Friday, August 31, 2001

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"The Jackson Laboratory has received a grant of more than $35 million over the next five years to support its bioinformatics program. This grant is the largest single gift the lab has ever received.

Bioinformatics is the science of managing and analyzing biological data using advanced computer techniques. The lab maintains an internationally recognized Mouse Genome Database - a database that includes information such as the location of genes on a chromosome, information about mouse genes that are similar to genes in humans and other mammals, differences in gene sequence among individual mice, mapping information, and the importance of specific genes in understanding disease and other health problems."

Thursday, August 30, 2001

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"Chinese President Jiang Zemin met with scientists participating in the Human Genome Project on Tuesday. He praised the project, saying genomic information should be "owned by all, done by all and shared by all." Full text: Chinese President Jiang Zemin met with scientists participating in the Human Genome Project on Tuesday. He praised the project, saying genomic information should be "owned by all, done by all and shared by all." The HGP is "of utmost importance" for people to learn more about themselves and advance life development, he said.

The Chinese government has always supported the project because it concerned human progress, Jiang said, adding China was thrilled to make its contributions to the project. HGP scientists in turn commended Chinese scientists for completing China's HGP assignment ahead of schedule.

HGP's general coordinator Francis Collins said that China has a crucial role in the HGP and that he hopes the international cooperation shared in the human genomics field will continue.

Reference: People's Daily, 29 August 2001"

redux [07.14.01]
Science Celera human genome data not Wellcome
[summary - can be viewed for free once registered]

"In this policy forum, Cook-Deegan and McCormack urge that DNA sequence information contained in patents be made publicly available soon after patent applications are filed. This will speed access to valuable data without undermining investment in subsequent development of DNA-based inventions. The authors further suggest that federal agencies and nonprofit funds consider adopting this policy as a condition of accepting their funders; private firms could adopt it as a norm to reduce duplication of effort and to accelerate innovation."

redux [02.27.01]
The Financial Times Opinion: No price should be placed on the book of life

"Let me be frank here: my view is, and always has been, that the information in the genome is our genetic heritage and should not be profited from directly. It is not for sale. This is a pro partnership, not an anti-business, stance. We want to ensure that the entire world has equal access to the data, so that the potential health benefits are reaped by the many, rather than the few.

As Prime Minister Blair said: "The knowledge contained in the map of the human genome has the power to touch the lives of everyone on the planet." It is for precisely this reason that our commitment should be for the entire world to use this data so the benefits can be realised by all, and major killers such as malaria, tuberculosis, river blindness and leprosy will not be neglected."

The Economist Science and profit

"ONCE upon a time, pure and applied science were the same. Sir Humphry Davy discovered seven chemical elements, and invented the miner's safety lamp. Louis Pasteur investigated the properties of molecules, and worked out how to stop milk spoiling. Everybody thought that was admirable. Somehow, things have changed. Today the feeling is widespread that science and commerce should not - must not - mix. There is a queasy suspicion that the process of discovery is in some way corrupted if it is driven by profit."

"Far from compromising science, profit in both these cases - the development of new medicines and the elucidation of the genome - has animated it, and directed it towards meeting pressing human needs. It is a happy marriage. Davy and Pasteur would surely have approved."

Wednesday, August 29, 2001

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"According to The Hitchhiker's Guide to the Galaxy, hyper-intelligent pan-dimensional beings (disguised as mice) are using us to compute The Ultimate Question of Life, The Universe, And Everything. Now earthling scientists have roped unsuspecting web servers into a similar - albeit slightly less ambitious - exercise in parasitic computing.

Using the Internet itself as a computer, Jay Brockman and colleagues at the University of Notre Dame, Indiana, have solved a mathematical problem with the unwitting assistance of machines in North America, Europe and Asia."

EyeForPharma Novartis evaluates Entropia's distributed computing technology for accelerating drug discovery

""The vast quantities of data involved in the genomic era of drug discovery are quickly outpacing advances in computing technology," said Robert North, Entropia CEO. "Distributed computing allows companies to cost-effectively access the massive computing power they'll need by using their existing PC networks. It's quite exciting that companies like Novartis are deploying our platform to demonstrate the potential of distributed computing as a valuable tool in drug discovery efforts.""

redux [07.22.00]
The Standard Distributed Computing Goes Commercial

"The distributed-computing model could be one of those rare cases where capitalism and pure scientific research mesh. Not every lab can afford to pay $200,000 for an eight-processor Origin 2000 SGI supercomputer, much less $1 million for a 40-processor machine, says David Fenstermacher, director of scientific computing for the medical school at the University of North Carolina at Chapel Hill. (Fenstermacher is also acting director of the campus' Center for Bioinformatics and a United Devices adviser.) And even the most powerful supercomputers need time to process data.

A project that would take several months on a supercomputer - creating a 3D model of a protein's linear be accomplished in much less time using thousands of distributed computers"

redux [02.18.01]
Wired News Genome Effort Hits Home

"A new distributed computing project is comparing gene data with protein structures to determine their genome sequences.

"Genome@home is the second project from Stanford University's chemistry department, which also runs the Folding@Home project.

