanying multiplicative cascading process on the

response series of 4 different cognitive tasks: simple response, word naming,

choice decision, and interval estimation. Results indicated that the major

portion of these response series had multiplicative interactions between temporal

scales, visible as intermittent periods of large and irregular fluctuations

(i.e., a multiFRACTAL structure). Comparing 2 component-dominant models of

1/f(alpha) fluctuations in cognitive performance with the multiplicative

cascading process indicated that the multiFRACTAL structure could not be

replicated by these component-dominant models. Furthermore, a similar

multiFRACTAL structure was shown to be present in a model of self-organized

criticality in the human nervous system, similar to a spatial extension of the

multiplicative cascading process. These results illustrate that a wavelet-based

multiFRACTAL analysis and the multiplicative cascading process form an

appropriate framework to characterize interaction-dominant dynamics in human

cognition. This new framework goes beyond the identification of 1/f(alpha) power

laws and non-gaussian distributions in response series as used in previous

studies. The present article provides quantitative support for a paradigm shift

toward interaction-dominant dynamics in human cognition.

2010 APA, all rights reserved

PMID: 20677894 [PubMed - indexed for MEDLINE]

107. Med Phys. 2010 Jun;37(6):2827-36.

Generalized FRACTAL dimensions of laser Doppler flowmetry signals recorded from

glabrous and nonglabrous skin.

Buard B(1), Mahé G, Chapeau-Blondeau F, Rousseau D, Abraham P, Humeau A.

Author information:

(1)Groupe ESAIP, 18 rue du 8 mai 1945, BP 80022, 49180 Saint Barthélémy d'Anjou

Cedex, France.

PURPOSE: The technique of laser Doppler flowmetry (LDF) is commonly used to have

a peripheral view of the cardiovascular system. To better understand the

microvascular perfusion signals, the authors herein propose to analyze and

compare the complexity of LDF data recorded simultaneously in glabrous and

nonglabrous skin. Glabrous zones are physiologically different from the others

partly due to the presence of a high density of arteriovenous anastomoses.

METHODS: For this purpose, a multiFRACTAL analysis based on the partition

function and generalized FRACTAL dimensions computation is proposed. The LDF data

processed are recorded simultaneously on the right and left forearms and on the

right and left hand palms of healthy subjects. The signal processing method is

first tested on a multiFRACTAL binomial measure. The generalized FRACTAL

dimensions of the normalized LDF signals are then estimated. Furthermore, for the

first time, the authors estimate the generalized FRACTAL dimensions from a range

of scales corresponding to factors influencing the microcirculation flow

(cardiac, respiratory, myogenic, neurogenic, and endothelial).

RESULTS: Different multiFRACTAL behaviors are found between normalized LDF

signals recorded in the forearms and in the hand palms of healthy subjects. Thus,

the variations in the estimated generalized FRACTAL dimensions of LDF signals

recorded in the hand palms are higher than those of LDF signals recorded in the

forearms. This shows that LDF signals recorded in glabrous zones may be more

complex than those recorded in nonglabrous zones. Furthermore, the results show

that the complexity in the hand palms could be more important at scales

corresponding to the myogenic control mechanism than at the other studied scales.

CONCLUSIONS: These findings suggest that the multiFRACTALity of the normalized

LDF signals is different on glabrous and nonglabrous skin. This difference may

rely on the density of arteriovenous anastomoses and differences in nerve supply

or biochemical properties. This study provides useful information for an in-depth

understanding of LDF data and a more detailed knowledge of the peripheral

cardiovascular system.

PMID: 20632594 [PubMed - indexed for MEDLINE]

108. Chaos. 2010 Jun;20(2):023121. doi: 10.1063/1.3427639.

Common multiFRACTALity in the heart rate variability and brain activity of

healthy humans.

Lin DC(1), Sharif A.

Author information:

(1)Department of Mechanical and Industrial Engineering, Ryerson University, Toronto,

Ontario M5B 2K3, Canada.

The influence from the central nervous system on the human multiFRACTAL heart

rate variability (HRV) is examined under the autonomic nervous system

perturbation induced by the head-up-tilt body maneuver. We conducted the

multiFRACTAL factorization analysis to factor out the common multiFRACTAL factor

in the joint fluctuation of the beat-to-beat heart rate and

electroencephalography data. Evidence of a central link in the multiFRACTAL HRV

was found, where the transition towards increased (decreased) HRV multiFRACTAL

complexity is associated with a stronger (weaker) multiFRACTAL correlation

between the central and autonomic nervous systems.

(c) 2010 American Institute of Physics.

PMID: 20590317 [PubMed - indexed for MEDLINE]

109. Genet Mol Res. 2010 May 25;9(2):949-65. doi: 10.4238/vol9-2gmr756.

The Caenorhabditis elegans genome: a multiFRACTAL analysis.

Vélez PE(1), Garreta LE, Martínez E, Díaz N, Amador S, Tischer I, Gutiérrez JM,

Moreno PA.

Author information:

(1)Departamento de Biología, Universidad del Cauca, Popayán, Colombia.

The Caenorhabditis elegans genome has several regular and irregular

characteristics in its nucleotide composition; these are observed within and

between chromosomes. To study these particularities, we carried out a

multiFRACTAL analysis, which requires a large number of exponents to characterize

scaling properties. We looked for a relationship between the genetic information

content of the chromosomes and multiFRACTAL parameters and found less

multiFRACTALity compared to the human genome. Differences in multiFRACTALity

among chromosomes and in regions of chromosomes, and two group averages of

chromosome regions were observed. All these differences were mainly dependent on

differences in the contents of repetitive DNA. Based on these properties, we

propose a nonlinear model for the structure of the C. elegans genome, with some

biological implications. These results suggest that examining differences in

multiFRACTALity is a viable approach for measuring local variations of genomic

information contents along chromosomes. This approach could be extended to other

genomes in order to characterize structural and functional regions of


PMID: 20506082 [PubMed - indexed for MEDLINE]

110. Hum Mov Sci. 2010 Jun;29(3):449-63. doi: 10.1016/j.humov.2009.08.004.

Data series embedding and scale invariant statistics.

Michieli I(1), Medved B, Ristov S.

Author information:

(1)Electronic Department, Ruder Bosković Institute, Zagreb 10000, Croatia.

Data sequences acquired from bio-systems such as human gait data, heart rate

interbeat data, or DNA sequences exhibit complex dynamics that is frequently

described by a long-memory or power-law decay of autocorrelation function. One

way of characterizing that dynamics is through scale invariant statistics or

"FRACTAL-like" behavior. For quantifying scale invariant parameters of

physiological signals several methods have been proposed. Among them the most

common are detrended fluctuation analysis, sample mean variance analyses, power

spectral density analysis, R/S analysis, and recently in the realm of the

multiFRACTAL approach, wavelet analysis. In this paper it is demonstrated that

embedding the time series data in the high-dimensional pseudo-phase space reveals

scale invariant statistics in the simple fashion. The procedure is applied on

different stride interval data sets from human gait measurements time series

(Physio-Bank data library). Results show that introduced mapping adequately

separates long-memory from random behavior. Smaller gait data sets were analyzed

and scale-free trends for limited scale intervals were successfully detected. The

method was verified on artificially produced time series with known scaling

behavior and with the varying content of noise. The possibility for the method to

falsely detect long-range dependence in the artificially generated short range

dependence series was investigated.

(c) 2009 Elsevier B.V. All rights reserved.

PMID: 20435364 [PubMed - indexed for MEDLINE]

111. Zh Obshch Biol. 2010 Mar-Apr;71(2):115-30.

[FRACTAL aspects of the taxic diversity].

[Article in Russian]

Gelashvili DB, Iakimov VN, Iudin DI, Rozenberg GS, Solntsev LA, Saksonov SV,

Snegireva MS.

Two approaches are suggested for describing taxic diversity as a FRACTAL, or

self-similar, object. One of them called "sampling approach" is based on

necessity of taking into account the sampling process and on proceeding from the

real ecological practice of exploration of the community structure. Verification

of this approach is fulfilled using a multiFRACTAL analysis of the generic

diversity of vascular plants of the National Park "Samarskaya Luka". The

previously revealed regularities of multiFRACTAL spectrum of the species

structure of communities are shown to be true to an extent for the generic

structure, as well. The second approach called "topological" one is based on an

abstract representation of the results of evolutionary process in form of

phylogenetic tree characterized by a non-trivial topological structure.

Approbations of this approach is fulfilled by analysis of topological structure

of the taxonomic tree of the class Mammalia, our calculations indicating FRACTAL

properties of its graph. These results make it reasonable to suppose that the

taxic diversity, as a replica of the real diversity of the FRACTALly organized

organic world, also possesses self-similar (FRACTAL) structure.

PMID: 20391749 [PubMed - indexed for MEDLINE]

112. Water Sci Technol. 2010;61(8):2113-8. doi: 10.2166/wst.2010.135.

Comparative analysis of time-scaling properties about water pH in Poyang Lake

Inlet and Outlet on the basis of FRACTAL methods.

Shi K(1), Liu CQ, Huang ZW, Zhang B, Su Y.

Author information:

(1)College of Biology and Environmental Sciences, Jishou University, Jishou Hunan

416000, China.

Detrended fluctuation analysis (DFA) and multiFRACTAL methods are applied to the

time-scaling properties analysis of water pH series in Poyang Lake Inlet and

Outlet in China. The results show that these pH series are characterised by

long-term memory and multiFRACTAL scaling, and these characteristics have obvious

differences between the Lake Inlet and Outlet. The comparison results suggest

that monoFRACTAL and multiFRACTAL parameters can be quantitative dynamical

indexes reflecting the capability of anti-acidification of Poyang Lake.

Furthermore, we investigated the frequency-size distribution of pH series in

Poyang Lake Inlet and Outlet. Our findings suggest that water pH is an example of

a self-organised criticality (SOC) process. The results show that it is different

SOC behaviours that result in the differences of power-law relations between pH

series in Poyang Lake Inlet and Outlet. This work can be helpful to improvement

of modelling of lake water quality.

PMID: 20389010 [PubMed - indexed for MEDLINE]

113. Proc Natl Acad Sci U S A. 2010 Apr 27;107(17):7640-5. doi:

10.1073/pnas.0912983107. Epub 2010 Apr 12.

MultiFRACTAL network generator.

Palla G(1), Lovász L, Vicsek T.

Author information:

(1)Statistical and Biological Physics Research Group of the Hungarian Academy of

Sciences, Eötvös University, Budapest, Hungary.

We introduce a new approach to constructing networks with realistic features. Our

method, in spite of its conceptual simplicity (it has only two parameters) is

capable of generating a wide variety of network types with prescribed statistical

properties, e.g., with degree or clustering coefficient distributions of various,

very different forms. In turn, these graphs can be used to test hypotheses or as

models of actual data. The method is based on a mapping between suitably chosen

singular measures defined on the unit square and sparse infinite networks. Such a

mapping has the great potential of allowing for graph theoretical results for a

variety of network topologies. The main idea of our approach is to go to the

infinite limit of the singular measure and the size of the corresponding graph

simultaneously. A very unique feature of this construction is that with the

increasing system size the generated graphs become topologically more structured.

We present analytic expressions derived from the parameters of the--to be

iterated--initial generating measure for such major characteristics of graphs as

their degree, clustering coefficient, and assortativity coefficient

distributions. The optimal parameters of the generating measure are determined

from a simple simulated annealing process. Thus, the present work provides a tool

for researchers from a variety of fields (such as biology, computer science,

biology, or complex systems) enabling them to create a versatile model of their

network data.

PMCID: PMC2867894

PMID: 20385847 [PubMed - indexed for MEDLINE]

114. Neurology. 2010 Apr 6;74(14):1102-7. doi: 10.1212/WNL.0b013e3181d7d8b4.

FRACTAL analysis of retinal vessels suggests that a distinct vasculopathy causes

lacunar stroke.

Doubal FN(1), MacGillivray TJ, Patton N, Dhillon B, Dennis MS, Wardlaw JM.

Author information:

(1)Division of Clinical Neurosciences, University of Edinburgh, Western General

Hospital, Edinburgh, UK.

Comment in

Neurology. 2010 Apr 6;74(14):1088-9.

OBJECTIVES: Lacunar strokes account for 25% of all ischemic strokes and may

represent the cerebral manifestation of a systemic small vessel vasculopathy of

unknown etiology. Altered retinal vessel FRACTAL dimensions may act as a

surrogate marker for diseased cerebral vessels. We used a cross-sectional study

to investigate FRACTAL properties of retinal vessels in lacunar stroke.

METHODS: We recruited patients presenting with lacunar stroke and patients with

minor cortical stroke as controls. All patients were examined by a stroke expert

and had MRI at presentation. Digital retinal photographs were taken of both eyes.

MonoFRACTAL and multiFRACTAL analyses were performed with custom-written

semiautomated software.

RESULTS: We recruited 183 patients. Seventeen were excluded owing to poor

photographic quality, leaving 166 patients (86 with lacunar and 80 with cortical

stroke). The mean age was 67.3 years (SD 11.5 years). The patients with lacunar

stroke were younger but the prevalence of diabetes, hypertension, and white

matter hyperintensities did not differ between the groups. The mean Dbox

(monoFRACTAL dimension) was 1.42 (SD 0.02), the mean D0 (multiFRACTAL dimension)

1.67 (SD 0.03). With multivariate analysis, decreased Dbox and D0 (both

representing decreased branching complexity) were associated with increasing age

and lacunar stroke subtype after correcting for hypertension, diabetes, stroke

severity, and white matter hyperintensity scores.

CONCLUSIONS: Lacunar stroke subtype and increasing age are associated with

decreased FRACTAL dimensions, suggesting a loss of branching complexity. Further

studies should concentrate on longitudinal associations with other manifestations

of cerebral small vessel disease.

PMCID: PMC2865776

PMID: 20368631 [PubMed - indexed for MEDLINE]

115. Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Feb;81(2 Pt 2):026102. Epub 2010

Feb 8.

Hierarchical multiFRACTAL representation of symbolic sequences and application to

human chromosomes.

Provata A(1), Katsaloulis P.

Author information:

(1)Institute of Physical Chemistry, National Center for Scientific Research

Demokritos, 15310 Athens, Greece.

The two-dimensional density correlation matrix is constructed for symbolic

sequences using contiguous segments of arbitrary size. The multiFRACTAL spectrum

obtained from this matrix motif is shown to characterize the correlations in the

symbolic sequences. This method is applied to entire human chromosomes, shuffled

human chromosomes, reconstructed human genomic sequences and to artificial random

sequences. It is shown that all human chromosomes have common characteristics in

their multiFRACTAL spectrum and deviate substantially from random and

uncorrelated sequences of the same size. Small deviations are observed between

the longer and the shorter chromosomes, especially for the higher (in absolute

values) statistical moments. The correlations are crucial for the form of the

multiFRACTAL spectrum; surrogate shuffled chromosomes present randomlike

spectrum, distinctly different from the actual chromosomes. Analytical approaches

based on hierarchical superposition of tensor products show that retaining pair

correlations in the sequences leads to a closer representation of the genomic

multiFRACTAL spectra, especially in the region of negative exponents, due to the

underrepresentation of various functional units (such as the cytosine-guanine CG

combination and its complementary GC complex). Retaining higher-order

correlations in the construction of the tensor products is a way to approach

closer the structure of the multiFRACTAL spectra of the actual genomic sequences.

This hierarchical approach is generic and is applicable to other correlated

symbolic sequences.

PMID: 20365626 [PubMed - indexed for MEDLINE]

116. Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Dec;80(6 Pt 1):061126. Epub 2009

Dec 18.

MultiFRACTAL analysis of light scattering-intensity fluctuations.

Shayeganfar F(1), Jabbari-Farouji S, Movahed MS, Jafari GR, Tabar MR.

Author information:

(1)Department of Physics, Sharif University of Technology, PO Box 11365-9161,

Tehran, Iran.

We provide a simple interpretation of non-Gaussian nature of the light

scattering-intensity fluctuations from an aging colloidal suspension of Laponite

using the multiplicative cascade model, Markovian method, and volatility

correlations. The cascade model and Markovian method enable us to reproduce most

of recent empirical findings: long-range volatility correlations and non-Gaussian

statistics of intensity fluctuations. We provide evidence that the intensity

increments Deltax(tau)=I(t+tau)-I(t), upon different delay time scales tau, can

be described as a Markovian process evolving in tau. Thus, the tau dependence of

the probability density function p(Deltax,tau) on the delay time scale tau can be

described by a Fokker-Planck equation. We also demonstrate how drift and

diffusion coefficients in the Fokker-Planck equation can be estimated directly

from the data.

PMID: 20365137 [PubMed - indexed for MEDLINE]

117. Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Nov;80(5 Pt 2):056302. Epub 2009

Nov 6.

Large deviation theory for coin tossing and turbulence.

Chakraborty S(1), Saha A, Bhattacharjee JK.

Author information:

(1)Neils Bohr Institute, Niels Bohr International Academy, Blegdamsvej 17, 2100

Copenhagen varphi, Denmark.

Large deviations play a significant role in many branches of nonequilibrium

statistical physics. They are difficult to handle because their effects, though

small, are not amenable to perturbation theory. Even the Gaussian model, which is

the usual initial step for most perturbation theories, fails to be a starting

point while discussing intermittency in fluid turbulence, where large deviations

dominate. Our contention is: in the large deviation theory, the central role is

played by the distribution associated with the tossing of a coin and the simple

coin toss is the "Gaussian model" of problems where rare events play significant

role. We illustrate this by applying it to calculate the multiFRACTAL exponents

of the order structure factors in fully developed turbulence.

PMID: 20365068 [PubMed - indexed for MEDLINE]

118. Physiol Meas. 2010 Apr;31(4):565-80. doi: 10.1088/0967-3334/31/4/008. Epub 2010

Mar 12.

MultiFRACTAL and nonlinear assessment of autonomous nervous system response

during transient myocardial ischaemia.

Magrans R(1), Gomis P, Caminal P, Wagner G.

Author information:

(1)Departament d'Enginyeria de Sistemes, Universitat Politècnica de Catalunya,

Barcelona, Spain.

We assess autonomic nervous system response during prolonged percutaneous

transluminal coronary angioplasty (PTCA) using heart rate variability analysis

with multiFRACTAL indices. These indices are used to evaluate the effects of the

PTCA procedures at different arteries and locations. A total of 55 patients from

the Staff3 database, with no prior history of myocardial infarction, were

included in the study. The indices increased significantly during the transient

ischaemia and reperfusion periods, indicating an increase in nonlinear

multiFRACTAL characteristics and a change in temporal correlations in heartbeat

fluctuations. This indicates that significant multiFRACTAL and nonlinear complex

reactions in the autonomic control of the heart rate occurred during coronary

artery occlusions and suggests that the multiFRACTAL indices may be a promising

nonlinear technique for evaluating autonomic nervous system response in the

presence of transient myocardial ischaemia.

PMID: 20228447 [PubMed - indexed for MEDLINE]

119. Chaos. 2009 Dec;19(4):043129. doi: 10.1063/1.3273187.

Computing the multiFRACTAL spectrum from time series: an algorithmic approach.

Harikrishnan KP(1), Misra R, Ambika G, Amritkar RE.

Author information:

(1)Department of Physics, The Cochin College, Cochin 682 002, India.

We show that the existing methods for computing the f(alpha) spectrum from a time

series can be improved by using a new algorithmic scheme. The scheme relies on

the basic idea that the smooth convex profile of a typical f(alpha) spectrum can

be fitted with an analytic function involving a set of four independent

parameters. While the standard existing schemes [P. Grassberger et al., J. Stat.

Phys. 51, 135 (1988); A. Chhabra and R. V. Jensen, Phys. Rev. Lett. 62, 1327

(1989)] generally compute only an incomplete f(alpha) spectrum (usually the top

portion), we show that this can be overcome by an algorithmic approach, which is

automated to compute the D(q) and f(alpha) spectra from a time series for any

embedding dimension. The scheme is first tested with the logistic attractor with

known f(alpha) curve and subsequently applied to higher-dimensional cases. We

also show that the scheme can be effectively adapted for analyzing practical time

series involving noise, with examples from two widely different real world

systems. Moreover, some preliminary results indicating that the set of four

independent parameters may be used as diagnostic measures are also included.

PMID: 20059225 [PubMed - indexed for MEDLINE]

120. Front Physiol. 2010 Oct 14;1:12. doi: 10.3389/fphys.2010.00012. eCollection 2010.

FRACTAL physiology and the fractional calculus: a perspective.

West BJ.

Author information:

Information Science Directorate, U.S. Army Research Office Research Triangle

Park, NC, USA.

This paper presents a restricted overview of FRACTAL Physiology focusing on the

complexity of the human body and the characterization of that complexity through

FRACTAL measures and their dynamics, with FRACTAL dynamics being described by the

fractional calculus. Not only are anatomical structures (Grizzi and

Chiriva-Internati, 2005), such as the convoluted surface of the brain, the lining

of the bowel, neural networks and placenta, FRACTAL, but the output of dynamical

physiologic networks are FRACTAL as well (Bassingthwaighte et al., 1994). The

time series for the inter-beat intervals of the heart, inter-breath intervals and

inter-stride intervals have all been shown to be FRACTAL and/or multiFRACTAL

statistical phenomena. Consequently, the FRACTAL dimension turns out to be a

significantly better indicator of organismic functions in health and disease than

the traditional average measures, such as heart rate, breathing rate, and stride

rate. The observation that human physiology is primarily FRACTAL was first made

in the 1980s, based on the analysis of a limited number of datasets. We review

some of these phenomena herein by applying an allometric aggregation approach to

the processing of physiologic time series. This straight forward method

establishes the scaling behavior of complex physiologic networks and some dynamic

models capable of generating such scaling are reviewed. These models include

simple and fractional random walks, which describe how the scaling of correlation

functions and probability densities are related to time series data.

Subsequently, it is suggested that a proper methodology for describing the

dynamics of FRACTAL time series may well be the fractional calculus, either

through the fractional Langevin equation or the fractional diffusion equation. A

fractional operator (derivative or integral) acting on a FRACTAL function, yields

another FRACTAL function, allowing us to construct a fractional Langevin equation

to describe the evolution of a FRACTAL statistical process. Control of

physiologic complexity is one of the goals of medicine, in particular,

understanding and controlling physiological networks in order to ensure their

proper operation. We emphasize the difference between homeostatic and allometric

control mechanisms. Homeostatic control has a negative feedback character, which

is both local and rapid. Allometric control, on the other hand, is a relatively

new concept that takes into account long-time memory, correlations that are

inverse power law in time, as well as long-range interactions in complex

phenomena as manifest by inverse power-law distributions in the network variable.

We hypothesize that allometric control maintains the FRACTAL character of erratic

physiologic time series to enhance the robustness of physiological networks.

Moreover, allometric control can often be described using the fractional calculus

to capture the dynamics of complex physiologic networks.

PMCID: PMC3059975

PMID: 21423355 [PubMed]

121. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:1808-11. doi:


MultiFRACTAL characterization of the autonomous nervous system during prolonged

coronary artery occlusion.

Magrans R(1), Gomis P, Caminal P, Wagner G.

Author information:

(1)Dept. ESAII, Universitat Politècnica de Catalunya (UPC), and CIBER de

Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), c/ Pau Gargallo 5,

08028, Barcelona, Spain.

We assess the autonomic nervous system response during prolonged percutaneous

transluminal coronary angioplasty (PTCA) by heart rate variability analysis using

multiFRACTAL indices. These indices are also used to evaluate the effects of the

PTCA at different arteries. The indices augmented significantly during transient

ischemia and reperfusion periods indicating an increase of multiFRACTAL degree

and a decrease of the long-range dependence on heartbeat fluctuations. This

indicates that significant multiFRACTAL complex reactions of autonomic control of

the heart rate occurred during coronary artery occlusions. Key words:

multiFRACTAL analysis, heartbeat fluctuations, myocardial ischemia, coronary

artery occlusion.

PMID: 19964563 [PubMed - indexed for MEDLINE]

122. Clin Physiol Funct Imaging. 2010 Jan;30(1):43-50. doi:

10.1111/j.1475-097X.2009.00902.x. Epub 2009 Oct 2.

Influence of smoking abstinence and nicotine replacement therapy on heart rate

and QT time-series.

Lewis MJ(1), Balaji G, Dixon H, Syed Y, Lewis KE.

Author information:

(1)School of Engineering, Swansea University, Wales, UK.

SUMMARY: Many smokers attempt to quit without using nicotine replacement therapy

(NRT) or pharmacotherapy, i.e. 'cold-turkey'. The cardiac implications of this

are important but are incompletely understood. Previous studies have associated

smoking cessation with improvements in heart rate (HR) and its variability, but

its influence on QT time-series is unclear. Furthermore, the relative influence

on these parameters of acute nicotine withdrawal and of NRT has not been

adequately compared. Additional insight might come from analysing the dynamic

(e.g. FRACTAL) properties of electrocardiographic data during different levels of

nicotine exposure. We examined the influence of smoking cessation, during

cold-turkey and subsequent NRT, on HR and QT time-series during 30 days of

smoking abstinence. Seven smokers and sixteen healthy non-smokers received ECG

monitoring at baseline (Day 0). Smokers subsequently refrained from smoking

without using NRT for 24 h, and then received NRT for 29 days. ECG monitoring was

repeated at Days 1, 7, 30. Following smoking cessation we observed that: HR and

rate-corrected QT were both reduced, heart rate variability (HRV) increased

(improved), and QT variability index (QTVI) showed signs of improvement (trend

only). Improvements in HR and QT were maintained throughout NRT use, whilst

improvements in HRV and QTVI were sustained for at least the early stages of NRT.

The dynamic (multiFRACTAL) properties of HR and QT were similar for smokers and

non-smokers, and were unchanged by smoking abstinence or NRT. Our results provide

tentative evidence that electrocardiographic improvements during a cold-turkey

smoking quit attempt (acute nicotine withdrawal) are maintained during NRT


PMID: 19799615 [PubMed - indexed for MEDLINE]

123. Dokl Biol Sci. 2009 Jul-Aug;427:374-7.

MultiFRACTAL analysis of the species structure of helminthic communities of small

mammals in the Samarskaya Luka.

Gelashvili DB(1), Iudin DI, Solntsev LA, Snegireva MS, Rozenberg GS, Evlanov IA,

Kirillova NJ, Kirillov AA.

Author information:

(1)Nizhni Novgorod State University, pr Gagarina 23, Nizhni Novgorod, 603950 Russia.

PMID: 19760887 [PubMed - indexed for MEDLINE]

124. Phys Rev Lett. 2009 Jun 19;102(24):244102. Epub 2009 Jun 17.

Butterfly Floquet spectrum in driven SU(2) systems.

Wang J(1), Gong J.

Author information:

(1)Temasek Laboratories, National University of Singapore, 117542, Singapore.

The Floquet spectrum of a class of driven SU(2) systems is shown to display a

butterfly pattern with multiFRACTAL properties. The level crossing between

Floquet states of the same parity or different parities is studied. The results

are relevant to studies of FRACTAL statistics, quantum chaos, coherent

destruction of tunneling, and the validity of mean-field descriptions of

Bose-Einstein condensates.

PMID: 19659010 [PubMed]

125. J Exp Psychol Hum Percept Perform. 2009 Aug;35(4):1072-91. doi: 10.1037/a0015017.

Spatiotemporal symmetry and multiFRACTAL structure of head movements during

dyadic conversation.

Ashenfelter KT(1), Boker SM, Waddell JR, Vitanov N.

Author information:

(1)U.S. Census Bureau, USA.

This study examined the influence of sex, social dominance, and context on

motion-tracked head movements during dyadic conversations. Windowed

cross-correlation analyses found high peak correlation between conversants' head

movements over short ( approximately 2-s) intervals and a high degree of

nonstationarity. Nonstationarity in head movements was found to be positively

related to the number of men in a conversation. Surrogate data analysis

offsetting the conversants' time series by a large lag was unable to reject the

null hypothesis that the observed high peak correlations were unrelated to

short-term coordination between conversants. One way that high peak correlations

could be observed when 2 time series are offset by a large time lag is for each

time series to exhibit self-similarity over a range of scales. MultiFRACTAL

analysis found small-scale fluctuations to be persistent, tau(q) < 0.5, and

large-scale fluctuations to be antipersistent, tau(q) > 0.5. These results are

consistent with a view that symmetry is formed between conversants over short

intervals and that this symmetry is broken at longer, irregular intervals.

PMID: 19653750 [PubMed - indexed for MEDLINE]

126. J Neurosci Methods. 2009 Dec 15;185(1):116-24. doi:

10.1016/j.jneumeth.2009.07.027. Epub 2009 Jul 29.

Spatio-temporal analysis of monoFRACTAL and multiFRACTAL properties of the human

sleep EEG.

Weiss B(1), Clemens Z, Bódizs R, Vágó Z, Halász P.

Author information:

(1)Faculty of Information Technology, Pázmány Péter Catholic University, Budapest,


FRACTALity is a common property in nature. It can also be observed in time series

representing dynamics of complex processes. Therefore FRACTAL analysis could be a

useful tool to describe the dynamics of brain electrical activities in

physiological and pathological conditions. In this study, we carried out a

spatio-temporal analysis of monoFRACTAL and multiFRACTAL properties of

whole-night sleep EEG recordings. We estimated the Hurst exponent (H) and the

range of FRACTAL spectra (dD) in 10 healthy subjects. We found higher H values

during NREM4 compared to NREM2 and REM in all electrodes. Measure dD showed an

opposite trend. Differences of H and dD between NREM2 and REM reached

significancy at circumscribed regions only. Our results contribute to a deeper

understanding of the FRACTAL nature of brain electrical activities and may have

implications for automatic classification of sleep stages.

PMID: 19646476 [PubMed - indexed for MEDLINE]

127. Eur Biophys J. 2009 Oct;38(8):1115-25. doi: 10.1007/s00249-009-0516-z. Epub 2009

Jul 18.

FRACTAL analysis and ionic dependence of endocytotic membrane activity of human

breast cancer cells.

Krasowska M(1), Grzywna ZJ, Mycielska ME, Djamgoz MB.

Author information:

(1)Division of Cell and Molecular Biology, Neuroscience Solutions to Cancer Research

Group, Imperial College London, Sir Alexander Fleming Building, South Kensington

Campus, London SW7 2AZ, UK.

The endocytic membrane activities of two human breast cancer cell lines

(MDA-MB-231 and MCF-7) of strong and weak metastatic potential, respectively,

were studied in a comparative approach. Uptake of horseradish peroxidase was used

to follow endocytosis. Dependence on ionic conditions and voltage-gated sodium

channel (VGSC) activity were characterized. FRACTAL methods were used to analyze

quantitative differences in vesicular patterning. Digital quantification showed

that MDA-MB-231 cells took up more tracer (i.e., were more endocytic) than MCF-7

cells. For the former, uptake was totally dependent on extracellular Na(+) and

partially dependent on extracellular and intracellular Ca(2+) and protein kinase

activity. Analyzing the generalized FRACTAL dimension (D(q )) and its Legendre

transform f(alpha) revealed that under control conditions, all multiFRACTAL

parameters determined had values greater for MDA-MB-231 compared with MCF-7

cells, consistent with endocytic/vesicular activity being more developed in the

strongly metastatic cells. All FRACTAL parameters studied were sensitive to the

VGSC blocker tetrodotoxin (TTX). Some of the parameters had a "simple" dependence

on VGSC activity, if present, whereby pretreatment with TTX reduced the values

for the MDA-MB-231 cells and eliminated the differences between the two cell

lines. For other parameters, however, there was a "complex" dependence on VGSC

activity. The possible physical/physiological meaning of the mathematical

parameters studied and the nature of involvement of VGSC activity in control of

endocytosis/secretion are discussed.

PMID: 19618177 [PubMed - indexed for MEDLINE]

128. Chaos. 2009 Jun;19(2):028507. doi: 10.1063/1.3152223.

MultiFRACTALity and heart rate variability.

Sassi R(1), Signorini MG, Cerutti S.

Author information:

(1)Dipartimento di Tecnologie dell'Informazione, Universita degli studi di Milano,

via Bramante 65, 26013 Crema, Italy.

In this paper, we participate to the discussion set forth by the editor of Chaos

for the controversy, "Is the normal heart rate chaotic?" Our objective was to

debate the question, "Is there some more appropriate term to characterize the

heart rate variability (HRV) fluctuations?" We focused on the approximately 24 h

RR series prepared for this topic and tried to verify with two different

techniques, generalized structure functions and wavelet transform modulus maxima,

if they might be described as being multiFRACTAL. For normal and congestive heart

failure subjects, the h(q) exponents showed to be decreasing for increasing q

with both methods, as it should be for multiFRACTAL signals. We then built 40

surrogate series to further verify such hypothesis. For most of the series

(approximately 75%-80% of cases) multiFRACTALity stood the test of the surrogate

data employed. On the other hand, series coming from patients in atrial

fibrillation showed a small, if any, degree of multiFRACTALity. The population

analyzed is too small for definite conclusions, but the study supports the use of

multiFRACTAL series to model HRV. Also it suggests that the regulatory action of

autonomous nervous system might play a role in the observed multiFRACTALity.

PMID: 19566282 [PubMed - indexed for MEDLINE]

129. Chaos. 2009 Jun;19(2):028503. doi: 10.1063/1.3152006.

Normal heartbeat series are nonchaotic, nonlinear, and multiFRACTAL: new evidence

from semiparametric and parametric tests.

Baillie RT(1), Cecen AA, Erkal C.

Author information:

(1)Departments of Economics and Finance, Michigan State University, East Lansing,

Michigan 48824, USA.

We present new evidence that normal heartbeat series are nonchaotic, nonlinear,

and multiFRACTAL. In addition to considering the largest Lyapunov exponent and

the correlation dimension, the results of the parametric and semiparametric

estimation of the long memory parameter (long-range dependence) unambiguously

reveal that the underlying process is nonstationary, multiFRACTAL, and has strong


PMID: 19566278 [PubMed - indexed for MEDLINE]

130. Chaos. 2009 Jun;19(2):028501. doi: 10.1063/1.3156832.

Introduction to controversial topics in nonlinear science: is the normal heart

rate chaotic?

Glass L.

Author information:

Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada.

In June 2008, the editors of Chaos decided to institute a new section to appear

from time to time that addresses timely and controversial topics related to

nonlinear science. The first of these deals with the dynamical characterization

of human heart rate variability. We asked authors to respond to the following

questions: Is the normal heart rate chaotic? If the normal heart rate is not

chaotic, is there some more appropriate term to characterize the fluctuations

(e.g., scaling, FRACTAL, multiFRACTAL)? How does the analysis of heart rate

variability elucidate the underlying mechanisms controlling the heart rate? Do

any analyses of heart rate variability provide clinical information that can be

useful in medical assessment (e.g., in helping to assess the risk of sudden

cardiac death)? If so, please indicate what additional clinical studies would be

useful for measures of heart rate variability to be more broadly accepted by the

medical community. In addition, as a challenge for analysis methods, PhysioNet

[A. L. Goldberger et al., "PhysioBank, PhysioToolkit, and PhysioNet: Components

of a new research resource for complex physiologic signals," Circulation 101,

e215-e220 (2000)] provided data sets from 15 patients of whom five were normal,

five had heart failure, and five had atrial fibrillation

( This introductory essay summarizes

the main issues and introduces the essays that respond to these questions.

PMID: 19566276 [PubMed - indexed for MEDLINE]

131. Chaos. 2009 Jun;19(2):026108. doi: 10.1063/1.3143035.

Understanding the complexity of human gait dynamics.

Scafetta N(1), Marchi D, West BJ.

Author information:

(1)Department of Physics, Duke University, Durham, North Carolina 27708, USA.

Time series of human gait stride intervals exhibit FRACTAL and multiFRACTAL

properties under several conditions. Records from subjects walking at normal,

slow, and fast pace speed are analyzed to determine changes in the FRACTAL

scalings as a function of the stress condition of the system. Records from

subjects with different age from children to elderly and patients suffering from

neurodegenerative disease are analyzed to determine changes in the FRACTAL

scalings as a function of the physical maturation or degeneration of the system.

A supercentral pattern generator model is presented to simulate the above two

properties that are typically found in dynamical network performance: that is,

how a dynamical network responds to stress and to evolution.

PMID: 19566268 [PubMed - indexed for MEDLINE]

132. Chaos. 2009 Jun;19(2):026101. doi: 10.1063/1.3155067.

Introduction to focus issue: bipedal locomotion--from robots to humans.

Milton JG.

Author information:

Joint Science Department, The Claremont Colleges, 925 N. Mills Ave., Claremont,

California 91711, USA.

Running and walking, collectively referred to as bipedal locomotion, represent

self-organized behaviors generated by a spatially distributed dynamical system

operating under the constraint that a person must be able to move without falling

down. The organizing principles involve both forces actively regulated by the

nervous system and those generated passively by the biomechanical properties of

the musculoskeletal system and the environment in which the movements occur. With

the development of modern motion capture and electrophysiological techniques it

has become possible to explore the dynamical interplay between the passive and

active controllers of locomotion in a manner that directly compares observation

to predictions made by relevant mathematical and computer models. Consequently,

many of the techniques initially developed to study nonlinear dynamical systems,

including stability analyses, phase resetting and entrainment properties of limit

cycles, and FRACTAL and multiFRACTAL analysis, have come to play major roles in

guiding progress. This Focus Issue discusses bipedal locomotion from the point of

view of dynamical systems theory with the goal of stimulating discussion between

the dynamical systems, physics, biomechanics, and neuroscience communities.

PMID: 19566261 [PubMed - indexed for MEDLINE]

133. Med Image Anal. 2009 Aug;13(4):634-49. doi: 10.1016/ Epub

2009 May 27.

FRACTAL and multiFRACTAL analysis: a review.

Lopes R(1), Betrouni N.

Author information:

(1)Inserm, U703, Pavillon Vancostenobel, CHRU Lille, Lille Cedex 59037, France.

Over the last years, FRACTAL and multiFRACTAL geometries were applied extensively

in many medical signal (1D, 2D or 3D) analysis applications like pattern

recognition, texture analysis and segmentation. Application of this geometry

relies heavily on the estimation of the FRACTAL features. Various methods were

proposed to estimate the FRACTAL dimension or multiFRACTAL spectral of a signal.

This article presents an overview of these algorithms, the way they work, their

benefits and their limits. The aim of this review is to explain and to categorize

the various algorithms into groups and their application in the field of medical

signal analysis.

PMID: 19535282 [PubMed - indexed for MEDLINE]

134. Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Apr;79(4 Pt 2):046111. Epub 2009

Apr 30.

Drip paintings and FRACTAL analysis.

Jones-Smith K(1), Mathur H, Krauss LM.

Author information:

(1)Department of Physics, Case Western Reserve University, Cleveland, Ohio

44106-7079, USA.

It has been claimed that FRACTAL analysis can be applied to unambiguously

characterize works of art such as the drip paintings of Jackson Pollock. This

academic issue has become of more general interest following the recent discovery

of a cache of disputed Pollock paintings. We definitively demonstrate here, by

analyzing paintings by Pollock and others, that FRACTAL criteria provide no

information about artistic authenticity. This work has led us to a result in

FRACTAL analysis of more general scientific significance: we show that the

statistics of the "covering staircase" (closely related to the box-counting

staircase) provide a way to characterize geometry and distinguish FRACTALs from

Euclidean objects. Finally we present a discussion of the composite of two

FRACTALs, a problem that was first investigated by Muzy. We show that the

composite is not generally scale invariant and that it exhibits complex

multiFRACTAL scaling in the small distance asymptotic limit.

PMID: 19518305 [PubMed]

135. Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Apr;79(4 Pt 1):041920. Epub 2009

Apr 21.

Levels of complexity in scale-invariant neural signals.

Ivanov PCh(1), Ma QD, Bartsch RP, Hausdorff JM, Nunes Amaral LA,

Schulte-Frohlinde V, Stanley HE, Yoneyama M.

Author information:

(1)Department of Physics and Center for Polymer Studies, Boston University, and

Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts

02115, USA.

Many physical and physiological signals exhibit complex scale-invariant features

characterized by 1/f scaling and long-range power-law correlations, indicating a

possibly common control mechanism. Specifically, it has been suggested that

dynamical processes, influenced by inputs and feedback on multiple time scales,

may be sufficient to give rise to 1/f scaling and scale invariance. Two examples

of physiologic signals that are the output of hierarchical multiscale physiologic

systems under neural control are the human heartbeat and human gait. Here we show

that while both cardiac interbeat interval and gait interstride interval time

series under healthy conditions have comparable 1/f scaling, they still may

belong to different complexity classes. Our analysis of the multiFRACTAL scaling

exponents of the fluctuations in these two signals demonstrates that in contrast

to the multiFRACTAL behavior found in healthy heartbeat dynamics, gait time

series exhibit less complex, close to monoFRACTAL behavior. Further, we find

strong anticorrelations in the sign and close to random behavior for the

magnitude of gait fluctuations at short and intermediate time scales, in contrast

to weak anticorrelations in the sign and strong positive correlation for the

magnitude of heartbeat interval fluctuations-suggesting that the neural

mechanisms of cardiac and gait control exhibit different linear and nonlinear

features. These findings are of interest because they underscore the limitations

of traditional two-point correlation methods in fully characterizing

physiological and physical dynamics. In addition, these results suggest that

different mechanisms of control may be responsible for varying levels of

complexity observed in physiological systems under neural regulation and in

physical systems that possess similar 1/f scaling.

PMID: 19518269 [PubMed - indexed for MEDLINE]

136. Phys Rev Lett. 2009 Mar 13;102(10):106406. Epub 2009 Mar 13.

MultiFRACTAL analysis with the probability density function at the

three-dimensional anderson transition.

Rodriguez A(1), Vasquez LJ, Römer RA.

Author information:

(1)Department of Physics and Centre for Scientific Computing, University of Warwick,

Coventry, CV4 7AL, United Kingdom.

The probability density function (PDF) for critical wave function amplitudes is

studied in the three-dimensional Anderson model. We present a formal expression

between the PDF and the multiFRACTAL spectrum f(alpha) in which the role of

finite-size corrections is properly analyzed. We show the non-Gaussian nature and

the existence of a symmetry relation in the PDF. From the PDF, we extract

information about f(alpha) at criticality such as the presence of negative

FRACTAL dimensions and the possible existence of termination points. A PDF-based

multiFRACTAL analysis is shown to be a valid alternative to the standard approach

based on the scaling of inverse participation ratios.

PMID: 19392138 [PubMed]

137. Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Jan;79(1 Pt 2):016104. Epub 2009

Jan 8.

Free-electron gas in the Apollonian network: multiFRACTAL energy spectrum and its

thermodynamic fingerprints.

de Oliveira IN(1), de Moura FA, Lyra ML, Andrade JS Jr, Albuquerque EL.

Author information:

(1)Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió-AL,


We study the free-electron gas in an Apollonian network within the tight-binding

framework. The scale-free and small-world character of the underlying lattice is

known to result in a quite structured energy spectrum with deltalike

singularities, gaps, and minibands. After an exact numerical diagonalization of

the corresponding adjacency matrix of the network with a finite number of

generations, we employ a scaling analysis of the moments of the density of states

to characterize its multiFRACTALity and report the associated singularity

spectrum. The FRACTAL nature of the energy spectrum is also shown to be reflected

in the thermodynamic behavior by logarithmic modulations on the temperature

dependence of the specific heat. The absence of chiral symmetry of the Apollonian

network leads to distinct thermodynamic behaviors due to electrons and holes

thermal excitations.

PMID: 19257104 [PubMed]

138. Braz J Biol. 2008 Nov;68(4 Suppl):1003-12.

Comments about some species abundance patterns: classic, neutral, and niche

partitioning models.

Ferreira FC(1), Petrere M Jr.

Author information:

(1)Departamento de Ecologia, Universidade Estadual Paulista - UNESP,CP 199, CEP

13506-900, Rio Claro, SP, Brazil.

The literature on species abundance models is extensive and a great deal of new

and important contributions have been published in the last three decades.

Broadly speaking, one can recognize five families of species abundance models: i)

purely statistical or classic models (Broken-stick, Log-normal, Logarithmic and

Geometric series); ii) branching process (Zipf-Mandelbrot and FRACTAL branching

models); iii) population dynamics (Neutral models included); iv) spatial

distribution of individuals (MultiFRACTAL and HEAP models) and v) niche

partitioning (Sugihara's breakage and Tokeshi models). Among these the neutral,

the classic and the niche partitioning models have been the most applied to

natural communities, the former having been more extensively discussed than the

others in the last years. The objective of this paper is to comment some aspects

of the classic, neutral and niche partitioning models in a way that the proposed

distributions may contribute to the analysis of the empirical patterns of species

abundance. In spite of the variety of models, the distributions in general vary

between the log-normal and the logarithmic series. From these models the

Power-Fraction, together with independent niche dimensions measures, are amenable

to experimental tests and may offer answers on which resources are important in

the structuring of biological communities.

PMID: 19197471 [PubMed - indexed for MEDLINE]

139. Conf Proc IEEE Eng Med Biol Soc. 2008;2008:3912-5. doi:


3D mutiFRACTAL analysis: a new tool for epileptic fit sources detection in SPECT


Lopes R(1), Viard R, Dewalle AS, Steinling M, Maouche S, Betrouni N.

Author information:

(1)INSERM U703, Lille, France.

One of the imaging modalities used for the diagnosis of epilepsy is SPECT

(Single-Photon Emission Computed Tomography). Ictal and interictal images are

registered to MR images (SISCOM (Substracted Ictal Spect COregistred to MR) to

delineate the sources. However, in some cases and for many reasons, the used

method does not lead to precise delimitation of epileptic fit sources. In this

case, works have been investigated on group's studies or in combining others

modalities like EEG (Electroencephalography). This study investigates the

possibility of using a mathematic model for the image texture to detect the

changes on SPECT images. Beyond encouraging preliminary results concerning the

multiFRACTAL analysis to distinguish volunteers and epileptic patients, our aim

was to detect sources by the singularity spectrum compute. The experiment is

divided into two phases. First, we developed a 3D method for the singularity

spectrum compute. In the test phase, we applied this multiFRACTAL spectrum to the

sources detection on SPECT images. The results obtained on a base of seven

patients show that the proposed method is encouraging. Indeed, the detections of

epileptic fit sources obtained were in agree with the expert diagnostic.