"Whereas Folding@Home is designed to learn how genomes fold into proteins, Genome@Home was launched this week to try and reverse engineer known proteins by guessing the genome sequence of their structures."

redux [10.09.00]
ACM CrossRoads The SETI@Home Problem

"The SETI@Home problem can be thought of as a special case of the distributed computation verification problem: "given a large amount of computation divided among many computers, how can malicious participating computers be prevented from doing damage?" This is not a new problem. Distributed computation is a venerable research topic, and the idea of "selling spare CPU cycles" has been a science fiction fixture for years."

"The Internet makes it possible for computation to be distributed to many more machines. However, distributing computing around the internet requires developers to consider the possibility of malicious clients."

"The general study of secure multiparty computation has produced much interesting work over the last two decades. Less well studied, unfortunately, are the tools and techniques required to move the theoretical results to the real world. The old dream of massively distributed computations is finally coming true, and yet our tools for building and analysing real systems still seem primitive. The challenge of the next few years will be to bridge this gap."

Tuesday, August 28, 2001

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"The SNP Consortium announced Tuesday that it had forged agreements with Motorola, Celera, Applied Biosystems, and Rutgers University that would enable it to build a SNP-based linkage map of the human genome by the end of the year.

The Consortium said it would make its linkage map available for free to researchers around the world."

Analytical Chemistry News & Features SNP Mining

"Researchers have not yet plumbed the depths of the Human Genome Project, but they are already looking for better prospects in the form of genetic variations called single nucleotide polymorphisms (SNPs, pronounced "snips"). Although SNPs are not the only type of genetic variation, many researchers expect them to be the most helpful for identifying disease genes. Others think SNPs will catapult us into the era of personalized medicine, when pharmacogenetics will enable physicians to prescribe drugs based on detailed knowledge of our genotypes. But even as enthusiasm for SNP analysis grows, studies suggest that there is a lot of pyrite mixed with the gold. And nobody knows how long the commercial sector will have to dig to reach pay dirt."

redux [07.23.01]
BioMedNet Genetic individuality
[requires 'free' registration]

"A haplotype is defined as the genetic constitution of a person with respect to one member of a pair of genes. Small differences in genes are known as single nucleotide polymorphisms (SNPs). Researchers analyzed 313 genes in 82 individuals with different ancestral backgrounds. They found that "the strength of the genetic association of pairs of SNPs (linkage disequilibrium), which is important in the identification of disease-related genes, could not be readily predicted from examining individual genes or genomic regions." It appears that haplotypes provide more information as genetic markers in a gene than do SNPs.

Reference: Stephens, J.C., Schneider, J.A., Tanguay, D.A. et al. 2001. Haplotype variation and linkage disequilibrium in 313 human genes. Science 293(5529):489-493."

USA Today Genome guide is next goal

"Until recently, scientists had hoped to predict a person's response to medicines and find disease-causing genes by analyzing specific gene variations, called single nucleotide polymorphisms, or SNPs. But the vast number of SNPs in the human genome would make this costly and laborious.

But new research indicates that SNPs actually travel together from one generation to the next in strands called haplotypes, Collins says.

Creating a haplotype map, he says, would greatly simplify the process of analyzing an individual's risk of disease and response to certain drugs. "The whole Human Genome Project has been a prelude to this," says Eric Lander of MIT, a leader of the publicly funded project."

""Trust me, it's going to be a very powerful way to understand genetic disease," he said."

redux [07.18.01]
BioMedNet For haplotype mappers, deja vu all over again
[requires 'free' registration]

"A US government-centered effort to gain useful information from a map of single nucleotype polymorphisms (SNPs) might be late off the starting block, again chasing a private effort toward the same goal. That conclusion is emerging even as the National Human Genome Research Institute (NHGRI) convenes a two-day planning meeting here, involving the SNP consortium of pharmaceutical and biotechnology companies as well as academic leaders."

"Larry Thompson, chief of the communications and public liaison branch of NHGRI, told BioMedNet News that there is no Haplotype Project currently underway, and this week's meeting (which Brooks had billed as the "Haplotype Meeting") will examine the opportunities that the science presents. "This is a natural extension of efforts that are currently underway and which we believe will help identify genes and their relationship to disease," he said. "How this project will take shape is a big unknown at the moment.""

Wired News Geneticists Await Haplotype Map

"An effort called the SNP Consortium is also underway to identify and interpret individual variations. Looking at SNPs individually can help determine predisposition to disease and potential reactions to drugs."

""It's like the differences between buses and cars," Venter explained."

"These are difficult concepts for non-scientists to understand, but Collins said everyone has an interest in knowing about this type of research."

""Trust me, it's going to be a very powerful way to understand genetic disease," he said."

Monday, August 27, 2001

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"India's Tata Consultancy Services, the largest software company in Asia, launched its foray into bioinformatics on Monday by entering a research and development collaboration with a government lab."

""We hope to combine our strengths in machine learning and pattern recognition with their expertise in biology," M. Vidyasagar, executive vice president of advanced technology at TCS, said in an interview."