PMID: 19163568 [PubMed - indexed for MEDLINE]

140. Sensors (Basel). 2009;9(11):8669-83. doi: 10.3390/s91108669. Epub 2009 Oct 29.

Super-resolution reconstruction of remote sensing images using multiFRACTAL


Hu MG(1), Wang JF, Ge Y.

Author information:

(1)Institute of Geographic Sciences & Nature Resources Research, Chinese Academy of

Sciences, Beijing, China; E-Mails: (M.H.);


Satellite remote sensing (RS) is an important contributor to Earth observation,

providing various kinds of imagery every day, but low spatial resolution remains

a critical bottleneck in a lot of applications, restricting higher spatial

resolution analysis (e.g., intra-urban). In this study, a multiFRACTAL-based

super-resolution reconstruction method is proposed to alleviate this problem. The

multiFRACTAL characteristic is common in Nature. The self-similarity or

self-affinity presented in the image is useful to estimate details at larger and

smaller scales than the original. We first look for the presence of multiFRACTAL

characteristics in the images. Then we estimate parameters of the information

transfer function and noise of the low resolution image. Finally, a noise-free,

spatial resolution-enhanced image is generated by a FRACTAL coding-based

denoising and downscaling method. The empirical case shows that the reconstructed

super-resolution image performs well in detail enhancement. This method is not

only useful for remote sensing in investigating Earth, but also for other images

with multiFRACTAL characteristics.

PMCID: PMC3260607

PMID: 22291530 [PubMed]

141. Chaos. 2008 Sep;18(3):033115. doi: 10.1063/1.2965502.

MultiFRACTAL and statistical analyses of heat release fluctuations in a spark

ignition engine.

Sen AK(1), Litak G, Kaminski T, Wendeker M.

Author information:

(1)Department of Mathematical Sciences, Indiana University, 402 North Blackford

Street, Indianapolis, Indiana 46202, USA.

Using multiFRACTAL and statistical analyses, we have investigated the complex

dynamics of cycle-to-cycle heat release variations in a spark ignition engine.

Three different values of the spark advance angle (Delta beta) are examined. The

multiFRACTAL complexity is characterized by the singularity spectrum of the heat

release time series in terms of the Holder exponent. The broadness of the

singularity spectrum gives a measure of the degree of mutiFRACTALity or

complexity of the time series. The broader the spectrum, the richer and more

complex is the structure with a higher degree of multiFRACTALity. Using this

broadness measure, the complexity in heat release variations is compared for the

three spark advance angles (SAAs). Our results reveal that the heat release data

are most complex for Delta beta=30 degrees followed in order by Delta beta=15

degrees and 5 degrees. In other words, the complexity increases with increasing

SAA. In addition, we found that for all the SAAs considered, the heat release

fluctuations behave like an antipersistent or a negatively correlated process,

becoming more antipersistent with decreasing SAA. We have also performed a

statistical analysis of the heat release variations by calculating the kurtosis

of their probability density functions (pdfs). It is found that for the smallest

SAA considered, Delta beta=5 degrees, the pdf is nearly Gaussian with a kurtosis

of 3.42. As the value of the SAA increases, the pdf deviates from a Gaussian

distribution and tends to be more peaked with larger values of kurtosis. In

particular, the kurtosis has values of 3.94 and 6.69, for Delta beta=15 degrees

and 30 degrees, respectively. A non-Gaussian density function with kurtosis in

excess of 3 is indicative of intermittency. A larger value of kurtosis implies a

higher degree of intermittency.

(c) 2008 American Institute of Physics.

PMID: 19045453 [PubMed - indexed for MEDLINE]

142. J Appl Clin Med Phys. 2008 Nov 11;9(4):2741.

A novel algorithm for initial lesion detection in ultrasound breast images.

Yap MH(1), Edirisinghe EA, Bez HE.

Author information:

(1)Department of Computer Science, Loughborough University, Loughborough, U.K.

This paper proposes a novel approach to initial lesion detection in ultrasound

breast images. The objective is to automate the manual process of region of

interest (ROI) labeling in computer-aided diagnosis (CAD). We propose the use of

hybrid filtering, multiFRACTAL processing, and thresholding segmentation in

initial lesion detection and automated ROI labeling. We used 360 ultrasound

breast images to evaluate the performance of the proposed approach. Images were

preprocessed using histogram equalization before hybrid filtering and

multiFRACTAL analysis were conducted. Subsequently, thresholding segmentation was

applied on the image. Finally, the initial lesions are detected using a

rule-based approach. The accuracy of the automated ROI labeling was measured as

an overlap of 0.4 with the lesion outline as compared with lesions labeled by an

expert radiologist. We compared the performance of the proposed method with that

of three state-of-the-art methods, namely, the radial gradient index filtering

technique, the local mean technique, and the FRACTAL dimension technique. We

conclude that the proposed method is more accurate and performs more effectively

than do the benchmark algorithms considered.

PMID: 19020477 [PubMed - indexed for MEDLINE]

143. Philos Trans A Math Phys Eng Sci. 2009 Jan 28;367(1887):277-96. doi:


Methods derived from nonlinear dynamics for analysing heart rate variability.

Voss A(1), Schulz S, Schroeder R, Baumert M, Caminal P.

Author information:

(1)Department of Medical Engineering and Biotechnology, University of Applied

Sciences Jena, 07745 Jena, Germany.

Methods from nonlinear dynamics (NLD) have shown new insights into heart rate

(HR) variability changes under various physiological and pathological conditions,

providing additional prognostic information and complementing traditional time-

and frequency-domain analyses. In this review, some of the most prominent indices

of nonlinear and FRACTAL dynamics are summarized and their algorithmic

implementations and applications in clinical trials are discussed. Several of

those indices have been proven to be of diagnostic relevance or have contributed

to risk stratification. In particular, techniques based on mono- and multiFRACTAL

analyses and symbolic dynamics have been successfully applied to clinical

studies. Further advances in HR variability analysis are expected through

multidimensional and multivariate assessments. Today, the question is no longer

about whether or not methods from NLD should be applied; however, it is relevant

to ask which of the methods should be selected and under which basic and

standardized conditions should they be applied.

PMID: 18977726 [PubMed - indexed for MEDLINE]

144. Dokl Biol Sci. 2008 Jul-Aug;421:257-61.

MultiFRACTAL analysis of the species structure of small-mammal communities of the

Volga-Ural paleobiocenosis.

Gelashvili DB(1), Dmitriev AI, Iudin DI, Rozenberg GS, Solntsev LA.

Author information:

(1)Faculty of Biology, Nizhni Novgorod State University, pr. Gagarina 23, Nizhni

Novgorod, 603950 Russia.

PMID: 18841809 [PubMed - indexed for MEDLINE]

145. Am Nat. 2002 Feb;159(2):138-55. doi: 10.1086/324787.

Species-area curves, diversity indices, and species abundance distributions: a

multiFRACTAL analysis.

Borda-de-Agua L(1), Hubbell SP, McAllister M.

Author information:

(1)Center for Environmental Research and Conservation, Columbia University, New

York, New York 10027, USA.

Although FRACTALs have been applied in ecology for some time, multiFRACTALs have,

in contrast, received little attention. In this article, we apply multiFRACTALs

to the species-area relationship and species abundance distributions. We

highlight two results: first, species abundance distributions collected at

different spatial scales may collapse into a single curve after appropriate

renormalization, and second, the power-law form of the species-area relationship

and the Shannon, Simpson, and Berger-Parker diversity indices belong to a family

of equations relating the species number, species abundance, and area through the

moments of the species abundance-probability density function. Explicit formulas

for these diversity indices, as a function of area, are derived. Methods to

obtain the multiFRACTAL spectra from a data set are discussed, and an example is

shown with data on tree and shrub species collected in a 50-ha plot on Barro

Colorado Island, Panama. Finally, we discuss the implications of the multiFRACTAL

formalism to the relationship between species range and abundance and the

relation between the shape of the species abundance distribution and area.

PMID: 18707410 [PubMed]

146. J Neurosci Methods. 2008 Sep 30;174(2):292-300. doi:

10.1016/j.jneumeth.2008.06.037. Epub 2008 Jul 23.

Endogenous multiFRACTAL brain dynamics are modulated by age, cholinergic blockade

and cognitive performance.

Suckling J(1), Wink AM, Bernard FA, Barnes A, Bullmore E.

Author information:

(1)Brain Mapping Unit, University of Cambridge, Department of Psychiatry,

Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.

The intuitive notion that a healthy organism is characterised by regular,

homeostatic function has been challenged by observations that a loss of

complexity is, in fact, indicative of ill-health. MonoFRACTALs succinctly

describe complex processes and are controlled by a single time-invariant scaling

exponent, H, simply related to the FRACTAL dimension. Previous analyses of

resting fMRI time-series demonstrated that ageing and scopolamine administration

were both associated with increases in H and that faster response in a prior

encoding task was also associated with increased H. We revisit this experiment

with a novel, multiFRACTAL approach in which FRACTAL dynamics are assumed to be

non-stationary and defined by a spectrum of local singularity exponents.

Parameterisation of this spectrum was capable of refracting the effects of age,

scopolamine and task performance as well as a refining a description of the

associated signal changes. Using the same imaging data, we also explored

turbulence as a possible mechanism underlying multiFRACTAL dynamics. Evidence is

provided that Carstaing's model of turbulent information flow from high to low

scales has only limited validity, and that scale invariance of energy dissipation

is better explained by critical-phase phenomena, supporting the proposition that

the brain maintains a state of self-organised criticality.

PMCID: PMC2590659

PMID: 18703089 [PubMed - indexed for MEDLINE]

147. J Pharmacol Toxicol Methods. 2008 Sep-Oct;58(2):118-28. doi:

10.1016/j.vascn.2008.05.005. Epub 2008 Jul 10.

Heartbeat dynamics in adrenergic blocker treated conscious beagle dogs.

Li D(1), Chiang AY, Clawson CA, Main BW, Leishman DJ.

Author information:

(1)Global Statistical Sciences and Toxicology, Lilly Research Laboratories, Eli

Lilly and Company, Greenfield, IN 46140, USA.

INTRODUCTION: Adrenergic blockade as a treatment for chronic heart failure (CHF)

has proved effective, but its pharmacological mechanism on CHF remains unclear.

In the past two decades, studies on heart rate variability (HRV) have reported

that CHF patients generally have a reduced temporal complexity in heart rate

variability. On the other hand, adrenergic blockers have been shown to restore

such complexity. FRACTAL analysis is a novel and efficient tool to explore the

adrenergic blockade effect on HRV. This paper applies the detrended fluctuation

analysis (DFA) and multiFRACTAL DFA (MF-DFA) methods in an attempt to understand

the effect of adrenergic blockade on cardiac dynamics in conscious beagle dogs.

METHODS: DFA and MF-DFA analysis are conducted on RR interval data generated from

telemetry instrumented dogs receiving a combination of 15 mg/kg nadolol and 5

mg/kg phenoxybenzamine orally administered at the 22nd and 34th hour in a

parallel design (n=12). All dogs had approximately 48 h of beat-to-beat heart

rate measurements recorded in the left ventricle. Complexity measures for

heartbeat series are compared between the blocker and vehicle group. We also

compute traditional statistics for HRV and spectral parameters and examine their

correlation with FRACTAL analysis.

RESULTS: When compared to the vehicle group, the adrenergic blocker group had: 1)

longer RR intervals (p=0.02) and lower beat-to-beat variability (p=0.04); 2)

decreased low frequency (LF) and high frequency (HF) power (p=0.03), and higher

LF-to-HF ratio; 3) larger middle-range scaling exponents (p<0.01); 4) broader

multiFRACTAL spectra (p=0.03) with higher dominant singularity indices (p=0.02).

DISCUSSION: Our results show that 1) adrenergic blockade alters the sympathovagal

balance; 2) adrenergic blockers enhance the complexity of the cardiac dynamics;

3) the adrenergic blockade effect on cardiac dynamics is primarily the

attenuation of small fluctuations in RR intervals. FRACTAL analysis also has the

potential to be applied to early QT diagnosis.

PMID: 18619862 [PubMed - indexed for MEDLINE]

148. Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Apr;77(4 Pt 2):045101. Epub 2008

Apr 18.

Self-affine FRACTALs embedded in spectra of complex networks.

Yang H(1), Yin C, Zhu G, Li B.

Author information:

(1)Department of Physics and Centre for Computational Science and Engineering,

National University of Singapore, Singapore 117542.

The scaling properties of spectra of real world complex networks are studied by

using the wavelet transform. It is found that the spectra of networks are

multiFRACTAL. According to the values of the long-range correlation exponent, the

Hust exponent H, the networks can be classified into three types, namely, H>0.5,

H=0.5, and H<0.5. All real world networks considered belong to the class of

H>or=0.5, which may be explained by the hierarchical properties.

PMID: 18517677 [PubMed]

149. Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Mar;77(3 Pt 2):036210. Epub 2008

Mar 18.

Anomaly of FRACTAL dimensions observed in stochastically switched systems.

Nishikawa J(1), Gohara K.

Author information:

(1)Department of Applied Physics, Hokkaido University, Sapporo, Hokkaido, Japan.

We studied an anomaly in FRACTAL dimensions measured from the attractors of

dynamical systems driven by stochastically switched inputs. We calculated the

dimensions for different switching time lengths in two-dimensional linear

dynamical systems, and found that changes in the dimensions due to the switching

time length had a singular point when the system matrix had two different real

eigenvalues. Using partial dimensions along each eigenvector, we explicitly

derived a generalized dimension D(q) and a multiFRACTAL spectrum f(alpha) to

explain this anomalous property. The results from numerical calculations agreed

well with those from analytical equations. We found that this anomaly is caused

by linear independence, inhomogeneity of eigenvalues, and overlapping conditions.

The mechanism for the anomaly could be identified for various inhomogeneous

systems including nonlinear ones, and this reminded us of anomalies in some

physical values observed in critical phenomena.

PMID: 18517488 [PubMed]

150. Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Mar;77(3 Pt 2):036205. Epub 2008

Mar 11.

FRACTAL Weyl law for chaotic microcavities: Fresnel's laws imply multiFRACTAL


Wiersig J(1), Main J.

Author information:

(1)Institut für Theoretische Physik, Universität Bremen, Bremen, Germany.

We demonstrate that the harmonic inversion technique is a powerful tool to

analyze the spectral properties of optical microcavities. As an interesting

example we study the statistical properties of complex frequencies of the fully

chaotic microstadium. We show that the conjectured FRACTAL Weyl law for open

chaotic systems [Lu, Phys. Rev. Lett. 91, 154101 (2003)] is valid for dielectric

microcavities only if the concept of the chaotic repeller is extended to a

multiFRACTAL by incorporating Fresnel's laws.

PMID: 18517483 [PubMed]

151. Hum Brain Mapp. 2008 Jul;29(7):791-801. doi: 10.1002/hbm.20593.

MonoFRACTAL and multiFRACTAL dynamics of low frequency endogenous brain

oscillations in functional MRI.

Wink AM(1), Bullmore E, Barnes A, Bernard F, Suckling J.

Author information:

(1)Brain Mapping Unit, Department of Psychiatry, Addenbrooke's Hospital, University

of Cambridge, Cambridge, United Kingdom.

FRACTAL processes, like trees or coastlines, are defined by self-similarity or

power law scaling controlled by a single exponent, simply related to the FRACTAL

dimension or Hurst exponent (H) of the process. MultiFRACTAL processes, like

turbulence, have more complex behaviours defined by a spectrum of possible local

scaling behaviours or singularity exponents (h). Here, we report two experiments

that explore the relationships between instrumental and cognitive variables and

the monoFRACTAL and multiFRACTAL parameters of functional magnetic resonance

imaging (fMRI) data acquired in a no-task or resting state. First, we show that

the Hurst exponent is greater in grey matter than in white matter regions, and it

is maximal in grey matter when data were acquired with an echo time known to

optimise BOLD contrast. Second, we show that latency of response in a fame

decision/facial encoding task was negatively correlated with the Hurst exponent

of resting state data acquired 30 min after task performance. This association

was localised to a right inferior frontal cortical region activated by the fame

decision task and indicated that people with shorter response latency had more

persistent dynamics (higher values of H). MultiFRACTAL analysis revealed that

faster responding participants had wider singularity spectra of resting fMRI time

series in inferior frontal cortex. Endogenous brain oscillations measured by fMRI

have monoFRACTAL and multiFRACTAL properties that can be related to instrumental

and cognitive factors in a way, which indicates that these low frequency dynamics

are relevant to neurocognitive function.

(c) 2008 Wiley-Liss, Inc.

PMID: 18465788 [PubMed - indexed for MEDLINE]

152. Gynecol Obstet Invest. 2008;66(2):127-33. doi: 10.1159/000129671. Epub 2008 May


MultiFRACTAL description of the maternal surface of the placenta.

Kikuchi A(1), Unno N, Shiba M, Sunagawa S, Ogiso Y, Kozuma S, Taketani Y.

Author information:

(1)Department of Obstetrics, Center for Perinatal Medicine, Nagano Children's

Hospital, Nagano, Japan.

BACKGROUND: Recently, multiFRACTAL analysis based on generalized concepts of

FRACTALs has been applied to biological tissues composed of complex structures.

METHODS: Using digitized images of the maternal surface of 278 placentas,

multiFRACTAL parameters were measured with a FRACTAL analysis software.

RESULTS: The values of alpha(min), alpha(0), alpha(max) and the degree of

multiFRACTALity given by the alpha(max) - alpha(min) difference calculated from

278 placentas were 1.840 +/- 0.068, 2.089 +/- 0.034, 2.856 +/- 0.128 and 1.017

+/- 0.136, respectively. A significant decrease of alpha(min) and as a

consequence a significant increase in the degree of multiFRACTALity were observed

according to gestational age. The alpha(0) value of the placenta complicated by

pregnancy-induced hypertension (PIH) was significantly higher than that without

PIH. The alpha(min) and alpha(0) values of the placenta having intrauterine

growth restriction (IUGR) were significantly higher than those without IUGR. On

the other hand, the presence of chorioamnionitis did not change multiFRACTAL

properties of the maternal surface of the placenta.

CONCLUSION: The multiFRACTAL parameters may be objective indices of the

heterogeneity or complexity of the macroscopic morphology of the maternal surface

of the placenta. MultiFRACTAL analysis holds a promise for quantitatively

evaluating physiological and pathological development of the placenta.

(c) 2008 S. Karger AG, Basel.

PMID: 18463415 [PubMed - indexed for MEDLINE]

153. Med Phys. 2008 Feb;35(2):717-23.

MultiFRACTALity, sample entropy, and wavelet analyses for age-related changes in

the peripheral cardiovascular system: preliminary results.

Humeau A(1), Chapeau-Blondeau F, Rousseau D, Rousseau P, Trzepizur W, Abraham P.

Author information:

(1)Groupe esaip, 18 rue du 8 mai 1945, BP 80022, 49180 Saint Barthélémy d'Anjou,


Using signal processing measures we evaluate the effect of aging on the

peripheral cardiovascular system. Laser Doppler flowmetry (LDF) signals,

reflecting the microvascular perfusion, are recorded on the forearm of 27 healthy

subjects between 20-30, 40-50, or 60-70 years old. Wavelet-based representations,

Hölder exponents, and sample entropy values are computed for each time series.

The results indicate a possible modification of the peripheral cardiovascular

system with aging. Thus, the endothelial-related metabolic activity decreases,

but not significantly, with aging. Furthermore, LDF signals are more monoFRACTAL

for elderly subjects than for young people for whom LDF signals are weakly

multiFRACTAL: the average range of Holder exponents computed with a parametric

generalized quadratic variation based estimation method is 0.13 for subjects

between 20 and 30 years old and 0.06 for subjects between 60 and 70 years old.

Moreover, the average mean sample entropy value of LDF signals slightly decreases

with age: it is 1.34 for subjects between 20 and 30 years old and 1.19 for

subjects between 60 and 70 years old. Our results could assist in gaining

knowledge on the relationship between microvascular system status and age and

could also lead to a more accurate age-related nonlinear modeling.

PMID: 18383693 [PubMed - indexed for MEDLINE]

154. Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Feb;77(2 Pt 2):026111. Epub 2008

Feb 15.

MultiFRACTALity and randomness in the unstable plastic flow near the lower

strain-rate boundary of instability.

Lebyodkin MA(1), Lebedkina TA.

Author information:

(1)Laboratoire de Physique et Mécanique des Matériaux, UMR CNRS No 7554, Université

Paul Verlaine - Metz, Ile du Saulcy, 57045 Metz Cedex, France.

The unstable plastic flow of an AlMg alloy, associated with the Portevin-Le

Chatelier effect, was studied near the lower strain-rate boundary of instability

using multiFRACTAL analysis. Self-similarity of deformation curves, indicating

long-range time correlations of stress serrations, was detected within the

strain-rate range where serrations are commonly ascribed to the occurrence of

uncorrelated deformation bands. The deformation curves display a wide range of

shapes that are characterized by different groupings of serrations. MultiFRACTAL

analysis provides a method to quantify the observed complexity and compare it to

known Portevin-Le Chatelier effect regimes. The measurement noise effect on the

multiFRACTAL spectra determined from experimental data was mimicked by

superposing multiFRACTAL Cantor sets with random noise. Such tests using standard

multiFRACTAL data sets justify the separation of self-similar and random

components of the serrated deformation curves. Furthermore, these results shed

light on the general problem of the effect of experimental noise on the apparent

multiFRACTAL properties of physical FRACTALs.

PMID: 18352094 [PubMed]

155. J Theor Biol. 2008 Mar 7;251(1):60-7. Epub 2007 Sep 26.

Why the wrinkling transition in partially polymerized membranes is not universal?

FRACTAL-multiFRACTAL hierarchy.

Chaieb S(1), Málková S, Lal J.

Author information:

(1)Mechanical Science and Engineering Department, University of Illinois at

Urbana-Champaign, USA.

When partially polymerized membranes wrinkle they exhibit a passage from a

conventional buckling (due to an instability caused by chiral symmetry breaking)

at low polymerization to a local roughening (due to a frustration in the local

packing of the chiral molecules composing the membrane) as a function of the

polymerization of the lipids aliphatic tails. This transition was found to be

non-universal and here we used neutron scattering to elucidate that this behavior

is due to the onset of stretching in the membrane accompanied by a bilayer

thickness variation. Close to the percolation limit this deformation is plastic

similar to mutated lysozymes. We draw an analogy between this transition and

echinocytes in red blood cells.

PMID: 18083197 [PubMed - indexed for MEDLINE]

156. Biophys J. 2007 Dec 15;93(12):L59-61.

MultiFRACTALity in the peripheral cardiovascular system from pointwise holder

exponents of laser Doppler flowmetry signals.

Humeau A(1), Chapeau-Blondeau F, Rousseau D, Tartas M, Fromy B, Abraham P.

Author information:

(1)Groupe ISAIP-ESAIP, Saint Barthélémy d'Anjou, France.

We study the dynamics of skin laser Doppler flowmetry signals giving a peripheral

view of the cardiovascular system. The analysis of Hölder exponents reveals that

the experimental signals are weakly multiFRACTAL for young healthy subjects at

rest. We implement the same analysis on data generated by a standard theoretical

model of the cardiovascular system based on nonlinear coupled oscillators with

linear couplings and fluctuations. We show that the theoretical model, although

it captures basic features of the dynamics, is not complex enough to reflect the

multiFRACTAL irregularities of microvascular mechanisms.

PMCID: PMC2098720

PMID: 18045964 [PubMed - indexed for MEDLINE]

157. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:5543-6.

Multidimensional models for methodological validation in multiFRACTAL analysis.

Lopes R(1), Dubois P, Bhouri I, Puech P, Maouche S, Betrouni N.

Author information:

(1)Inserm, U703, Lille, France.

MultiFRACTAL analysis is known as a useful tool in signal analysis. However

methods are often used without methodological validation. In this study, we

define multidimensional models in order to validate multiFRACTAL analysis


PMID: 18003268 [PubMed - indexed for MEDLINE]

158. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:5035-8.

Local-scale analysis of cardiovascular signals by detrended fluctuations

analysis: effects of posture and exercise.

Castiglioni P(1), Quintin L, Civijian A, Parati G, Di Rienzo M.

Author information:

(1)Polo Tecnologico (Biomedical Technology Department), IRCCS S. Maria Nascente,

Fondazione Don Gnocchi Onlus, Milan, Italy.

The FRACTAL structure of heart rate is usually quantified by estimating a

short-term (alpha(1)) and a long-term (alpha(2)) scaling exponent by Detrended

Fluctuations Analysis (DFA). Evidence, however, has been provided that heart rate

is a multiFRACTAL signal, better characterized by a large number of scaling

exponents. Aim of this study is to verify whether two scaling exponents only from

DFA provide a sufficiently accurate description of the possibly multiFRACTAL

nature of cardiovascular signals. We measured ECG and finger arterial pressure in

33 volunteers for 10 minutes during each of 3 conditions: supine rest (SUP);

sitting at rest (SIT); light physical exercise (EXE). DFA was applied on the

beat-by-beat series of R-R interval (RRI) and mean arterial pressure (MAP). We

then computed the local scaling exponent alpha(n), defined as the slope of the

detrended fluctuation function F(n) around the beat scale n, in a log-log plot.

If alpha(1) and alpha(2) correctly model the multiscale structure of blood

pressure and heart rate, we should find that alpha(n) is constant over a

short-term and a longterm range of beat scales. Results show that only the

long-term alpha2 exponent provides a relatively good approximation of the

multiscale structure of RRI and MAP. Moreover, posture and physical activity have

important effects on local scaling exponents, and on the range of beat scales n

where alpha(n) can be approximated by a constant alpha2 coefficient.

PMID: 18003137 [PubMed - indexed for MEDLINE]

159. Brain Res. 2007 Dec;1186:113-23. Epub 2007 Oct 16.

Neuronal response to Shepard's tones: an auditory fMRI study using multiFRACTAL


Shimizu Y(1), Umeda M, Mano H, Aoki I, Higuchi T, Tanaka C.

Author information:

(1)Department of Neurosurgery, Meiji University of Oriental Medicine, Hiyoshi-cho,

Funai-gun, Kyoto, Japan.

Shepard's tones are a typical example for auditory illusion. They consist in a

series of computer generated tones, which prohibit relative pitch discrimination.

As a result, when repetitively played in sequence, the illusion of an

ever-ascending scale is evoked. In order to investigate this aural phenomenon,

fMRI time series were acquired during presentation of a conventional

block-designed paradigm as well as during continuous presentation of Shepard's

tones. With respect to the different setups of the two experiments, two

fundamentally different methods were applied in order to conduct data analysis.

Common Statistical Parameter Mapping served to evaluate the time series obtained

with the block-designed paradigm. For the continuous experiment, a novel

wavelet-based multiFRACTAL analysis was used, recently proposed as a

classification tool for fMRI time series. This approach applies the wavelet

transform to extract multiFRACTAL spectra from time-signals. For reasons of

quantification, we introduced an ameliorated method for visual inspection of the

multiFRACTAL properties. The results proved existence of characteristic neural

responses to continuously presented Shepard's tones. Interestingly, the same was

not restricted to the auditory cortex, but also involved areas of the visual

cortex. Related impact on the imaged cognitive areas, primary motor cortex, and

primary sensory cortex could not be observed. We further provide evidence that

pitch misjudgment does not occur in temporal concurrence with the repetition of

the whole scale, but according to whether the main perceived frequency is located

in the sensitive range of auditory perception or not. We remark that this is the

first time, continuously stimulated brain areas could be detected by means of


PMID: 17999926 [PubMed - indexed for MEDLINE]

160. Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Oct;76(4 Pt 2):046612. Epub 2007

Oct 29.

Soliton FRACTALs in the Korteweg-de Vries equation.

Zamora-Sillero E(1), Shapovalov AV.

Author information:

(1)Departamento de Fisica Aplicada I, Escuela Universitaria Politecnica. Universidad

de Sevilla Virgen de Africa 7, 41011 Sevilla, Spain.

We have studied the process of creation of solitons and generation of FRACTAL

structures in the Korteweg-de Vries (KdV) equation when the relation between the

nonlinearity and dispersion is abruptly changed. We observed that when this

relation is changed nonadiabatically the solitary waves present in the system

lose their stability and split up into ones that are stable for the set of

parameters. When this process is successively repeated the trajectories of the

solitary waves create a FRACTAL treelike structure where each branch bifurcates

into others. This structure is formed until the iteration where two solitary

waves overlap just before the breakup. By means of a method based on the inverse

scattering transformation, we have obtained analytical results that predict and

control the number, amplitude, and velocity of the solitary waves that arise in

the system after every change in the relation between the dispersion and the

nonlinearity. This complete analytical information allows us to define a

recursive L system which coincides with the treelike structure, governed by KdV,

until the stage when the solitons start to overlap and is used to calculate the

Hausdorff dimension and the multiFRACTAL properties of the set formed by the

segments defined by each of the two "brothers" solitons before every breakup.

PMID: 17995132 [PubMed]

161. Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Oct;76(4 Pt 1):041910. Epub 2007

Oct 19.

MultiFRACTALity and scale invariance in human heartbeat dynamics.

Ching ES(1), Tsang YK.

Author information:

(1)Department of Physics and Institute of Theoretical Physics, The Chinese

University of Hong Kong, Shatin, Hong Kong.

Human heart rate is known to display complex fluctuations. Evidence of

multiFRACTALity in heart rate fluctuations in healthy state has been reported

[Ivanov, Nature (London) 399, 461 (1999)]. This multiFRACTAL character could be

manifested as the dependence of the probability density functions (PDFs) of the

interbeat interval increments, which are the differences in two interbeat

intervals that are separated by n beats, on n . On the other hand, "scale

invariance in the PDFs of detrended healthy human heart rate increments" was

recently reported [Kiyono, Phys. Rev. Lett. 93, 178103 (2004)]. In this paper, we

clarify that the scale invariance reported is actually exhibited by the PDFs of

the increments of the "detrended" integrated healthy interbeat interval and

should, therefore, be more accurately referred as the scale invariance or n

independence of the PDFs of the sum of n detrended interbeat intervals. Indeed,

we demonstrate explicitly that the PDFs of detrended healthy interbeat interval

increments are scale or n dependent in accord with its multiFRACTAL character.

Our work also establishes that this n independence of the PDFs of the sum of n

detrended interbeat intervals is a general feature of human heartbeat dynamics,

shared by heart rate fluctuations in both healthy and pathological states.

PMID: 17995029 [PubMed - indexed for MEDLINE]

162. Nord J Psychiatry. 2007;61(5):339-42.

MultiFRACTAL analysis as an aid in the diagnostics of mental disorders.

Slezin VB(1), Korsakova EA, Dytjatkovsky MA, Schultz EA, Arystova TA, Siivola JR.

Author information:

(1)Bekhterevs Psychoneurological Research Institute, St Petersburg, Russia.

The digitalization of EEGs (electroencephalogram) has showed new possibilities

for analyzing electrical activity of brain. This has offered new methods, e.g.

multiFRACTAL analysis of 1/f(beta) EEG rhythms fluctuations. It is one of highly

mathematical methods feasible in routine practice now that modern personal

computers (PCs) have reached sufficient computing power. In this study, we

applied the multiFRACTAL analysis of 1/f(beta) EEG rhythms fluctuations in 33

patients suffering from schizophrenia and schizophrenia-like syndromes, and we

had 23 healthy controls. Our results indicated that the patients suffering from

schizophrenia have statistically different values compared with the controls.

This method is rather easy and quick to perform when using a standard PC. It may

have the potential to become an important tool in the diagnostics and analysis of

the patients with schizophrenia and schizophreniformic psychoses. It can help to

understand the quasi-chaotic processes in neural processing and narrow the gap

between the phenomenological psychiatry and bio-psychiatry.

PMID: 17990194 [PubMed - indexed for MEDLINE]

163. Conf Proc IEEE Eng Med Biol Soc. 2006;1:1450-3.

Further study of the asymmetry for multiFRACTAL spectra of heartbeat time series.

Muñoz-Diosdado A(1), Del Río-Correa JL.

Author information:

(1)Department of Mathematics, Unidad Profesional Interdisciplinaria de

Biotecnología, Instituto Politécnico Nacional, México, Col. Barrio la Laguna

Ticomán, 07340, México, DF.

We study the asymmetry of multiFRACTAL spectra of diurnal heartbeat time series

from healthy young subjects, healthy elderly subjects and patients with

congestive heart failure (CHF). Aging and CHF causes loss of multiFRACTALity. We

report here some ways of analyzing the asymmetry of these spectra and we show how

the joint analysis of the degree of multiFRACTALity and the parameters that

characterizes the asymmetry can differentiate between the cardiac interbeat time

series of young and elderly persons and it can also separate healthy subjects and

CHF patients.

PMID: 17946464 [PubMed - indexed for MEDLINE]

164. Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Sep;76(3 Pt 2):036705. Epub 2007

Sep 14.

FRACTAL geometry in an expanding, one-dimensional, Newtonian universe.

Miller BN(1), Rouet JL, Le Guirriec E.

Author information:

(1)Department of Physics and Astronomy, Texas Christian University, Fort Worth,

Texas 76129, USA.

Observations of galaxies over large distances reveal the possibility of a FRACTAL

distribution of their positions. The source of FRACTAL behavior is the lack of a

length scale in the two body gravitational interaction. However, even with new,

larger, sample sizes from recent surveys, it is difficult to extract information

concerning FRACTAL properties with confidence. Similarly, three-dimensional

N-body simulations with a billion particles only provide a thousand particles per

dimension, far too small for accurate conclusions. With one-dimensional models

these limitations can be overcome by carrying out simulations with on the order

of a quarter of a million particles without compromising the computation of the

gravitational force. Here the multiFRACTAL properties of two of these models that

incorporate different features of the dynamical equations governing the evolution

of a matter dominated universe are compared. For each model at least two scaling

regions are identified. By employing criteria from dynamical systems theory it is

shown that only one of them can be geometrically significant. The results share

important similarities with galaxy observations, such as hierarchical clustering

and apparent biFRACTAL geometry. They also provide insights concerning possible

constraints on length and time scales for FRACTAL structure. They clearly

demonstrate that FRACTAL geometry evolves in the mu (position, velocity) space.

The observed patterns are simply a shadow (projection) of higher-dimensional


PMID: 17930359 [PubMed]

165. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2007 Jun;24(3):522-5.

[MultiFRACTAL analysis of genomes sequences' CGR graph].

[Article in Chinese]

Fu W(1), Wang Y, Lu D.

Author information:

(1)Department of Physics, Fudan University, Shanghai 200433, China.

To describe the FRACTAL feature of CGR (Chaos-game representation) graph of

genomes sequences, a multiFRACTAL theory is presented in the analysis. By

studying the effect of three probability sets on the scale invariance range, the

probability set with the best scale invariance is chosen, and then the smooth

general dimension spectrum and multiFRACTAL spectrum are calculated. The

experimental result shows that the probability set composed of the relative

probability has the best scale-invariance performance. The scale invariance has

three different variance regions, which indicate that genomes sequence segments

with different lengths have different distribution rules. It is concluded that

the multiFRACTAL method is effective for describing the FRACTAL feature of CGR

graph of genomes sequences.

PMID: 17713253 [PubMed - indexed for MEDLINE]

166. Philos Trans A Math Phys Eng Sci. 2008 Feb 13;366(1864):345-57.

A complex biological system: the fly's visual module.

Baptista MS(1), de Almeida LO, Slaets JF, Köberle R, Grebogi C.

Author information:

(1)Institut für Physik Am Neuen Palais 10, Universität Potsdam, 14469 Potsdam,


Is the characterization of biological systems as complex systems in the

mathematical sense a fruitful assertion? In this paper we argue in the

affirmative, although obviously we do not attempt to confront all the issues

raised by this question. We use the fly's visual system as an example and analyse

our experimental results of one particular neuron in the fly's visual system from

this point of view. We find that the motion-sensitive 'H1' neuron, which converts

incoming signals into a sequence of identical pulses or 'spikes', encodes the

information contained in the stimulus into an alphabet composed of a few letters.

This encoding occurs on multilayered sets, one of the features attributed to

complex systems. The conversion of intervals between consecutive occurrences of

spikes into an alphabet requires us to construct a generating partition. This

entails a one-to-one correspondence between sequences of spike intervals and

words written in the alphabet. The alphabet dynamics is multiFRACTAL both with

and without stimulus, though the multiFRACTALity increases with the stimulus

entropy. This is in sharp contrast to models generating independent spike

intervals, such as models using Poisson statistics, whose dynamics is

monoFRACTAL. We embed the support of the probability measure, which describes the

distribution of words written in this alphabet, in a two-dimensional space, whose

topology can be reproduced by an M-shaped map. This map has positive Lyapunov

exponents, indicating a chaotic-like encoding.

PMID: 17673416 [PubMed - indexed for MEDLINE]

167. Ann Noninvasive Electrocardiol. 2007 Apr;12(2):130-6.

The "Chaos Theory" and nonlinear dynamics in heart rate variability analysis:

does it work in short-time series in patients with coronary heart disease?

Krstacic G(1), Krstacic A, Smalcelj A, Milicic D, Jembrek-Gostovic M.

Author information:

(1)Institute for Cardiovascular Diseases and Rehabilitation, Zagreb, Croatia.

BACKGROUND: Dynamic analysis techniques may quantify abnormalities in heart rate

variability (HRV) based on nonlinear and FRACTAL analysis (chaos theory). The

article emphasizes clinical and prognostic significance of dynamic changes in

short-time series applied on patients with coronary heart disease (CHD) during

the exercise electrocardiograph (ECG) test.

METHODS: The subjects were included in the series after complete cardiovascular

diagnostic data. Series of R-R and ST-T intervals were obtained from exercise ECG

data after sampling digitally. The range rescaled analysis method determined the

FRACTAL dimension of the intervals. To quantify FRACTAL long-range correlation's

properties of heart rate variability, the detrended fluctuation analysis

technique was used. Approximate entropy (ApEn) was applied to quantify the

regularity and complexity of time series, as well as unpredictability of

fluctuations in time series.

RESULTS: It was found that the short-term FRACTAL scaling exponent (alpha(1)) is

significantly lower in patients with CHD (0.93 +/- 0.07 vs 1.09 +/- 0.04; P <

0.001). The patients with CHD had higher FRACTAL dimension in each exercise test

program separately, as well as in exercise program at all. ApEn was significant

lower in CHD group in both RR and ST-T ECG intervals (P < 0.001).

CONCLUSIONS: The nonlinear dynamic methods could have clinical and prognostic

applicability also in short-time ECG series. Dynamic analysis based on chaos

theory during the exercise ECG test point out the multiFRACTAL time series in CHD

patients who loss normal FRACTAL characteristics and regularity in HRV. Nonlinear

analysis technique may complement traditional ECG analysis.

PMID: 17593181 [PubMed - indexed for MEDLINE]

168. Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Mar;75(3 Pt 1):032902. Epub 2007

Mar 12.

BiFRACTALity of human DNA strand-asymmetry profiles results from transcription.

Nicolay S(1), Brodie Of Brodie EB, Touchon M, Audit B, d'Aubenton-Carafa Y,

Thermes C, Arneodo A.

Author information:

(1)Laboratoire Joliot-Curie and Laboratoire de Physique, UMR 5672, CNRS, ENS-Lyon,

46 Allée d'Italie, 69364 Lyon Cedex 07, France.

We use the wavelet transform modulus maxima method to investigate the

multiFRACTAL properties of strand-asymmetry DNA walk profiles in the human

genome. This study reveals the biFRACTAL nature of these profiles, which involve

two competing scale-invariant (up to repeat-masked distances less, or similar 40

kbp) components characterized by Hölder exponents h{1}=0.78 and h{2}=1,

respectively. The former corresponds to the long-range-correlated homogeneous

fluctuations previously observed in DNA walks generated with structural codings.

The latter is associated with the presence of jumps in the original

strand-asymmetry noisy signal S. We show that a majority of upward (downward)

jumps co-locate with gene transcription start (end) sites. Here 7228 human gene

transcription start sites from the refGene database are found within 2 kbp from

an upward jump of amplitude DeltaS > or = 0.1 which suggests that about 36% of

annotated human genes present significant transcription-induced strand asymmetry

and very likely high expression rate.

PMID: 17500744 [PubMed - indexed for MEDLINE]

169. Acad Radiol. 2007 May;14(5):513-21.

FRACTAL analysis of mammographic parenchymal patterns in breast cancer risk


Li H(1), Giger ML, Olopade OI, Lan L.

Author information:

(1)Department of Radiology, The University of Chicago, 5841 S. Maryland Avenue,

Chicago, IL 60637, USA.

Comment in

Acad Radiol. 2007 May;14(5):511-2.

RATIONALE AND OBJECTIVES: To evaluate FRACTAL-based computerized image analyses

of mammographic parenchymal patterns in the task of differentiating between women

at high risk and women at low risk for developing breast cancer.

MATERIALS AND METHODS: The FRACTAL-based texture analyses are based on a

box-counting method and a Minkowski dimension, and were performed within the

parenchymal regions of normal mammograms. Four approaches were evaluated: 1) a

conventional box-counting method, 2) a modified box-counting technique using

linear discriminant analysis (LDA), 3) a global Minkowski dimension, and 4) a

modified Minkowski technique using LDA. These FRACTAL based texture features were

extracted from regions of interest to assess the mammographic parenchymal

patterns of the images. Receiver operating characteristic analysis was used to

evaluate the performance of these features in the task of differentiating between

the two groups of women.

RESULTS: Receiver operating characteristic analysis yielded an A(z) value of 0.74

based on the conventional box-counting technique and an A(z) value of 0.84 based

on the global Minkowski dimension in the task of distinguishing between the two

groups. By using LDA to assess the characteristics of mammograms, A(z) values of

0.90 and 0.93 were obtained in differentiating the two groups, for the modified

box-counting and Minkowski techniques, respectively. Statistically significant

improvement was achieved (P < .05) with the new techniques compared to the

conventional FRACTAL analysis methods. A simulation study, which used the slope

and intercept extracted from the least square fit of the experimental data with

the LDA approaches, yielded A(z) values similar to those obtained with the

conventional approaches in the task of differentiating between the two groups.

CONCLUSIONS: The proposed LDA approach improved significantly the separation

between the two groups based on experimental data. Because this approach was used

as a linear classifier rather than as a regression function, it combined the

FRACTAL analysis with the knowledge of the high- and low-risk patterns, and thus

better characterized the multiFRACTAL nature of the parenchymal patterns. We

believe that the proposed analyses based on the LDA technique to characterize

mammographic parenchymal patterns may potentially yield radiographic markers for

assessing breast cancer risk.

PMID: 17434064 [PubMed - indexed for MEDLINE]

170. Conf Proc IEEE Eng Med Biol Soc. 2005;5:4783-6.

MultiFRACTAL Analysis of Genomic Sequences CGR Images.

Fu W(1), Wang Y, Lu D.

Author information:

(1)Department of Electronic Engineering, Fudan University, Shanghai 200433, China.

To describe the FRACTAL feature of Chaos Game Representation (CGR) images of

genomic sequences, a multiFRACTAL theory is presented in the analysis. With the

probability set of CGR images, the general dimension spectrum and the

multiFRACTAL spectrum are calculated and compared between two sample groups of

gene thick sequences and gene black sequences. The experimental result shows that

the probability set composed of the relative probability has the best

scale-invariance performance. The scale invariance has different variance

regions, which indicates genomic sequence segments with different lengths have

different distribution rules. It is also shown that the sequences, spectra for

two groups are different, specially the attenuation index and value range of the

general dimension spectrum, and the width of the multiFRACTAL spectrum. It is

concluded that the mutiFRACTAL analysis and its parameters may be useful to

analyze sequences's statistic property and recognize gene sequence.

PMID: 17281311 [PubMed]

171. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Dec;74(6 Pt 1):061110. Epub 2006

Dec 12.

Application of the microcanonical multiFRACTAL formalism to monoFRACTAL systems.

Pont O(1), Turiel A, Pérez-Vicente CJ.

Author information:

(1)Departament de Física Fonamental, Universitat de Barcelona, Diagonal, 647, 08028

Barcelona, Spain.

The design of appropriate multiFRACTAL analysis algorithms, able to correctly

characterize the scaling properties of multiFRACTAL systems from experimental,

discretized data, is a major challenge in the study of such scale invariant

systems. In the recent years, a growing interest for the application of the

microcanonical formalism has taken place, as it allows a precise localization of

the FRACTAL components as well as a statistical characterization of the system.

In this paper, we deal with the specific problems arising when systems that are

strictly monoFRACTAL are analyzed using some standard microcanonical multiFRACTAL

methods. We discuss the adaptations of these methods needed to give an

appropriate treatment of monoFRACTAL systems.

PMID: 17280041 [PubMed]

172. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Dec;74(6 Pt 1):061104. Epub 2006

Dec 7.

Detrended fluctuation analysis for FRACTALs and multiFRACTALs in higher


Gu GF(1), Zhou WX.

Author information:

(1)School of Business, East China University of Science and Technology, Shanghai

200237, China.

One-dimensional detrended fluctuation analysis (DFA) and multiFRACTAL detrended

fluctuation analysis (MFDFA) are widely used in the scaling analysis of FRACTAL

and multiFRACTAL time series because they are accurate and easy to implement. In

this paper we generalize the one-dimensional DFA and MFDFA to higher-dimensional

versions. The generalization works well when tested with synthetic surfaces

including fractional Brownian surfaces and multiFRACTAL surfaces. The

two-dimensional MFDFA is also adopted to analyze two images from nature and

experiment, and nice scaling laws are unraveled.

PMID: 17280035 [PubMed]

173. IEEE Trans Biomed Eng. 2006 Oct;53(10):1920-5.

MultiFRACTAL ECG mapping of ventricular epicardium during regional ischemia in

the pig.

Chen Y(1), Nash MP, Ning X, Wang Y, Paterson DJ, Wang J.

Author information:

(1)Department of Electronic Science and Engineering, Nanjing University, Nanjing CO

1051, China.

Myocardial ischemia creates abnormal electrophysiological substrates that can

result in life-threatening ventricular arrhythmias. Early clinical identification

of ischemia in patients is important to managing their condition. We analyzed

electrograms from an ischemia-reperfusion animal model in order to investigate

the relationship between myocardial ischemia and variability of electrocardiogram

(ECG) multiFRACTALity. Ventricular epicardial electropotential maps from the

anesthetized pig during LAD ischemia-reperfusion were analyzed using multiFRACTAL

methods. A new parameter called the singularity spectrum area reference

dispersion (SARD) is presented to represent the temporal evolution of

multiFRACTALity. By contrasting the ventricular epicardial SARD and range of

singularity strength (delta alpha) maps against activation-recovery interval

(ARI) maps, we found that the dispersions of SARD and dleta alpha increased

following the onset of ischemia and decreased with tissue recovery. In addition,

steep spatial gradients of SARD and delta alpha corresponded to locations of

ischemia, although the distribution of multiFRACTALity did not reflect the degree

of myocardial ischemia. However, the multiFRACTALity of the ventricular

epicardial electrograms was useful for classifying the recoverability of ischemic

tissue. Myocardial ischemia significantly influenced the multiFRACTALity of

ventricular electrical activity. Recoverability of ischemic myocardium can be

classified using the multiFRACTALity of ventricular epicardial electrograms. The

location and size of regions of severe ischemic myocardium with poor

recoverability is detectable using these methods.

PMID: 17019855 [PubMed - indexed for MEDLINE]

174. Chaos. 2006 Sep;16(3):033129.

Self-organized critical gating of ion channels: on the origin of long-term memory

in dwell time series.

Brazhe AR(1), Maksimov GV.

Author information:

(1)Biophysics Department, Faculty of Biology, Moscow State University, Moscow,


We present the model of an ion channel, operating in a regime of self-organized

criticality. It is suggested that complex cooperative dynamics takes place in the

protein and the overall tension of it facilitates an open or closed state of the

rigid gates in the pore-making domain. For the first time multiFRACTAL spectra of

ion channel dynamics are presented. Our model well reproduces the multiFRACTAL

properties of ion channel dwell time series and provides an insight on the origin

of the long-term correlations in these series.

PMID: 17014234 [PubMed - indexed for MEDLINE]

175. J Neurosurg Anesthesiol. 2006 Oct;18(4):223-9.

Identification of patients with childhood moyamoya diseases showing temporary

hypertension after anesthesia by preoperative multiFRACTAL Hurst analysis of

heart rate variability.

Yum MK(1), Oh AY, Lee HM, Kim CS, Kim SD, Lee YS, Wang KC, Chung YN, Kim HS.

Author information:

(1)Department of Pediatrics, College of Medicine, Hanyang University, Korea.

OBJECTIVE: This study was performed to determine whether the preoperative

multiFRACTAL Hurst analysis of heart rate variability might identify and

characterize childhood patients with moyamoya disease (MMD) who showed temporary

postoperative hypertension.

METHODS: We studied 59 childhood patients with MMD. Thirty were classified as

hypertensive group when the mean arterial pressure in the postoperative recovery

room was 120% or greater than that during the preoperative period and 29 were

classified as normotensive group. The 2 groups were compared with respect to

preoperative indices of heart rate variability including frequency-domain

measures, approximate entropy, and very short-term multiFRACTAL Hurst exponents

of RR intervals (RRI). Using preoperative indices that showed significant

differences, discriminant analysis was performed to identify postoperative

hypertensive patients.

RESULTS: Only exponents of the order > or =3 (H3alpha, H4alpha, and H5alpha) were

significantly lower in the hypertensive group than in the normotensive group.

Frequency-domain measures, approximate entropy, and the exponents of the order <

or =2 were not significantly different in the 2 groups. Discriminant analysis

using all of the three exponents correctly identified 27/30 (90%) of the

postoperative hypertensive patients.

CONCLUSIONS: Preoperative very short-term multiFRACTAL Hurst analysis of RRI

variability identified 90% of childhood MMD patients who developed postoperative

hypertension. The preoperative characteristic of RRI variability was the reduced

smoothness at the 8-second-long, local RRI regions within which a very large

change of RRI occurs.

PMID: 17006118 [PubMed - indexed for MEDLINE]

176. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jul;74(1 Pt 2):016103. Epub 2006

Jul 6.

Wavelet versus detrended fluctuation analysis of multiFRACTAL structures.

Oświecimka P(1), Kwapień J, Drozdz S.

Author information:

(1)Institute of Nuclear Physics, Polish Academy of Sciences, Kraków, Poland.

We perform a comparative study of applicability of the multiFRACTAL detrended

fluctuation analysis (MFDFA) and the wavelet transform modulus maxima (WTMM)

method in proper detecting of monoFRACTAL and multiFRACTAL character of data. We

quantify the performance of both methods by using different sorts of artificial

signals generated according to a few well-known exactly soluble mathematical

models: monoFRACTAL fractional Brownian motion, biFRACTAL Lévy flights, and

different sorts of multiFRACTAL binomial cascades. Our results show that in the

majority of situations in which one does not know a priori the FRACTAL properties

of a process, choosing MFDFA should be recommended. In particular, WTMM gives

biased outcomes for the fractional Brownian motion with different values of Hurst

exponent, indicating spurious multiFRACTALity. In some cases WTMM can also give

different results if one applies different wavelets. We do not exclude using WTMM

in real data analysis, but it occurs that while one may apply MFDFA in a more

automatic fashion, WTMM must be applied with care. In the second part of our

work, we perform an analogous analysis on empirical data coming from the American

and from the German stock market. For this data both methods detect rich

multiFRACTALity in terms of broad f(alpha), but MFDFA suggests that this

multiFRACTALity is poorer than in the case of WTMM.

PMID: 16907147 [PubMed]

177. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jun;73(6 Pt 2):066125. Epub 2006

Jun 26.

Inhomogeneous sandpile model: Crossover from multiFRACTAL scaling to finite-size


Cernák J.

Author information:

Department of Biophysics, University of P. J. Safárik in Kosice, Jesenná 5,

SK-04000 Kosice, Slovak Republic.

We study an inhomogeneous sandpile model in which two different toppling rules

are defined. For any site only one rule is applied corresponding to either the

Bak, Tang, and Wiesenfeld model [P. Bak, C. Tang, and K. Wiesenfeld, Phys. Rev.

Lett. 59, 381 (1987)] or the Manna two-state sandpile model [S. S. Manna, J.

Phys. A 24, L363 (1991)]. A parameter c is introduced which describes a density

of sites which are randomly deployed and where the stochastic Manna rules are

applied. The results show that the avalanche area exponent tau a, avalanche size

exponent tau s, and capacity FRACTAL dimension Ds depend on the density c. A

crossover from multiFRACTAL scaling of the Bak, Tang, and Wiesenfeld model (c =

0) to finite-size scaling was found. The critical density c is found to be in the

interval 0 < c < 0.01. These results demonstrate that local dynamical rules are

important and can change the global properties of the model.

PMID: 16906932 [PubMed]

178. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jun;73(6 Pt 2):066102. Epub 2006

Jun 1.

Statistical self-similar properties of complex networks.

Lee CY(1), Jung S.

Author information:

(1)The Department of Industrial Information, Kongju National University, Chungnam,

340-702 South Korea.

It has been shown that many complex networks shared distinctive features, which

differ in many ways from the random and the regular networks. Although these

features capture important characteristics of complex networks, their

applicability depends on the type of networks. To unravel ubiquitous

characteristics that complex networks may have in common, we adopt the clustering

coefficient as the probability measure, and present a systematic analysis of

various types of complex networks from the perspective of statistical

self-similarity. We find that the probability distribution of the clustering

coefficient is best characterized by the multiFRACTAL; moreover, the support of

the measure had a FRACTAL dimension. These two features enable us to describe

complex networks in a unified way; at the same time, offer unforeseen

possibilities to comprehend complex networks.

PMID: 16906909 [PubMed]

179. IEEE Trans Med Imaging. 2006 Aug;25(8):1101-7.

MultiFRACTAL analysis of human retinal vessels.

Stosić T(1), Stosić BD.

Author information:

(1)Departamento de Estatísica e Informática, Universidade Federal Rural de

Pernambuco, Dois Irmaos, Recife-PE, Brazil.

In this paper, it is shown that vascular structures of the human retina represent

geometrical multiFRACTALs, characterized by a hierarchy of exponents rather then

a single FRACTAL dimension. A number of retinal images from the STARE database

are analyzed, corresponding to both normal and pathological states of the retina.

In all studied cases, a clearly multiFRACTAL behavior is observed, where capacity

dimension is always found to be larger then the information dimension, which is

in turn always larger then the correlation dimension, all the three being

significantly lower then the diffusion limited aggregation (DLA) FRACTAL

dimension. We also observe a tendency of images corresponding to the pathological

states of the retina to have lower generalized dimensions and a shifted spectrum

range, in comparison with the normal cases.

PMID: 16895002 [PubMed - indexed for MEDLINE]

180. Neuroimage. 2006 Sep;32(3):1158-66. Epub 2006 Jul 11.

MultiFRACTAL analysis of deep white matter microstructural changes on MRI in

relation to early-stage atherosclerosis.

Takahashi T(1), Murata T, Narita K, Hamada T, Kosaka H, Omori M, Takahashi K,

Kimura H, Yoshida H, Wada Y.

Author information:

(1)Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui,

23-3 Shimoaizuki, Matsuoka-cho, Yoshida-gun, Fukui 910-1193, Japan.

MultiFRACTAL analysis based on generalized concepts of FRACTALs has been applied

to evaluate biological tissues composed of complex structures. This type of

analysis can provide a precise quantitative description of a broad range of

heterogeneous phenomena. Previously, we applied multiFRACTAL analysis to describe

heterogeneity in white matter signal fluctuation on T2-weighted MR images as a

new method of texture analysis and established Deltaalpha as the most suitable

index for evaluating white matter structural complexity (Takahashi et al. J.

Neurol. Sci., 2004; 225: 33-37). Considerable evidence suggests that

pathophysiological processes occurring in deep white matter regions may be partly

responsible for cognitive deterioration and dementia in elderly subjects. We

carried out a multiFRACTAL analysis in a group of 36 healthy elderly subjects who

showed no evidence of atherosclerotic risk factors to examine the microstructural

changes of the deep white matter on T2-weighted MR images. We also performed

conventional texture analysis, i.e., determined the standard deviation of signal

intensity divided by mean signal intensity (SD/MSI) for comparison with

multiFRACTAL analysis. Next, we examined the association between the findings of

these two types of texture analysis and the ultrasonographically measured

intima-media thickness (IMT) of the carotid arteries, a reliable indicator of

early carotid atherosclerosis. The severity of carotid IMT was positively

associated with Deltaalpha in the deep white matter region. In addition, this

association remained significant after excluding 12 subjects with visually

detectable deep white matter hyperintensities on MR images. However, there was no

significant association between the severity of carotid IMT and SD/MSI. These

results indicate the potential usefulness of applying multiFRACTAL analysis to

conventional MR images as a new approach to detect the microstructural changes of

apparently normal white matter during the early stages of atherosclerosis.

PMID: 16815037 [PubMed - indexed for MEDLINE]

181. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Mar;73(3 Pt 1):031920. Epub 2006

Mar 21.

Clustering of protein structures using hydrophobic free energy and solvent

accessibility of proteins.

Yu ZG(1), Anh VV, Lau KS, Zhou LQ.

Author information:

(1)Program in Statistics and Operations Research, Queensland University of

Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia.

The hydrophobic free energy and solvent accessibility of amino acids are used to

study the relationship between the primary structure and structural

classification of large proteins. A measure representation and a Z curve

representation of protein sequences are proposed. FRACTAL analysis of the measure

and Z curve representations of proteins and multiFRACTAL analysis of their

hydrophobic free energy and solvent accessibility sequences indicate that the

protein sequences possess correlations and multiFRACTAL scaling. The parameters

from the FRACTAL and multiFRACTAL analyses on these sequences are used to

construct some parameter spaces. Each protein is represented by a point in these

spaces. A method is proposed to distinguish and cluster proteins from the alpha,

beta, alpha + beta, and alpha/beta structural classes in these parameter spaces.

Fisher's linear discriminant algorithm is used to give a quantitative assessment

of our clustering on the selected proteins. Numerical results indicate that the

discriminant accuracies are satisfactory. In particular, they reach 94.12% and

88.89% in separating proteins from {alpha, alpha + beta, alpha/beta} proteins in

a three-dimensional space.

PMID: 16605571 [PubMed - indexed for MEDLINE]

182. Hum Biol. 2005 Oct;77(5):577-617.

Identification of spatial genetic boundaries using a multiFRACTAL model in human

population genetics.

Xue F(1), Wang J, Hu P, Ma D, Liu J, Li G, Zhang L, Wu M, Sun G, Hou H.

Author information:

(1)Department of Epidemiology and Biostatistics, School of Public Health, Shandong

University China, No. 44 Wen-hua-xi-lu Road, Jinan City, Shandong 250012,

People's Republic of China.

There are two purposes in displaying spatial genetic structure. One is that a

visual representation of the variation of the genetic variable should be provided

in the contour map. The other is that spatial genetic structure should be

reflected by the patterns or the gradients with genetic boundaries in the map.

Nevertheless, most conventional interpolation methods, such as Cavalli-Sforza's

method in genography, inverse distance-weighted methods, and the Kriging

technique, focus only on the first primary purpose because of their arbitrary

thresholds marked on the maps. In this paper we present an application of the

contour area multiFRACTAL model (CAMM) to human population genetics. The method

enables the analysis of the geographic distribution of a genetic marker and

provides an insight into the spatial and geometric properties of obtained

patterns. Furthermore, the CAMM may overcome some of the limitations of other

interpolation techniques because no arbitrary thresholds are necessary in the

computation of genetic boundaries. The CAMM is built by establishing power law

relationships between the area A (> or =rho) in the contour map and the value p

itself after plotting these values on a log-log graph. A series of straight-line

segments can be fitted to the points on the log-log graph, each representing a

power law relationship between the area A (> or =rho) and the cutoff genetic

variable value for rho in a particular range. These straight-line segments can

yield a group of cutoff values, which can be identified as the genetic boundaries

that can classify the map of genetic variable into discrete genetic zones. These

genetic zones usually correspond to spatial genetic structure on the landscape.

To provide a better understanding of the interest in the CAMM approach, we

analyze the spatial genetic structures of three loci (ABO, HLA-A, and TPOX) in

China using the CAMM. Each synthetic principal component (SPC) contour map of the

three loci is created by using both Han and minority groups data together. These

contour maps all present an obvious geographic diversity, which gradually

increases from north to south, and show that the genetic differences among

populations in different districts of the same nationality are greater than those

among different nationalities of the same district. It is surprising to find that

both the value of p and the FRACTAL dimension alpha have a clear north to south

gradient for each locus, and the same clear boundary between southern and

northern Asians in each contour map is still seen in the zone of the Yangtze

River, although substantial population migrations have occurred because of war or

famine in the last 2,000 or 3,000 years. A clear genetic boundary between

Europeans and Asians in each contour map is still seen in northwestern China with

a small value of alpha, although the genetic gradient caused by gene flow between

Europeans and Asians has tended to show expansion from northwestern China. From

the three contour maps another interesting result can be found: The values of

alpha north of the Yangtze River are generally less than those south of the

Yangtze River. This indicates that the genetic differences among the populations

north of the Yangtze River are generally smaller than those in populations south

of the Yangtze River.

PMID: 16596942 [PubMed - indexed for MEDLINE]

183. J Math Biol. 2006 Jun;52(6):830-74. Epub 2006 Mar 6.

FRACTAL rigidity by enhanced sympatho-vagal antagonism in heartbeat interval

dynamics elicited by central application of corticotropin-releasing factor in


Meyer M(1), Stiedl O.

Author information:

(1)FRACTAL Physiology, Max Planck Institute for Experimental Medicine, 37075

Göttingen, Germany.

The dynamics of heartbeat interval fluctuations were studied in awake

unrestrained mice following intracerebroventricular application of the

neuropeptide corticotropin-releasing factor (CRF). The cardiac time series

derived from telemetric ECG monitoring were analyzed by non-parametric techniques

of nonlinear signal processing: delay-vector variance (DVV) analysis,

higher-order variability (HOV) analysis, empirical mode decomposition (EMD),

multiscale embedding-space decomposition (MESD), multiexponent multiFRACTAL

(MEMF) analysis. The analyses support the conjecture that cardiac dynamics of

normal control mice has both deterministic and stochastic elements, is

nonstationary, nonlinear, and exerts multiFRACTAL properties. Central application

of CRF results in bradycardia and increased variability of the beat-to-beat

fluctuations. The altered dynamical properties elicited by CRF reflect a

significant loss of intrinsic structural complexity of cardiac control which is

due to central neuroautonomic hyperexcitation, i.e., enhanced sympatho-vagal

antagonism. The change in dynamical complexity is characterized by an effect

referred to as FRACTAL rigidity, leading to a significant impairment of

adaptability to extrinsic challenges in a fluctuating environment. The impact of

dynamical neurocardiopathy as a major precipiting factor for the propensity of

cardiac arrhythmias or sudden cardiac death by unchecked central CRF release in

significant acute life events in man is critically discussed.

PMID: 16521022 [PubMed - indexed for MEDLINE]

184. IEEE Trans Image Process. 2006 Mar;15(3):614-23.

Morphology-based multiFRACTAL estimation for texture segmentation.

Xia Y(1), Feng D, Zhao R.

Author information:

(1)Center for Multimedia Signal Processing, Department of Electronic and Information

Engineering, Hong Kong Polytechnic University, Hong Kong, China.

MultiFRACTAL analysis is becoming more and more popular in image segmentation

community, in which the box-counting based multiFRACTAL dimension estimations are

most commonly used. However, in spite of its computational efficiency, the

regular partition scheme used by various box-counting methods intrinsically

produces less accurate results. In this paper, a novel multiFRACTAL estimation

algorithm based on mathematical morphology is proposed and a set of new

multiFRACTAL descriptors, namely the local morphological multiFRACTAL exponents

is defined to characterize the local scaling properties of textures. A series of

cubic structure elements and an iterative dilation scheme are utilized so that

the computational complexity of the morphological operations can be tremendously

reduced. Both the proposed algorithm and the box-counting based methods have been

applied to the segmentation of texture mosaics and real images. The comparison

results demonstrate that the morphological multiFRACTAL estimation can

differentiate texture images more effectively and provide more robust


PMID: 16519348 [PubMed - indexed for MEDLINE]

185. J Chem Phys. 2006 Feb 14;124(6):64706.

Diffusion-limited deposition with dipolar interactions: FRACTAL dimension and

multiFRACTAL structure.

Tasinkevych M(1), Tavares JM, de Los Santos F.

Author information:

(1)Max-Planck-Institut für Metallforschung, Germany.

Computer simulations are used to generate two-dimensional diffusion-limited

deposits of dipoles. The structure of these deposits is analyzed by measuring

some global quantities: the density of the deposit and the lateral correlation

function at a given height, the mean height of the upper surface for a given

number of deposited particles, and the interfacial width at a given height.

Evidences are given that the FRACTAL dimension of the deposits remains constant

as the deposition proceeds, independently of the dipolar strength. These same

deposits are used to obtain the growth probability measure through the Monte

Carlo techniques. It is found that the distribution of growth probabilities obeys

multiFRACTAL scaling, i.e., it can be analyzed in terms of its f(alpha)

multiFRACTAL spectrum. For low dipolar strengths, the f(alpha) spectrum is

similar to that of diffusion-limited aggregation. Our results suggest that for

increasing the dipolar strength both the minimal local growth exponent alpha(min)

and the information dimension D(1) decrease, while the FRACTAL dimension remains

the same.

PMID: 16483228 [PubMed]

186. IEEE Trans Biomed Eng. 2006 Jan;53(1):83-8.

Local holder exponent analysis of heart rate variability in preterm infants.

Nakamura T(1), Horio H, Chiba Y.

Author information:

(1)Division of Biophysical Engineering, Department of Systems and Human Science,

Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.

Heart rate variability (HRV) displays scale-invariant FRACTAL properties. Recent

studies have revealed multiFRACTAL properties in the healthy human HRV, which

could be characterized by singularities with various strength of local Hölder

exponents embedded in HRV. In this paper, HRV time series from preterm infants,

whose autonomic nervous system undergoes dramatic development, were collected

longitudinally. Changes in FRACTALity/multiFRACTALity of those HRV time series as

the postmenstrual age were examined in order to see if they could quantify

development of the autonomic nervous system. Temporal structure of the

singularities at several representative time scales was also analyzed to show

that intersingular event intervals could be well described by "power law

distribution," and the singular events appeared with age-dependent long-range

correlation in its strength. Detailed analyses suggested that FRACTALity and

multiFRACTALity of HRV, respectively, could quantify the development of the

respiratory center and the parasympathetic nervous system in the preterm infants.

The results obtained in this study might be beneficial for detecting occurrences

of life threatening singular events such as big apnea in preterm infants.

PMID: 16402606 [PubMed - indexed for MEDLINE]

187. Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Oct;72(4 Pt 2):046213. Epub 2005

Oct 20.

Formation of multiFRACTAL population patterns from reproductive growth and local


Ozik J(1), Hunt BR, Ott E.

Author information:

(1)Department of Physics and Institute for Research in Electronics and Applied

Physics, University of Maryland, College Park, Maryland 20742, USA.

We consider the general character of the spatial distribution of a population

that grows through reproduction and subsequent local resettlement of new

population members. We present several simple one- and two-dimensional point

placement models to illustrate possible generic behavior of these distributions.

We show, numerically and analytically, that these models all lead to multiFRACTAL

spatial distributions of population. Additionally, we make qualitative links

between our models and the example of the Earth at Night image, showing the

Earth's nighttime man-made light as seen from space. The Earth at Night data

suffer from saturation of the sensing photodetectors at high brightness

("clipping"), and we account for how this influences the determined dimension

spectrum of the light intensity distribution.

PMID: 16383518 [PubMed - indexed for MEDLINE]

188. Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Oct;72(4 Pt 2):046101. Epub 2005

Oct 3.

MultiFRACTAL structure in nonrepresentational art.

Mureika JR(1), Dyer CC, Cupchik GC.

Author information:

(1)Department of Physics, Loyola Marymount University, Los Angeles, California

90045-8227, USA.

MultiFRACTAL analysis techniques are applied to patterns in several abstract

expressionist artworks, painted by various artists. The analysis is carried out

on two distinct types of structures: the physical patterns formed by a specific

color ("blobs") and patterns formed by the luminance gradient between adjacent

colors ("edges"). It is found that the multiFRACTAL analysis method applied to

"blobs" cannot distinguish between artists of the same movement, yielding a

multiFRACTAL spectrum of dimensions between about 1.5 and 1.8. The method can

distinguish between different types of images, however, as demonstrated by

studying a radically different type of art. The data suggest that the "edge"

method can distinguish between artists in the same movement and is proposed to

represent a toy model of visual discrimination. A "FRACTAL reconstruction"

analysis technique is also applied to the images in order to determine whether or

not a specific signature can be extracted which might serve as a type of

fingerprint for the movement.

PMID: 16383462 [PubMed]

189. Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Oct;72(4 Pt 2):045301. Epub 2005

Oct 14.

Cancellation exponent and multiFRACTAL structure in two-dimensional

magnetohydrodynamics: direct numerical simulations and Lagrangian averaged


Graham JP(1), Mininni PD, Pouquet A.

Author information:

(1)National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado 80307,


We present direct numerical simulations and Lagrangian averaged (also known as

alpha model) simulations of forced and free decaying magnetohydrodynamic

turbulence in two dimensions. The statistics of sign cancellations of the current

at small scales is studied using both the cancellation exponent and the FRACTAL

dimension of the structures. The alpha model is found to have the same scaling

behavior between positive and negative contributions as the direct numerical

simulations. The alpha model is also able to reproduce the time evolution of

these quantities in free decaying turbulence. At large Reynolds numbers, an

independence of the cancellation exponent with the Reynolds numbers is observed.

PMID: 16383461 [PubMed]

190. Biol Cybern. 2006 Feb;94(2):149-56. Epub 2005 Dec 9.

MultiFRACTALity of decomposed EEG during imaginary and real visual-motor


Popivanov D(1), Stomonyakov V, Minchev Z, Jivkova S, Dojnov P, Jivkov S,

Christova E, Kosev S.

Author information:

(1)Institute of Physiology, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.

We test the possible multiFRACTAL properties of dominant EEG frequency

components, when a subject tracks a path on a map, either only by eyes (imaginary

movement - IM) or by visual-motor tracking of discretely moving spot in regular

(RM) and Brownian time-step (BM) (real tracking of moving spot). We check the

hypotheses that the FRACTAL properties of filtered EEG (1) change with respect to

the law of spot movement; (2) differ among filtered EEG components and scalp

sites; (3) differ among real and imaginary tracking. Sixteen right-handed

subjects begin to perform IM, next--real spot tracking (RM and BM) following a

moving spot on streets of a citymap displayed on a computer screen, by push

forward/backward a joystick. Multichannel long-lasting EEG is band-pass filtered

for theta, alpha, beta and gamma oscillations. The

Wavelet-Transform-Modulus-Maxima-Method is applied to reveal multiFRACTALity

[local FRACTAL dimensions Dmax(h)] among task conditions, frequency bands and

sites. Non-parametric statistical estimation of the FRACTAL measures h (Dmax) is

finally applied. MultiFRACTALity is established for all experimental conditions,

EEG components and sites as follows among filtered components - anticorrelation

(h(Dmax) < 0.5) in beta and gamma, and long-range correlation (h(Dmax) > 0.5) for

theta and alpha oscillations; among tasks--for RM and BM, h (Dmax) differ

significantly whereas IM resembles mostly RM; among sites--no significant

difference for local FRACTAL properties is established. The results suggest that

for both imaginary and real visual-motor tracking a line, multiFRACTAL scaling,

specific for lower and higher EEG oscillations, is a very stable intrinsic one

for the activity of large brain areas. The external events (task conditions)

insert weak effect on the scaling.

PMID: 16341722 [PubMed - indexed for MEDLINE]

191. IEEE Trans Image Process. 2005 Oct;14(10):1435-47.

Image denoising based on wavelets and multiFRACTALs for singularity detection.

Zhong J(1), Ning R.

Author information:

(1)Department of Radiology, University of Rochester, Rochester, NY 14642, USA.

This paper presents a very efficient algorithm for image denoising based on

wavelets and multiFRACTALs for singularity detection. A challenge of image

denoising is how to preserve the edges of an image when reducing noise. By

modeling the intensity surface of a noisy image as statistically self-similar

multiFRACTAL processes and taking advantage of the multiresolution analysis with

wavelet transform to exploit the local statistical self-similarity at different

scales, the pointwise singularity strength value characterizing the local

singularity at each scale was calculated. By thresholding the singularity

strength, wavelet coefficients at each scale were classified into two categories:

the edge-related and regular wavelet coefficients and the irregular coefficients.

The irregular coefficients were denoised using an approximate minimum

mean-squared error (MMSE) estimation method, while the edge-related and regular

wavelet coefficients were smoothed using the fuzzy weighted mean (FWM) filter

aiming at preserving the edges and details when reducing noise. Furthermore, to

make the FWM-based filtering more efficient for noise reduction at the lowest

decomposition level, the MMSE-based filtering was performed as the first pass of

denoising followed by performing the FWM-based filtering. Experimental results

demonstrated that this algorithm could achieve both good visual quality and high

PSNR for the denoised images.

PMID: 16238050 [PubMed - indexed for MEDLINE]

192. Proc Biol Sci. 2005 Sep 7;272(1574):1815-22.

Metapopulations in multiFRACTAL landscapes: on the role of spatial aggregation.

Gamarra JG.

Author information:

Department of Natural Resources, Center for the Environment, Cornell University,

103 Rice Hall, Ithaca, NY 14853, USA.

The use of FRACTALs in ecology is currently pervasive over many areas. However,

very few studies have linked FRACTAL properties of landscapes to generating

ecological mechanisms and dynamics. In this study I show that lacunarity (a

measure of the landscape texture) is a well suited ecologically scaled landscape

index that can be explicitly incorporated in metapopulation models such as the

classical Levins equation. I show that the average lacunarity of an aggregated

landscape is linearly correlated to the habitat that a species with local spatial

processed information may perceive. Lacunarity is a computationally feasible

index to measure, and is related to the metapopulation capacity of landscapes. A

general approach to multiFRACTAL landscapes has been conceived, and some

analytical results for self-similar landscapes are outlined, including the

specific effect of landscape heterogeneity, decoupled from that of contagion by

dispersal. Spatially explicit simulations show agreement with the semi-implicit

method presented.

PMCID: PMC1559862

PMID: 16096094 [PubMed - indexed for MEDLINE]

193. Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jul;72(1 Pt 1):011913. Epub 2005

Jul 21.

Volatility of linear and nonlinear time series.

Kalisky T(1), Ashkenazy Y, Havlin S.

Author information:

(1)Minerva Center and Department of Physics, Bar-Ilan University, Ramat-Gan, Israel.

Previous studies indicated that nonlinear properties of Gaussian distributed time

series with long-range correlations, u(i), can be detected and quantified by

studying the correlations in the magnitude series |u(i)|, the "volatility."

However, the origin for this empirical observation still remains unclear and the

exact relation between the correlations in u(i) and the correlations in |u(i)| is

still unknown. Here we develop analytical relations between the scaling exponent

of linear series u(i) and its magnitude series |u(i)|. Moreover, we find that

nonlinear time series exhibit stronger (or the same) correlations in the

magnitude time series compared with linear time series with the same two-point

correlations. Based on these results we propose a simple model that generates

multiFRACTAL time series by explicitly inserting long range correlations in the

magnitude series; the nonlinear multiFRACTAL time series is generated by

multiplying a long-range correlated time series (that represents the magnitude

series) with uncorrelated time series [that represents the sign series sgn

(u(i))]. We apply our techniques on daily deep ocean temperature records from the

equatorial Pacific, the region of the El-Ninõ phenomenon, and find: (i)

long-range correlations from several days to several years with 1/f power

spectrum, (ii) significant nonlinear behavior as expressed by long-range

correlations of the volatility series, and (iii) broad multiFRACTAL spectrum.

PMID: 16090007 [PubMed - indexed for MEDLINE]

194. Phys Rev E Stat Nonlin Soft Matter Phys. 2005 May;71(5 Pt 2):056121. Epub 2005

May 27.

MultiFRACTAL properties of the harmonic measure on Koch boundaries in two and

three dimensions.

Grebenkov DS(1), Lebedev AA, Filoche M, Sapoval B.

Author information:

(1)Laboratoire de Physique de la Matière Condensée, C.N.R.S. Ecole Polytechnique,

91128 Palaiseau, France.

The multiFRACTAL properties of the harmonic measure on quadratic and cubic Koch

boundaries are studied with the help of a new fast random walk algorithm adapted

to these FRACTAL geometries. The conjectural logarithmic development of local

multiFRACTAL exponents is guessed for regular FRACTALs and checked by extensive

numerical simulations. This development allows one to compute the multiFRACTAL

exponents of the harmonic measure with high accuracy, even with the first

generations of the FRACTAL. In particular, the information dimension in the case

of the concave cubic Koch surface embedded in three dimensions is found to be

slightly higher than its value D1 =2 for a smooth boundary.

PMID: 16089616 [PubMed]

195. Chemosphere. 2006 Feb;62(6):934-46. Epub 2005 Aug 2.

Scaling characteristics in ozone concentration time series (OCTS).

Lee CK(1), Juang LC, Wang CC, Liao YY, Yu CC, Liu YC, Ho DS.

Author information:

(1)Department of Environmental Engineering, Green Environment R&D Center, Vanung

University, Chung-Li 320, Taiwan, ROC.

One-year series of hourly average ozone observations, which were obtained from

urban and national park air monitoring stations at Taipei (Taiwan), were analyzed

by means of descriptive statistics and FRACTAL methods to examine the scaling

structures of ozone concentrations. It was found that all ozone measurements

exhibited the characteristic right-skewed frequency distribution, cyclic pattern,

and long-term memory. A mono-FRACTAL analysis was performed by transferring the

ozone concentration time series (OCTS) into a useful compact form, namely, the

box-dimension (D(B))-threshold (T(h)) and critical scale (C(S))-threshold (T(h))

plots. Scale invariance was found in these time series and the box dimension was

shown to be a decreasing function of the threshold ozone level, implying the

existence of multiFRACTAL characteristics. To test this hypothesis, the OCTS were

transferred into the multiFRACTAL spectra, namely, the tau(q)-q plots. The

analysis confirmed the existence of multiFRACTAL characteristics in the

investigated OCTS. A simple two-scale Cantor set with unequal scales and weights

was then used to fit the calculated tau(q)-q plots. This model fitted remarkably

well the entire spectrum of scaling exponents for the examined OCTS. Because the

existence of chaos behavior in OCTS has been reported in the literature, the

possibility of a chaotic multiFRACTAL approach for OCTS characterization was


PMID: 16081138 [PubMed - indexed for MEDLINE]

196. J Neuroeng Rehabil. 2005 Aug 2;2:24.

Fractional Langevin model of gait variability.

West BJ(1), Latka M.

Author information:

(1)Mathematical and Informational Sciences Directorate US Army Research Office,

Research Triangle Park, NC 27709, USA.

The stride interval in healthy human gait fluctuates from step to step in a

random manner and scaling of the interstride interval time series motivated

previous investigators to conclude that this time series is FRACTAL. Early

studies suggested that gait is a monoFRACTAL process, but more recent work

indicates the time series is weakly multiFRACTAL. Herein we present additional

evidence for the weakly multiFRACTAL nature of gait. We use the stride interval

time series obtained from ten healthy adults walking at a normal relaxed pace for

approximately fifteen minutes each as our data set. A fractional Langevin

equation is constructed to model the underlying motor control system in which the

order of the fractional derivative is itself a stochastic quantity. Using this

model we find the FRACTAL dimension for each of the ten data sets to be in

agreement with earlier analyses. However, with the present model we are able to

draw additional conclusions regarding the nature of the control system guiding

walking. The analysis presented herein suggests that the observed scaling in

interstride interval data may not be due to long-term memory alone, but may, in

fact, be due partly to the statistics.

PMCID: PMC1224863

PMID: 16076394 [PubMed]

197. J Chem Phys. 2005 Jun 1;122(21):214725.

MultiFRACTAL analysis of dynamic potential surface of ion-conducting materials.

Habasaki J(1), Ngai KL.

Author information:

(1)Tokyo Institute of Technology, 4259 Nagatsuta-cho, Yokohama 226-8502, Japan.

A multiFRACTAL analysis using singularity spectra [T.C. Halsey et al., Phys. Rev.

A 33, 1141 (1986)] provides a general tool to study the temporal-spatial

properties of particles in complex disordered materials such as ions in ionically

conducting glasses and melts. Obtained by molecular-dynamics simulations, the

accumulated positions of the particles dynamically form a structural pattern

called the dynamical potential surface. In this work, the complex dynamical

potential surfaces of Li ions in the lithium silicates were visualized and

characterized by the multiFRACTAL analysis. The FRACTAL dimensions and strength

of the singularity related to the spatial intermittency of the dynamics are

examined, and the relationship between dynamics and the singularity spectra is


PMID: 15974780 [PubMed]

198. Hypertens Res. 2004 Dec;27(12):911-8.

A consistent abnormality in the average local smoothness of fetal heart rate in

growth-restricted fetuses affected by severe pre-eclampsia.

Yum MK(1), Kim K, Kim JH, Park EY.

Author information:

(1)Department of Pediatrics, School of Medicine, Hanyang University, Seoul, Korea.

An abnormality in cardiovascular regulation during the prenatal period has been

suggested to be the pathophysiological link between fetal growth restriction and

adult hypertension. The purpose of this study was to determine how consistently

abnormal the local smoothness of the very-short-term heart rate is in

growth-restricted fetuses associated with severe pre-eclamptic pregnancy.

MultiFRACTAL Hurst analysis on the structure function of heart rate was performed

in control fetuses (n =150), in fetuses affected by severe pre-eclampsia and not

showing growth restriction (n =66) and in fetuses affected by severe

pre-eclampsia and showing growth restriction (n =58). The very-short-term (< or

=15 heart beats) generalized Hurst exponents of the order of -5 to 5 in three

groups were compared. Each exponent quantifies an average local heart rate

smoothness at 15-successive-heart rate sites, which were specified by the

magnitude of the heart rate variation within the sites determined by and

positively correlated with the order of the exponent. This means that the fetal

heart rates within the sites of q > or =2 have a large fetal heart rate (FHR)

variation, and those within the sites of q < or =-2 have a small FHR variation.

In the fetuses affected by severe pre-eclampsia and not showing growth

restriction, only values of the exponents of the order > or =2 were abnormally

lower. In the fetuses affected by severe pre-eclampsia and showing growth

restriction, the values of the exponents of all orders were abnormally lower. In

conclusion, the local smoothness of heart rate is consistently abnormal

regardless of the magnitude of heart rate variation within a very-short-term

period in growth-restricted fetuses affected by severe pre-eclampsia.

PMID: 15894830 [PubMed - indexed for MEDLINE]

199. Appl Opt. 2005 Feb 1;44(4):527-33.

Superhydrophobic antireflective silica films: FRACTAL surfaces and laser-induced

damage thresholds.

Xu Y(1), Wu D, Sun YH, Huang ZX, Jiang XD, Wei XF, Li ZH, Dong BZ, Wu ZH.

Author information:

(1)State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese

Academy of Sciences, Taiyuan 030001, China.

Several superhydrophobic antireflective silica films have been prepared by a

solgel method that uses hexamethyl-disilizane (HMDS) as a modifier. In a

high-power laser, laser-induced damage thresholds (LIDTs) of 23-30 J/cm2 were

obtained at 1064-nm wavelength with 1-ns pulse duration. By atomic-force

microscopy and optical microscopy, the FRACTAL surfaces of films were studied,

and multiFRACTAL spectra (MFSs) were calculated both before and after laser

damage. The two-sided effect of HMDS on particle growth determined the surface

FRACTAL of a particle and the multiFRACTAL structure of a film's surface. The

bigger deltaalpha was, both before and after laser damage, the lower the LIDT

was. The effect of methyl groups should be included in the determination of the

MFS of the LIDT.

PMID: 15726949 [PubMed]

200. J Theor Biol. 2005 Mar 21;233(2):191-8. Epub 2004 Nov 18.

Middle and long distance athletics races viewed from the perspective of


García-Manso JM(1), Martín-González JM, Dávila N, Arriaza E.

Author information:

(1)Departamento de Educación Física, Facultad de Ciencias de la Actividad Física y

el Deporte, Universidad de Las Palmas de Gran Canaria, 35017 Canary Islands,


Middle and long distance athletics races behave as power-laws when time (or

average speed) and distance are related, thus suggesting the presence of critical

phenomena. Power-laws as a function of the athlete's position in the all-time

world ranking allows us to define a Performance Index that reveals the existence

of possible multiFRACTAL structures associated to the natural barriers to that

the athletes tend in their evolution towards better results and in pursuit of

world records. The new theories of self-organized critical phenomena provide an

explanation for the power-law and FRACTAL structures in systems at, or near,

their critical points. In this paper we analyse the athletic races using these

theories and as a result of this study a new variety of interpretations are


PMID: 15619360 [PubMed - indexed for MEDLINE]

201. Biofizika. 2004 Nov-Dec;49(6):1075-83.

[Calculation of local Hurst exponents in the Ca(2+)-activated K(+)-channel dwell


[Article in Russian]

Brazhe AR, Astashev ME, Maksimov GV, Kazachenko VN, Rubin AB.

A novel method based on the maximum overlap wavelet transform of dwell time

series is proposed. Information on local multiFRACTAL properties of the series,

namely local Hurst exponents or Holder exponents, was obtained. The results

confirm the presence of multiFRACTALity and intrinsic correlations in the

Ca(2+)-activated K+ channel dwell time series. The data on the local multiFRACTAL

structure of the series can be interpreted in terms of processes having

self-organized criticality. The proposed approach allows one to widen the store

of methods for the analysis of single ion channel activity.

PMID: 15612549 [PubMed - indexed for MEDLINE]

202. J Theor Biol. 2005 Feb 21;232(4):559-67.

A FRACTAL method to distinguish coding and non-coding sequences in a complete

genome based on a number sequence representation.

Zhou LQ(1), Yu ZG, Deng JQ, Anh V, Long SC.

Author information:

(1)School of Mathematics and Computing Science, Xiangtan University,Hunan 411105,


A FRACTAL method to distinguish coding and non-coding sequences in a complete

genome is proposed, based on different statistical behaviors between these two

kinds of sequences. We first propose a number sequence representation of DNA

sequences. MultiFRACTAL analysis is then performed on the measure representation

of the obtained number sequence. The three exponents C(-1), C1 and C2 are

selected from the result of multiFRACTAL analysis. Each DNA may be represented by

a point in the three-dimensional space generated by these three-component

vectors. It is shown that points corresponding to coding and non-coding sequences

in the complete genome of many prokaryotes are roughly distributed in different

regions. Fisher's discriminant algorithm can be used to separate these two

regions in the spanned space. If the point (C(-1),C1,C2) for a DNA sequence is

situated in the region corresponding to coding sequences, the sequence is

discriminated as a coding sequence; otherwise, the sequence is classified as a

non-coding one. For all 51 prokaryotes we considered , the average discriminant

accuracies pc,pnc,qc and qnc reach 72.28%, 84.65%, 72.53% and 84.18%,


PMID: 15588636 [PubMed - indexed for MEDLINE]

203. Ultramicroscopy. 2004 Dec;102(1):51-9.

Influence of the atomic force microscope tip on the multiFRACTAL analysis of

rough surfaces.

Klapetek P(1), Ohlídal I, Bílek J.

Author information:

(1)Czech Metrology Institute, Okruzní 31, 638 00 Brno, Czech Republic.

In this paper, the influence of atomic force microscope tip on the multiFRACTAL

analysis of rough surfaces is discussed. This analysis is based on two methods,

i.e. on the correlation function method and the wavelet transform modulus maxima

method. The principles of both methods are briefly described. Both methods are

applied to simulated rough surfaces (simulation is performed by the spectral

synthesis method). It is shown that the finite dimensions of the microscope tip

misrepresent the values of the quantities expressing the multiFRACTAL analysis of

rough surfaces within both the methods. Thus, it was concretely shown that the

influence of the finite dimensions of the microscope tip changed mono-FRACTAL

properties of simulated rough surface to multiFRACTAL ones. Further, it is shown

that a surface reconstruction method developed for removing the negative

influence of the microscope tip does not improve the results obtained in a

substantial way. The theoretical procedures concerning both the methods, i.e. the

correlation function method and the wavelet transform modulus maxima method, are

illustrated for the multiFRACTAL analysis of randomly rough gallium arsenide

surfaces prepared by means of the thermal oxidation of smooth gallium arsenide

surfaces and subsequent dissolution of the oxide films.

PMID: 15556700 [PubMed - indexed for MEDLINE]

204. Biofizika. 2004 Sep-Oct;49(5):852-65.

[FRACTAL properies of gating in potential-dependent K+-channels in Lymnaea

stagnalis neurons].

[Article in Russian]

Kazachenko VN, Kochetkov KV, Astashev ME, Grinevich AA.

Sets of the channel open times, [tau(o)], and closed times, [tau(c)], and the

full set of the channel open and closed times, [tau(o), tau(c)], in the activity

of single voltage-dependent K+-channels in mollusc L. stagnalis neurons were

analyzed using the rescaled range analysis (Hurst method), fast Fourier and

wavelet transforms. It was found that the Hurst dependence for each time series

could be approximated by a polygonal line with at least two slopes: H1 and H2

(Hurst exponents). The averaged values of H1 and H2 for the sets [tau(o), tau(c)]

were equal to 0.61 +/- 0.03 and 0.83 +/- 0.11, respectively; for the [tau(o)]

sets H1 = 0.66 +/- 0.03 and H2 = 0.95 +/- 0.10; for the [tau(c)] sets, H1 = 0.62

+/- 0.05 and H2 = 0.85 +/- 0.10. In some cases, a third slope appeared on the

Hurst dependences. It was very variable and ranged between 0.5 and 1. The Hurst

exponents H1, H2, and H3 characterized short, intermediate, and long time ranges,

respectively. The ranges greatly varied from experiment to experiment. The data

obtained show that the channel openings and closings (gating process) represent a

persistent process correlated in time. The randomization of the time sets

resulted in a single slope, H, of 0.52 +/- 0.02 characteristic of random

processes. The results were confirmed by the fast Fourier and wavelet transforms.

In addition, possible voltage dependences of Hurst exponents and their

correlation with tau(o) and tau(c) were investigated. As a whole, single channel

activity may be characterized as a multiFRACTAL process with a slight voltage

dependence of the Hurst exponents.

PMID: 15526471 [PubMed - indexed for MEDLINE]

205. Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Sep;70(3 Pt 2):035104. Epub 2004

Sep 21.

Where two FRACTALs meet: the scaling of a self-avoiding walk on a percolation


von Ferber C(1), Blavats'ka V, Folk R, Holovatch Y.

Author information:

(1)Theoretische Polymerphysik, Universität Freiburg, D-79104 Freiburg, Germany.

The scaling properties of self-avoiding walks on a d -dimensional diluted lattice

at the percolation threshold are analyzed by a field-theoretical renormalization

group approach. To this end we reconsider the model of Phys. Rev. Lett. 63, 2819

(1989)] and argue that via renormalization its multiFRACTAL properties are

directly accessible. While the former first order perturbation did not agree with

the results of other methods our analytic result gives an accurate description of

the available MC and exact enumeration data in a wide range of dimensions

2</=d</=6 .

PMID: 15524568 [PubMed]

206. J Neurol Sci. 2004 Oct 15;225(1-2):33-7.

Quantitative evaluation of age-related white matter microstructural changes on

MRI by multiFRACTAL analysis.

Takahashi T(1), Murata T, Omori M, Kosaka H, Takahashi K, Yonekura Y, Wada Y.

Author information:

(1)Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui,

Fukui 910-1193, Japan.

MultiFRACTAL analysis has been applied to evaluate biological tissues, which are

composed of complex structures. We carried out multiFRACTAL analyses in a group

of healthy young and elderly subjects to examine age-related white matter

microstructural changes on T2-weighted MR images without any visible abnormal

intensity, and to correlate such changes with age-related cognitive decline.

Comparison between the two age groups showed that Deltaalpha (established as the

most suitable index of heterogeneity in our previous report) in the frontal

region was significantly higher in the elderly group, but no significant group

difference was found in Deltaalpha in the parieto-occipital region. The

Trail-Making Test score (a measure of executive dysfunction) was significantly

higher in the elderly group. In the elderly group, the Trail-Making Test score

was positively correlated with Deltaalpha in the frontal region, but not in the

parieto-occipital region. These results suggest that microstructural changes in

the white matter preferentially occur in the frontal region with normal aging,

and these changes are associated with executive cognitive decline reflective of

frontal-subcortical dysfunction.

PMID: 15465083 [PubMed - indexed for MEDLINE]

207. Phys Rev E Stat Nonlin Soft Matter Phys. 2004;70(1 Pt 2):016306. Epub 2004 Jul


Anomalous diffusion exponents in continuous two-dimensional multiFRACTAL media.

de Dreuzy JR(1), Davy P, Erhel J, de Brémond d'Ars J.

Author information:

(1)Géosciences Rennes, UMR CNRS 6118, Université de Rennes, Campus de Beaulieu,

35042 Rennes Cedex, France.

We study diffusion in heterogeneous multiFRACTAL continuous media that are

characterized by the second-order dimension of the multiFRACTAL spectrum D2,

while the FRACTAL dimension of order 0, D0, is equal to the embedding Euclidean

dimension 2. We find that the mean anomalous and fracton dimensions, d(w) and

d(s), are equal to those of homogeneous media showing that, on average, the key

parameter is the FRACTAL dimension of order 0 D0, equal to the Euclidean

dimension and not to the correlation dimension D2. Beyond their average, the

anomalous diffusion and fracton exponents, d(w) and d(s), are highly variable and

consistently range in the interval [1,4]. d(w) can be consistently either larger

or lower than 2, indicating possible subdiffusive and superdiffusive regimes. On

a realization basis, we show that the exponent variability is related to the

local conductivity at the medium inlet through the conductivity scaling.

PMID: 15324168 [PubMed]

208. Phys Rev E Stat Nonlin Soft Matter Phys. 2004 May;69(5 Pt 1):051919. Epub 2004

May 28.

Hierarchical structure in healthy and diseased human heart rate variability.

Ching ES(1), Lin DC, Zhang C.

Author information:

(1)Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong.

It is shown that the healthy and diseased human heart rate variability (HRV)

possesses a hierarchical structure of the She-Leveque (SL) form. This structure,

first found in measurements in turbulent fluid flows, implies further details in

the HRV multiFRACTAL scaling. The potential of diagnosis is also discussed based

on the characteristics derived from the SL hierarchy.

PMID: 15244859 [PubMed - indexed for MEDLINE]

209. Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Jun;69(6 Pt 2):066135. Epub 2004

Jun 23.

Percolation on a multiFRACTAL.

Corso G(1), Freitas JE, Lucena LS, Soares RF.

Author information:

(1)International Center for Complex Systems and Departamento de Física Teórica e

Experimental, Universidade Federal do Rio Grande do Norte, Campus Universitário

59078 970, Natal, RN, Brazil.

We investigate percolation phenomena in multiFRACTAL objects that are built in a

simple way. In these objects the multiFRACTALity comes directly from the

geometric tiling. We identify some differences between percolation in the

proposed multiFRACTALs and in a regular lattice. There are basically two sources

of these differences. The first is related to the coordination number, which

changes along the multiFRACTAL. The second comes from the way the weight of each

cell in the multiFRACTAL affects the percolation cluster. We use many samples of

finite size lattices and draw the histogram of percolating lattices against site

occupation probability. Depending on a parameter characterizing the multiFRACTAL

and the lattice size, the histogram can have two peaks. We observe that the

percolation threshold for the multiFRACTAL is lower than that for the square

lattice. We compute the FRACTAL dimension of the percolating cluster and the

critical exponent beta. Despite the topological differences, we find that the

percolation in a multiFRACTAL support is in the same universality class as

standard percolation.

PMID: 15244695 [PubMed]

210. Neuroimage. 2004 Jul;22(3):1195-202.

Wavelet-based multiFRACTAL analysis of fMRI time series.

Shimizu Y(1), Barth M, Windischberger C, Moser E, Thurner S.

Author information:

(1)MR Centre of Excellence, Medical University of Vienna, Austria.

Functional magnetic resonance imaging (fMRI) time series are investigated with a

multiFRACTAL method based on the Wavelet Modulus Maxima (WTMM) method to extract

local singularity ("FRACTAL") exponents. The spectrum of singularity exponents of

each fMRI time series is quantified by spectral characteristics including its

maximum and the corresponding dimension. We found that the range of Hölder

exponents in voxels with activation is close to 1, whereas exponents are close to

0.5 in white matter voxels without activation. The maximum dimension decreases

going from white matter to gray matter, and is lower still for activated time

series. The full-width-at-half-maximum of the spectra is higher in activated

areas. The proposed method becomes particularly effective when combining these

spectral characteristics into a single parameter. Using these multiFRACTAL

parameters, it is possible to identify activated areas in the human brain in both

hybrid and in vivo fMRI data sets without knowledge of the stimulation paradigm


Copyright 2004 Elsevier Inc.

PMID: 15219591 [PubMed - indexed for MEDLINE]

211. Neurol Neurochir Pol. 2003 Nov-Dec;37(6):1199-209.

[FRACTAL analysis of MCA blood flow velocity fluctuations in

migraine--preliminary report].

[Article in Polish]

Glaubic-Latka M(1), Latka M, Latka D, Bury W, Pierzchała K.

Author information:

(1)Oddziału Neurologii B Wojewódzkiego Zespołu Neuropsychiatrycznego w Opolu.

Many reports confirm the existence of long-range correlations between

fluctuations of various physiological signals in healthy subjects and demonstrate

disappearance of these correlations in pathological conditions. Blood flow

velocity in intracranial vessels is changeable over time and depends on complex

physiological regulatory mechanisms. The character of blood flow velocity

fluctuations may indicate the presence of vascular disorders associated with

various diseases. The aim of our study was to establish whether fluctuations in

MCA blood flow velocity are FRACTAL in physiological conditions and if so,

whether this feature is lost in migraine, as the role of vasomotoric disturbances

has been already evidenced in pathophysiology of this disease. The axial flow

velocity changes averaged over a cardiac beat interval were monitored

continuously via two channels through the temporal windows using a DWL Multi-DopT

TCD device with 2-MHz probes. The examinations were performed in supine rest in

two-hour periods in two groups: of 7 patients with clinically confirmed migraine

with aura during headache-free intervals (15 recordings), and in the control

group of 4 young, healthy volunteers (10 recordings). The results in the form of

time series were analysed using the methods of FRACTAL statistics.

MultiFRACTALity in the recordings in physiological conditions was clearly

confirmed, as well as its absence in the averaged recordings in the group of

migraneurs. The findings justify a supposition that the breakdown of multiFRACTAL

properties of MCA blood flow time series in migraine may result from the

vasomotor disturbances present even during headache-free intervals. However,

possible usefulness of this method in the diagnostics of migraine requires

further investigation.

PMID: 15174233 [PubMed - indexed for MEDLINE]

212. Comput Med Imaging Graph. 2004 Jun;28(4):203-11.

A digital reference model of the human bronchial tree.

Schmidt A(1), Zidowitz S, Kriete A, Denhard T, Krass S, Peitgen HO.

Author information:

(1)Image Processing Laboratory, Institute of Anatomy and Cell Biology,

Justus-Liebig-University, Aulweg 123, 35385 Giessen, Germany.

In-vitro preparations of the human lung combined with high-resolution tomography

can be used to derive precise models of the human lung. To develop an abstract

graph representation, specially adapted image processing algorithms were applied

to segment and delineate the bronchi. The graph thus obtained contains

topological information about spatial coordinates, connectivities, diameters and

branching angles of 1453 bronchi up to the 17th Horsfield order. The graph was

analyzed for statistical and FRACTAL properties and was compared with current

models. Results indicate a model that exhibits asymmetry and multiFRACTAL

properties. This newly established reference model is an important step forward

in geometrical accuracy of the bronchial tree representation that will improve

both analysis of lung images in clinical imaging and the realism of functional


PMID: 15121209 [PubMed - indexed for MEDLINE]

213. Eur Biophys J. 2004 Oct;33(6):535-42. Epub 2004 Mar 16.

Patterning of endocytic vesicles and its control by voltage-gated Na+ channel

activity in rat prostate cancer cells: FRACTAL analyses.

Krasowska M(1), Grzywna ZJ, Mycielska ME, Djamgoz MB.

Author information:

(1)Neuroscience Solutions to Cancer Research Group, Department of Biological

Sciences, Imperial College London, Sir Alexander Fleming Building, South

Kensington Campus, London, SW7 2AZ, UK.

FRACTAL methods were used to analyze quantitative differences in secretory

membrane activities of two rat prostate cancer cell lines (Mat-LyLu and AT-2) of

strong and weak metastatic potential, respectively. Each cell's endocytic

activity was determined by horseradish peroxidase uptake. Digital images of the

patterns of vesicular staining were evaluated by multiFRACTAL analyses:

generalized FRACTAL dimension (Dq) and its Legendre transform f(alpha), as well

as partitioned iterated function system -- semiFRACTAL (PIFS-SF) analysis. These

approaches revealed consistently that, under control conditions, all multiFRACTAL

parameters and PIFS-SF codes determined had values greater for Mat-LyLu compared

with AT-2 cells. This would agree generally with the endocytic/vesicular activity

of the strongly metastatic Mat-LyLu cells being more developed than the

corresponding weakly metastatic AT-2 cells. All the parameters studied were

sensitive to tetrodotoxin (TTX) pre-treatment of the cells, which blocked

voltage-gated Na+ channels (VGSCs). Some of the parameters had a "simple"

dependence on VGSC activity, whereby pre-treatment with TTX reduced the values

for the MAT-LyLu cells and eliminated the differences between the two cell lines.

For other parameters, however, there was a "complex" dependence on VGSC activity.

The possible physical/physiological meaning of the mathematical parameters

studied and the nature of involvement of VGSC activity in control of

endocytosis/secretion are discussed.

PMID: 15024523 [PubMed - indexed for MEDLINE]

214. Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Jan;69(1 Pt 2):016309. Epub 2004

Jan 29.

Dual multiFRACTAL spectra.

Roux S(1), Jensen MH.

Author information:

(1)Laboratoire Surface du Verre et Interfaces, UMR CNRS/Saint-Gobain, 39 quai Lucien

lefranc, 93303 Aubervilliers cedex, France.

The multiFRACTAL formalism characterizes the scaling properties of a physical

density rho as a function of the distance L. To each singularity alpha of the

field is attributed a FRACTAL dimension for its support f(alpha). An alternative

representation has been proposed by considering the distribution of distances

associated to a fixed mass. Computing these spectra for a multiFRACTAL Cantor

set, it is shown that these two approaches are dual to each other, and that both

spectra as well as the moment scaling exponents are simply related. We apply the

same inversion formalism to exponents obtained for turbulent statistics in the

Gledzer-Ohkitani-Yamada shell model and observe that the same duality relation

holds here.

PMID: 14995714 [PubMed]

215. Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Jan;69(1 Pt 1):011403. Epub 2004

Jan 27.

Diffusion-limited aggregation with power-law pinning.

Hentschel HG(1), Popescu MN, Family F.

Author information:

(1)Department of Physics, Emory University, Atlanta, Georgia 30322, USA.

Using stochastic conformal mapping techniques we study the patterns emerging from

Laplacian growth with a power-law decaying threshold for growth R(-gamma)(N)

(where R(N) is the radius of the N-particle cluster). For gamma>1 the growth

pattern is in the same universality class as diffusion limited aggregation (DLA),

while for gamma<1 the resulting patterns have a lower FRACTAL dimension D(gamma)

than a DLA cluster due to the enhancement of growth at the hot tips of the

developing pattern. Our results indicate that a pinning transition occurs at

gamma=1/2, significantly smaller than might be expected from the lower bound

alpha(min) approximately 0.67 of multiFRACTAL spectrum of DLA. This limiting case

shows that the most singular tips in the pruned cluster now correspond to those

expected for a purely one-dimensional line. Using multiFRACTAL analysis, analytic

expressions are established for D(gamma) both close to the breakdown of DLA

universality class, i.e., gamma less, similar 1, and close to the pinning

transition, i.e., gamma greater, similar 1/2.

PMID: 14995617 [PubMed]

216. J Biol Phys. 2004 Mar;30(1):33-81. doi: 10.1023/B:JOBP.0000016438.86794.8e.

Wavelet Analysis of DNA Bending Profiles reveals Structural Constraints on the

Evolution of Genomic Sequences.

Audit B(1), Vaillant C, Arnéodo A, d'Aubenton-Carafa Y, Thermes C.

Author information:

(1)Centre de Recherche Paul Pascal, avenue Schweitzer, 33600 Pessac, France.

Analyses of genomic DNA sequences have shown in previous works that base pairs

are correlated at large distances with scale-invariant statistical properties. We

show in the present study that these correlations between nucleotides (letters)

result in fact from long-range correlations (LRC) between sequence-dependent DNA

structural elements (words) involved in the packaging of DNA in chromatin. Using

the wavelet transform technique, we perform a comparative analysis of the DNA

text and of the corresponding bending profiles generated with curvature tables

based on nucleosome positioning data. This exploration through the optics of the

so-called `wavelet transform microscope' reveals a characteristic scale of

100-200 bp that separates two regimes of different LRC. We focus here on the

existence of LRC in the small-scale regime (≲ 200 bp). Analysis of genomes in the

three kingdoms reveals that this regime is specifically associated to the

presence of nucleosomes. Indeed, small scale LRC are observed in eukaryotic

genomes and to a less extent in archaeal genomes, in contrast with their absence

in eubacterial genomes. Similarly, this regime is observed in eukaryotic but not

in bacterial viral DNA genomes. There is one exception for genomes of Poxviruses,

the only animal DNA viruses that do not replicate in the cell nucleus and do not

present small scale LRC. Furthermore, no small scale LRC are detected in the

genomes of all examined RNA viruses, with one exception in the case of

retroviruses. Altogether, these results strongly suggest that small-scale LRC are

a signature of the nucleosomal structure. Finally, we discuss possible

interpretations of these small-scale LRC in terms of the mechanisms that govern

the positioning, the stability and the dynamics of the nucleosomes along the DNA

chain. This paper is maily devoted to a pedagogical presentation of the

theoretical concepts and physical methods which are well suited to perform a

statistical analysis of genomic sequences. We review the results obtained with

the so-called wavelet-based multiFRACTAL analysis when investigating the DNA

sequences of various organisms in the three kingdoms. Some of these results have

been announced in B. Audit et al. [1, 2].

PMCID: PMC3456503

PMID: 23345861 [PubMed]

217. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Dec;68(6 Pt 1):061509. Epub 2003

Dec 24.

FRACTAL patterns, cluster dynamics, and elastic properties of magnetorheological


Carrillo JL(1), Donado F, Mendoza ME.

Author information:

(1)Instituto de Física de la Universidad Autónoma de Puebla, Apartado Postal J-48,

Puebla 72570, Puebla, México.

We study pattern formation and the aggregation processes in magnetorheological

suspensions in the presence of a static magnetic field, and some of their

associated physical properties. In particular, we analyze the elastic modes as a

function of the intensity of the applied field and for several particle

concentrations. We observe that the clusters formed in these systems have

multiFRACTAL characteristics, which are the result of three well defined stages

of the aggregation process. In these stages three generations of clusters are

produced sequentially. The structure of the suspension can be well characterized

by its mass FRACTAL dimensions and the mass radial distribution. The size

distribution of the second-generation clusters written in terms of their mass

FRACTAL dimension allows us to calculate the sound speed of the longitudinal

modes in the large wavelength regime. This multiFRACTAL analysis applied to

several kinds of aggregates reveals that the occurrence of at least three stages

of aggregation is a common feature to several physical aggregation processes.

PMID: 14754214 [PubMed]

218. J Theor Biol. 2004 Feb 7;226(3):341-8.

Chaos game representation of protein sequences based on the detailed HP model and

their multiFRACTAL and correlation analyses.

Yu ZG(1), Anh V, Lau KS.

Author information:

(1)Program in Statistics and Operations Research, Queensland University of

Technology, G.P.O. Box 2434, QLD 4001, Brisbane, Australia

Similar to the chaos game representation (CGR) of DNA sequences proposed by

Jeffrey (Nucleic Acid Res. 18 (1990) 2163), a new CGR of protein sequences based

on the detailed HP model is proposed. MultiFRACTAL and correlation analyses of

the measures based on the CGR of protein sequences from complete genomes are

performed. The Dq spectra of all organisms studied are multiFRACTAL-like and

sufficiently smooth for the Cq curves to be meaningful. The Cq curves of bacteria

resemble a classical phase transition at a critical point. The correlation

distance of the difference between the measure based on the CGR of protein

sequences and its FRACTAL background is also proposed to construct a more precise

phylogenetic tree of bacteria.

PMID: 14643648 [PubMed - indexed for MEDLINE]

219. Int J Neurosci. 2003 Nov;113(11):1615-39.

Regular developmental changes in EEG multiFRACTAL characteristics.

Polonnikov RI(1), Wasserman EL, Kartashev NK.

Author information:

(1)Saint Petersburg Institute for Informatics and Automation of Russian Academy of

Sciences, Saint Petersburg, Russia.

Electroencephalograms (EEGs) of 110 pupils (aged 6.5-19.5 years; 48 healthy

subjects, 51 with cerebral palsy, 11 with acquired cerebral defect) were

acquired. The stable age dependences of averaged parameters of k x f-beta EEG

spectra model, deviations from the model, and normalized ranges of detrended EEGs

were found. These dependences were observed in both healthy subjects and

patients, in males and females, in the cases of congenital and acquired

pathology. This regularity reflects the process of cerebral maturation and

developmental change of structure types of the EEG process, and it is inherent to

normal as well as to abnormal brain development.

PMID: 14585757 [PubMed - indexed for MEDLINE]

220. Med Biol Eng Comput. 2003 Sep;41(5):543-9.

Multi- and monoFRACTAL indices of short-term heart rate variability.

Fischer R(1), Akay M, Castiglioni P, Di Rienzo M.

Author information:

(1)Department of Biomedical Engineering, Rutgers University, Piscataway, USA.

Indices of heart rate variability (HRV) based on FRACTAL signal models have

recently been shown to possess value as predictors of mortality in specific

patient populations. To develop more powerful clinical indices of HRV based on a

FRACTAL signal model, the study investigated two HRV indices based on a

monoFRACTAL signal model called fractional Brownian motion and an index based on

a multiFRACTAL signal model called multifractional Brownian motion. The

performance of the indices was compared with an HRV index in common clinical use.

To compare the indices, 18 normal subjects were subjected to postural changes,

and the indices were compared on their ability to respond to the resulting

autonomic events in HRV recordings. The magnitude of the response to postural

change (normalised by the measurement variability) was assessed by analysis of

variance and multiple comparison testing. Four HRV indices were investigated for

this study: the standard deviation of all normal R-R intervals; an HRV index

commonly used in the clinic; detrended fluctuation analysis, an HRV index found

to be the most powerful predictor of mortality in a study of patients with

depressed left ventricular function; an HRV index developed using the maximum

likelihood estimation (MLE) technique for a monoFRACTAL signal model; and an HRV

index developed for the analysis of multifractional Brownian motion signals. The

HRV index based on the MLE technique was found to respond most strongly to the

induced postural changes (95% CI). The magnitude of its response (normalised by

the measurement variability) was at least 25% greater than any of the other

indices tested.

PMID: 14572004 [PubMed - indexed for MEDLINE]

221. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Aug;68(2 Pt 1):021913. Epub 2003

Aug 22.

MultiFRACTAL and correlation analyses of protein sequences from complete genomes.

Yu ZG(1), Anh V, Lau KS.

Author information:

(1)Program in Statistics and Operations Research, Queensland University of

Technology, GPO Box 2434, Brisbane Q4001, Australia.

A measure representation of protein sequences similar to the measure

representation of DNA sequences proposed in our previous paper [Yu et al., Phys.

Rev. E 64, 031903 (2001)] and another induced measure are introduced.

MultiFRACTAL analysis is then performed on these two kinds of measures of a large

number of protein sequences derived from corresponding complete genomes. From the

values of the D(q) (generalized dimensions) spectra and related C(q) (analogous

specific heat) curves, it is concluded that these protein sequences are not

completely random sequences. For substrings with length K=5, the D(q) spectra of

all organisms studied are multiFRACTAL-like and sufficiently smooth for the C(q)

curves to be meaningful. The C(q) curves of all bacteria resemble a classical

phase transition at a critical point. But the "analogous" phase transitions of

higher organisms studied exhibit the shape of double-peaked specific heat

function. But for the classification problem, the multiFRACTAL property is not

sufficient. When the measure representations of protein sequences from complete

genomes are considered as time series, a method based on correlation analysis

after removing some memory from the time series is proposed to construct a

phylogenetic tree. This construction is shown to be reasonably satisfactory.

PMID: 14525012 [PubMed - indexed for MEDLINE]

222. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Sep;68(3 Pt 2):036129. Epub 2003

Sep 24.

Logarithmic corrections to scaling in critical percolation and random resistor


Stenull O(1), Janssen HK.

Author information:

(1)Department of Physics and Astronomy, University of Pennsylvania, Philadelphia,

Pennsylvania 19104, USA.

We study the critical behavior of various geometrical and transport properties of

percolation in six dimensions. By employing field theory and renormalization

group methods we analyze fluctuation induced logarithmic corrections to scaling

up to and including the next-to-leading order correction. Our study comprehends

the percolation correlation function, i.e., the probability that two given points

are connected, and some of the FRACTAL masses describing percolation clusters. To

be specific, we calculate the mass of the backbone, the red bonds, and the

shortest path. Moreover, we study key transport properties of percolation as

represented by the random resistor network. We investigate the average two-point

resistance as well as the entire family of multiFRACTAL moments of the current


PMID: 14524854 [PubMed]

223. Eur J Appl Physiol. 2003 Oct;90(3-4):305-16. Epub 2003 Aug 27.

Self-affine FRACTAL variability of human heartbeat interval dynamics in health

and disease.

Meyer M(1), Stiedl O.

Author information:

(1)Max Planck Institute for Experimental Medicine, Hermann-Rein Str 3, 37075

Göttingen, Germany.

The complexity of the cardiac rhythm is demonstrated to exhibit self-affine

multiFRACTAL variability. The dynamics of heartbeat interval time series was

analyzed by application of the multiFRACTAL formalism based on the Cramèr theory

of large deviations. The continuous multiFRACTAL large deviation spectrum

uncovers the nonlinear FRACTAL properties in the dynamics of heart rate and

presents a useful diagnostic framework for discrimination and classification of

patients with cardiac disease, e.g., congestive heart failure. The characteristic

multiFRACTAL pattern in heart transplant recipients or chronic heart disease

highlights the importance of neuroautonomic control mechanisms regulating the

FRACTAL dynamics of the cardiac rhythm.

PMID: 12942331 [PubMed - indexed for MEDLINE]

224. Health Phys. 2003 Sep;85(3):330-42.

Application of FRACTAL and morphological methods in radioecology.

Makarenko N(1), Karimova L, Novak MM.

Author information:

(1)Institute of Mathematics, 480100 Almaty, Kazakhstan.

Effective management of radioactive contamination requires comprehensive

knowledge of pollutants' characteristics. The complicated character of the

problem is due to a number of issues, such as the very wide range of

contamination, the presence of a mixture of radioactive isotopes, the highly

variable diffusion of radionuclides in soil, water, and air, and the effect of

climatic conditions. The resultant field has an irregular mosaic structure, which

restricts the choice of measurement methods and data processing. In view of this,

application of classical statistics techniques is often inappropriate in modeling

such an environment. Application of the tools of FRACTAL and stochastic geometry

provides a good insight and helps to distinguish between distribution

characteristics of natural and man-made isotopes. Several techniques are

implemented to determine scaling aspects of contaminated fields. The discovery of

multiFRACTAL scaling leads to the hierarchical structure of contamination spots

on different scales and intensity and places restrictions on the measurement net

for detecting anomalies. The method of stochastic geometry further demonstrates

that topological characteristics of contamination fields differ from those of the

Gaussian fields and the topology of man-made isotopes differs from natural ones.

PMID: 12938723 [PubMed - indexed for MEDLINE]

225. Acta Med Okayama. 2003 Apr;57(2):49-52.

Variations of multiFRACTAL structure in the fetal heartbeats.

Miyagi Y(1), Miyagi Y, Terada S, Kudo T.

Author information:

(1)Department of Obstetrics and Gynecology, Okayama University Graduate School of

Medicine and Dentistry, Okayama 700-8558, Japan.

Several procedures for evaluating fetal well-being are in clinical use. The

cardiotocograph is mostly used as a non-invasive procedure to measure fetal

well-being in clinical settings. The cardiotocograph displays the fetal heartbeat

counts that vibrate. This variation has been classified into 2 categories. We

investigated this variation by a novel method, in which we analyzed the change of

structure of the attractors in the phase spaces according to the time course. We

adopted the global spectrum, which means the distribution of FRACTAL dimensions,

for that structure. In this procedure, we discovered a new variation in which the

cycle is much longer than the 2 types of known variabilities. Although loud

noises such as white noises with a magnitude 1/4 times as large as the standard

deviation of the original data were added to the original data, the variations

were still detected. The variation is very difficult to detect by Fourier or

wavelet transformation, however, because it changes very slowly. Through this new

way of analyzing the vibration phenomena, we obtained a new perspective on the

biological information available.

PMID: 12866743 [PubMed - indexed for MEDLINE]

226. Dokl Biol Sci. 2003 Mar-Apr;389:143-6.

MultiFRACTAL analysis of the species structure of biotic communities.

Iudin DI(1), Gelashvili DB, Rozenberg GS.

Author information:

(1)Lobachevsky Nizhni Novgorod State University, Nizhni Novgorod, Russia.

PMID: 12854413 [PubMed - indexed for MEDLINE]

227. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Apr;67(4 Pt 1):042402. Epub 2003

Apr 17.

Scaling exponent of the maximum growth probability in diffusion-limited


Jensen MH(1), Mathiesen J, Procaccia I.

Author information:

(1)The Niels Bohr Institute, Blegdamsvej 17, Copenhagen, Denmark.

An early (and influential) scaling relation in the multiFRACTAL theory of

diffusion limited aggregation (DLA) is the Turkevich-Scher conjecture that

relates the exponent alpha(min) that characterizes the "hottest" region of the

harmonic measure and the FRACTAL dimension D of the cluster, i.e.,

D=1+alpha(min). Due to lack of accurate direct measurements of both D and

alpha(min), this conjecture could never be put to a serious test. Using the

method of iterated conformal maps, D was recently determined as D=1.713+/-0.003.

In this paper, we determine alpha(min) accurately with the result

alpha(min)=0.665+/-0.004. We thus conclude that the Turkevich-Scher conjecture is

incorrect for DLA.

PMID: 12786408 [PubMed]

228. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 May;67(5 Pt 1):051917. Epub 2003

May 20.

Nonlinear dynamical model of human gait.

West BJ(1), Scafetta N.

Author information:

(1)Pratt School of EE Department, Duke University, and Mathematics Division, Army

Research Office, Research Triangle Park, North Carolina, USA.

We present a nonlinear dynamical model of the human gait control system in a

variety of gait regimes. The stride-interval time series in normal human gait is

characterized by slightly multiFRACTAL fluctuations. The FRACTAL nature of the

fluctuations becomes more pronounced under both an increase and decrease in the

average gait. Moreover, the long-range memory in these fluctuations is lost when

the gait is keyed on a metronome. Human locomotion is controlled by a network of

neurons capable of producing a correlated syncopated output. The central nervous

system is coupled to the motocontrol system, and together they control the

locomotion of the gait cycle itself. The metronomic gait is simulated by a forced

nonlinear oscillator with a periodic external force associated with the conscious

act of walking in a particular way.

PMID: 12786188 [PubMed - indexed for MEDLINE]

229. Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 2):036702. Epub 2003

Mar 24.

Models for correlated multiFRACTAL hypersurfaces.

Tavares DM(1), Lucena LS.

Author information:

(1)International Center for Complex Systems and Departamento de Física Teórica e

Experimental-UFRN, Natal-RN 59078-970, Brazil.

We discuss and implement computer approximations of FRACTAL and multiFRACTAL

hypersurfaces. These hypersurfaces consist of reconstructions of a stochastic

process in the real space from randomly distributed variables in the discrete

wavelet domain. The synthetic surfaces have the usual fractional Brownian motion

as a particular case, and inherit the correlation structure of these FRACTALs. We

first introduce the one-dimensional version of these surfaces that obey a weak

self-affine symmetry. This symmetry appears in the wavelet domain as a condition

on the second moments of the probability distributions of the wavelet

coefficients. Then we use these relations to define the FRACTALs and

multiFRACTALs in d dimensions. Finally, we concentrate on the generation of

samples of these hypersurfaces.

PMID: 12689197 [PubMed]

230. Phys Rev E Stat Nonlin Soft Matter Phys. 2002 Dec;66(6 Pt 1):061906. Epub 2002

Dec 18.

MultiFRACTAL analysis of DNA walks and trails.

Rosas A(1), Nogueira E Jr, Fontanari JF.

Author information:

(1)Instituto de Física de São Carlos, Universidade de São Paulo, Caixa Postal 369,

13560-970 São Carlos, SP, Brazil.

The characterization of the long-range order and FRACTAL properties of DNA

sequences has proved a difficult though rewarding task mainly due to the mosaic

character of DNA consisting of many interwoven patches of various lengths with

different nucleotide constitutions. We apply here a recently proposed

generalization of the detrended fluctuation analysis method to show that the DNA

walk construction, in which the DNA sequence is viewed as a time series, exhibits

a monoFRACTAL structure regardless of the existence of local trends in the

series. In addition, we point out that the monoFRACTAL structure of the DNA walks

carries over to an apparently alternative graphical construction given by the

projection of the DNA walk into the d spatial coordinates, termed DNA trails. In

particular, we calculate the FRACTAL dimension D(t) of the DNA trails using a

well-known result of FRACTAL theory linking D(t) to the Hurst exponent H of the

corresponding DNA walk. Comparison with estimates obtained by the standard

box-counting method allows the evaluation of both finite-length and local trends


PMID: 12513317 [PubMed - indexed for MEDLINE]

231. J Theor Biol. 2003 Jan 7;220(1):75-82.

The multiFRACTAL structure of arterial trees.

Grasman J(1), Brascamp JW, Van Leeuwen JL, Van Putten B.

Author information:

(1)Wageningen University and Research Centre, Biometrics, Postbus 100, 6700 AC

Wageningen, The Netherlands.

FRACTAL properties of arterial trees are analysed using the cascade model of

turbulence theory. It is shown that the branching process leads to a non-uniform

structure at the micro-level meaning that blood supply to the tissue varies in

space. From the model it is concluded that, depending on the branching parameter,

vessels of a specific size contribute dominantly to the blood supply of tissue.

The corresponding tissue elements form a dense set in the tissue. Furthermore, if

blood flow in vessels can get obstructed with some probability, the above set of

tissue elements may not be dense anymore. Then there is the risk that, spread out

over the tissue, nutrient and gas exchange fall short.

Copyright 2003 Elsevier Science Ltd.

PMID: 12453452 [PubMed - indexed for MEDLINE]

[Dr. Pellionisz is legally permitted to practice Compensated Professional Services (Analysis, Advisorship, Consultantship, Board Membership, etc) as long as there is no "Conflict of Interest", through holgentech_at_gmail_dot_com.

Communication regarding Intellectual Property of any kind, including but not limited to patents, trade secrets, know-how associated with Dr. Pellionisz must be strictly gated by "Attorney Kevin Roe, Esq. FractoGene Legal Department", mailing address (USPS/UPS/FedEx) "155 E Campbell Ave, Campbell, CA 95008"]

23andMe aims to be Google for genetic research

By Heather

POSTED: 09/06/2014 05:00:28 PM UPDATED: 5 DAYS AGO

MOUNTAIN VIEW -- In less than a decade, biotech company 23andMe has turned a refrigerator full of spit into one of the largest databases of personal genetics information in the world.

The brainchild of Anne Wojcicki, the wife of Google co-founder Sergey Brin, 23andMe began in 2006 as a startup mailing DNA testing kits to customers' front doors and asking them to mail back a vial of saliva. Eight years later, the company is the gatekeeper of a database of hundreds of thousands of people's DNA -- a self-described Google for genetics information.

"It's actually bigger than anything else I can think of, way bigger," said Lisa Brooks, program director of the National Human Genome Research Institute, part of the National Institutes of Health.

23andMe has begun selling that genetics data to researchers and pharmaceutical companies to conduct large-scale medical studies, making it an emerging leader in a largely underexplored, and at times hotly debated, area of scientific research. In the last couple of months, 23andMe has announced a joint effort with Pfizer to research inflammatory bowel disease, released findings from a joint study of more than 100,000 people that made new discoveries on Parkinson's disease, and received a $1.4 million grant from the NIH.

But as the guardian of a very lucrative set of data -- the accuracy of which has come under question -- critics say the Mountain View company also may pose a threat to consumers' privacy.

Most medical studies take months or years to solicit enough volunteers. But 23andMe puts the genetic information of 700,000 people at researchers' fingertips, allowing medical studies to be fast-tracked and new treatments to make their way into hospitals sooner, experts say, giving patients with chronic diseases a better quality of life.

"Instead of actually having to do clinical trials the old-fashioned way, we can enable researchers to get their answers instantaneously," Wojcicki said in an interview with this newspaper. "And they pay us for that."

But some experts worry 23andMe users have no idea where their own genetic information will end up. Because the company is relying on data sales to become profitable -- selling $99 home genetic testing kits doesn't pull in the big-dollar revenue -- 23andMe may disseminate consumers' genetic information not only to government agencies and research institutions, say legal and bioethics experts, but also to big pharmaceutical companies, marketers and advertisers.

"There are a lot of people who would want to use that data. There's a lot of money potentially locked up in that data," said Charles Seife, a professor at New York University and longtime science writer.

Indeed, in a 2013 interview with The New York Times, Wojcicki said, "I remember in the early days of Google, Larry (Page) would say, 'I just want the world's data on my laptop.' I feel the same way about health care. I want the world's data accessible."

Some research experts also question the accuracy of 23andMe's data, which it collects through surveys it sends to customers, asking about their family and medical histories.

The validity of these studies "is going to depend on the accuracy of the medical information in 23andMe's database," said Dr. Paul Appelbaum, director of the Division of Law, Ethics and Psychiatry at Columbia University. "The information 23andMe has is exclusively self-reported, so how accurate it is will become a critical point."

Regardless, the NIH and the companies buying the data don't see a problem: "It doesn't need to be perfect to be helpful," said Brooks of the NIH. "23andMe has managed at no cost to the government to amass a very large set of data on people."

23andMe, which has raised more than $126 million and has the backing of Google's venture arm and investments from Brin, as well as Russian billionaire and Facebook and Twitter investor Yuri Milner, has proved a much more powerful research engine than almost any public effort to understand human genetics, which tend to suffer from underfunding. By comparison, a national genetics study in the United Kingdom is collecting DNA from 500,000 people, and the NIH genome project has 1,000 genome samples.

The NIH grant will allow 23andMe to further expand and refine its database so that it will eventually become a portal of genetics information researchers can access with a keystroke.

The boost from the NIH followed a protracted battle with the Food and Drug Administration, which in November compelled 23andMe to stop offering some of its genetic testing services after regulators questioned the accuracy of the results and warned of the danger of consumers receiving life-changing health information that doesn't come from a doctor. By that time, 23andMe had the DNA of 550,000 customers.

Customers must sign a consent form for 23andMe to use their genetics information in medical research -- and about 85 to 90 percent of customers do, Wojcicki said, explaining that most customers suffer from or have an interest in a genetic disease and want to contribute to scientific research.

But Appelbaum questions how many customers fully understand what they are agreeing to: "That consent rate is quite high. Most studies conducted in academic settings have much lower consent rates," he said. "That raises the question of how well 23andMe describes what it is that they are asking permission for."

The company sells genetics data for research only in aggregate "to minimize the possibility of exposing individual-level information," according to the privacy policy. But customers can also agree to share their personal information, and when given permission, 23andMe will give out details such as their name, email, height, eye color and birth date. The company could not say how many of its customers agree to that level of disclosure.

The privacy policy doesn't limit with whom 23andMe can share data and stipulates the company can "enter into commercial arrangements" with other companies for the purpose of selling or offering products and services.

Spokeswoman Catherine Afarian said 23andMe asks customers "in every single specific instance in which we want to use personal information" and "there is no scenario in which someone could give us a blanket permission. We believe you own your information. It's your data, you should have access to it and you should have control over it."

But in a 2012 study from the Massachusetts Institute of Technology, researchers proved they could determine the identities of some customers of two online genetics testing companies simply by studying their DNA samples, tracing their ancestry to figure out their last names and doing an Internet search. That led researchers to call for stricter data-sharing policies for companies such as 23andMe.

Wojcicki isn't surprised or fazed by the criticism: "23andMe is forging new ground," she said. "I'm not here just to try and make a quick buck. We're code-breaking here, and it's a really complex problem."

Contact Heather Somerville at 510-208-6413. Follow her at

[It is now in the books of history, that "Anne Wojcicki picked up the Genome Baby", in 2006 (when even the first ENCODE wasn't finished, thus Junk DNA and Central Dogma "ruled"; took real guts for IT to pick it up):

YouTube of 2008

Today, in Mountain View 23andMe aims to be the Google of Genetic Research, meanwhile Google Genomics seems committed to take off - but Venter just snatched Franz Och from Google, claiming that what they will do in genome analytics to fight cancer will make Google "Child Play". Next door, also in Mountain View, Complete Genomics is now a subsidiary of China's BGI (see the same YouTube citing that Complete Genomics planned to also build their own "Google Type Data Center")... This peak season of the USA business from Labor Day till Thanksgiving will be very interesting. More off-line... AJP; holgentech_at_gmail_dot_com]

Mayo Clinic, IBM Collaborate to Match Patients with Clinical Trials

GenomeWeb Daily News

September 10, 2014

NEW YORK (GenomeWeb) – The Mayo Clinic and IBM this week announced a pilot program to use IBM's Watson to match patients with clinical trials.

The initiative is in its proof-of-concept stage and Watson is being familiarized with clinical trial terms. Further down the road, genetic and genomic information may be included in the patient-matching process, a Mayo Clinic spokesperson told GenomeWeb Daily News.

Mayo said that enrolling patients in clinical trials has been a challenge, and at the clinic just 5 percent of patients take part in clinical studies. Nationally, the enrollment is just 3 percent, Mayo added.

Additionally, the process is done manually with clinical coordinators sorting through patient records and conditions to match appropriate patients with studies. Mayo conducts more than 8,000 human studies, and Watson could accelerate and simplify the matching process by sifting through available Mayo clinical trials to ensure that more patients are accurately and consistently matched with clinical trial options.

The version of Watson to be used in the collaboration will be designed specifically for Mayo and as it moves through the collaboration, Watson will learn more about the clinical trial process, becoming more efficient and "likely more generalizable," Mayo said. Watson may also be able to identify patients for trials that are especially difficult to recruit patients for, such as those involving rare diseases.

"With shorter times from initiation to completion of trials, our research teams will have the capacity for deeper, more complete investigations," Nicholas LaRusso, a Mayo gastroenterologist and the project lead on the Mayo-IBM collaboration, said in a statement. "Coupled with increased accuracy, we will be able to develop, refine, and improve new and better techniques in medicine at a higher level."

Mayo and IBM are working to expand Watson's knowledgebase to include all clinical trials at Mayo, as well as those in public databases such as Additionally, the partners are exploring other applications for Watson in the future.

[Dr. Pellionisz is legally permitted to practice Compensated Professional Services (Analysis, Advisorship, Consultantship, Board Membership, etc) as long as there is no "Conflict of Interest", through holgentech_at_gmail_dot_com.

Communication regarding Intellectual Property of any kind, including but not limited to patents, trade secrets, know-how associated with Dr. Pellionisz must be strictly gated by "Attorney Kevin Roe, Esq. FractoGene Legal Department", mailing address (USPS/UPS/FedEx) "155 E Campbell Ave, Campbell, CA 95008"]

Venter steals top scholar from Google
University of San Diego News

By Gary Robbins2:55 P.M.JULY 29, 2014

La Jolla geneticist J. Craig Venter has hired one of the world’s top computer scientists to help him try to prolong and improve people’s lives by deciphering hundreds of thousands of human genomes.

Franz Och was lured away from Mountain View-based Google, where he has been guiding Google Translate, a service that is capable of translating more than 80 languages. The software has more than 200 million active users and translates everything from Yiddish to Swahili to English.

Och, 42, will help find ways to make it faster and easier for scientists to sift through the extraordinary amounts of data produced by sequencing. He will serve as chief data scientist at Human Longevity, Inc., a La Jolla company that Venter founded earlier this year to conduct the largest sequencing effort ever undertaken. The company will initially sequence 40,000 human genomes a year, then ramp up to 100,000.

“I basically did a search and tracked down the person who led the Google Translate effort, which I see as similar to the challenges we face with genomics,” said Venter, who helped lead, and speed up, the Human Genome Project.

“The six billion letters of the genome represents one of the biggest translation issues ever. Your genetic code translates into your biological code which translates into you. We need to use machine learning to find associations between genes that mere mortals can’t find from staring at the data. It’s too complex.”

Venter also needs help deciphering the tremendous amount of data that will be generated by examing microbiomes, or the countless microbes found on the human body. Scientists believe that such microbes can affect people’s health in ways large and small.

Och will operate out of Mountain View rather than moving to La Jolla.

“San Diego is phenomenal place for recruiting biologically-oriented scientists,” Venter said Tuesday. “But the Silicon Valley for people into computation science. So rather than try to convince a few hundred people to love to La Jolla, we’re just going to build on the talent base in the Silican Valley.”

Computational scientists also work at Human Longevity in La Jolla, and a facility Venter is opening in Singapore.

In a statement, Och said, “We’re going to need the best and brightest from the areas of computer science, machine learning and big data generation and interpretation as well as those from biology, genomics and bioinformatics to reach a new level of understanding of this massive database.

“I look forward to working with Craig and the team at HLI to enhance our understanding of human biology, to better manage the healthy aging process and thus increase the healthy human lifespan.”

[Dr. Pellionisz is legally permitted to practice Compensated Professional Services (Consultantship, Board Membership, etc) as long as there is no "Conflict of Interest", through holgentech_at_gmail_dot_com. Communication regarding Intellectual Property of any kind, including but not limited to patents, trade secrets, know-how associated with Dr. Pellionisz must be strictly gated by "Attorney Kevin Roe, Esq. FractoGene Legal Department", mailing address (USPS/UPS/FedEx) "155 E Campbell Ave, Campbell, CA 95008"]

End of Summer - Beginning of The New Era of Global Industrial Bidding War

September 6th is 2 years after the "shell shock" of "Junk Genomics" gone forever. (ENCODE I in 2007 established that "the genome is much more complex than we have ever imagined"). It took another 5 years for the message to sink in. By September 6th, 2012, the "Labor Day Type Fireworks" by the admission of ENCODE-II that "at least 80% of the human DNA is functional", along with the earlier statement by Craig Venter that "our concepts of genome regulation are frighteningly unsophisticated", as of this fall an entirely new era, a global industrial competition is afoot, led by Samsung, Sony/Illumina, Panasonic and BGI in Asia, Siemens and SAP in Europe and traditional health-care IT giants in the USA of HP, Dell, Intel, Oracle etc. More recent to the fervor are Calico (bringing together Apple with Google), and Google Genomics now in a head-on competition with the new genome analytics player, Craig Venter (both in Mountain View, along with BGI-fully owned Complete Genomics). While the ENCODE I-II took 9 years, statistics shows that in 2005 7.6 million people died of the genome regulation disease (cancer), a projected 9 million will be dead in 2015 of cancer, and in 2030 the number is projected to be 11.4 million. Thus, about 70 million humans died during ENCODE I-II, the period to clinch the need for software-enabling algoritms for totally available computers for cancer genome analysis. Who will take responsibility for any undue delays? One can monitor a death at about every 3 seconds.

[Dr. Pellionisz is legally permitted to practice Compensated Professional Services (Consultantship, Board Membership, etc) as long as there is no "Conflict of Interest", through holgentech_at_gmail_dot_com. Communication regarding Intellectual Property of any kind, including but not limited to patents, trade secrets, know-how associated with Dr. Pellionisz must be strictly gated by "Attorney Kevin Roe, Esq. FractoGene Legal Department", mailing address (USPS/UPS/FedEx) "155 E Campbell Ave, Campbell, CA 95008"]

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."

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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 s