Business Standard TCS enters into bio-informatics

""TCS has always been exploring new areas on a continuous basis and has been pioneering research for over 20 years. As we go into multiple domains, intersection of biological sciences, life sciences and information technology poses interesting situations," S Ramadorai, CEO of TCS."

"It is estimated that the bioinformatics area will require 20,000 professionals within the next five years and the estimated trained professionals at the moment in the industry are just about 1,000."

Hindu Business Line That's the sequence, Watson!

"THE mood is one of caution as far as bioinformatics is concerned. The beginning of the year saw hype building up around the fledgling industry as the next big gold rush for India.

But six months after the first bioinformatics seminar in the country, with the IT industry's lesson on hype fresh in mind, things are moving at a more sedate pace."

"In India, bioinformatics training institutes have already begun to mushroom. Bangalore and Hyderabad have around five private training institutes between them. However, the industry is sceptical about the quality of manpower these centres can supply because most of them have short-term courses offering basic skills, says Dr. Sabharwal. In all fairness to them she adds, "We need to wait for a few months to see the outcome of it all.""

redux [05.09.01]
Sri Lanka Lakehouse Daily News WWW.Human Genome

"The Internet could turnout to become the equaliser in the brave new world of research into human genetics - up to a point.

Following a fierce dispute, the data on the reading of the human genetic code has been published on the Internet to make it accessible to scientists anywhere. The result has been a flood of research projects in the developing world into data that would otherwise not have been accessible."

"During the past couple of months, the public genome databases have ben used by scientists 160,000 times in India, 61,000 times in Mexico and about 50,000 times each in China and in Brazil. The data is being accessed daily by about 10,000 organisations around the world."

Sunday, August 26, 2001

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"The mapping of the human genome, in which scientists wrote out the entire chemical sequence of DNA, was a first step in genetic research. Now, scientists are seeking to discover how specific genes play a role in disease. Then, they hope to find drugs that act on those genes.

But many of the simple diseases - those in which a single genetic defect is the cause - have already been deciphered. More challenging are diseases in which many genes play smaller roles. So how can researchers know for sure which genes to target? GCI thinks the answers are embedded in the samples in its library."

Friday, August 24, 2001

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"After a humiliating deflation this February, human dignity is on the recovery path, at least as measured by the number of genes in the human genome.

Two new estimates put the likely number of human genes at around 40,000, up by a third from the estimate of about 30,000 in February by the two teams of scientists who decoded the human genome. The low estimate still has its defenders."

NPR: All Things Considered DNA Recount

"Recent estimates that the human genome consists of only about 30,000 genes may be way off the mark, according to a study published today in the journal Cell. NPR's Richard Harris has the story. (3:45)"

redux [01.18.01]
ScienceDaily With First Comparative Look At Human And Mouse DNA, Joint Genome Institute Team Confirms Gene Estimate

"Earlier this year, researchers mapping the human genome estimated that human DNA contains about 30,000 genes. Now, based on the first-ever look at comparable sections of human and mouse DNA, a team of Walnut Creek-based Joint Genome Institute (JGI) scientists has confirmed that estimate as roughly accurate."

""There had been speculation that aligning the human and mouse DNA sequence might reveal many more genes," Stubbs said. "However, if chromosome 19 is indicative of other chromosomes, the estimate of 30,000 genes is fairly accurate.""

BBC Dispute over number of human genes

"Two rival teams that cracked the human genome may have underestimated the number of human genes, according to a new computer analysis."

Scientists in the United States claim humans are built from 66,000 genes, nearly twice as many as the current consensus."

"But the new analysis, published on the website of the journal Genome Biology, has been dismissed by the Sanger Centre, in Cambridgeshire, UK, which was responsible for about a third of the human genome sequencing effort."

""The experimental evidence actually points to 30-40,000 genes," Dr Hubbard told BBC News Online. "I don't believe the argument in this paper that there are a lot more genes. This is an entirely computational paper and I don't think it's very credible.""

redux [11.13.00]
BioMedNet UK geneticist offers exact count of human genes
[requires 'free' registration]

"If James Watson, co-discoverer of DNA's structure, says we don't know how many genes there are, you're inclined to believe him. So it was a great surprise to hear the legend denounced, albeit with due deference. At the last count, insisted Kay Davies, professor of anatomy at the University of Oxford, humans are reckoned to have 40,944 tiny protein factories.

She was drawing on statistics that define the proteome, the protein equivalent of the genome, as the set of all expressed proteins in humans, for which 40,944 genes are individually responsible. Not a huge figure, she noted, barely the equivalent of three flies or a couple of worms. "Apologies Jim, let's talk over tea," she added."

redux [06.08.01]
Red Herring Genomics offers an odd proposition

"Research on the human genome may well pay fat dividends in 10 or 20 years, but you can make money on it now, the old-fashioned way: by gambling. Find out how on the Web site of Project Ensembl, a European organization that develops genome-related software."

At the May 2000 Annual Meeting on Genome Sequencing and Biology at the Cold Spring Harbor Laboratory in Long Island, New York, Ewan Birney, team leader of Project Ensembl, proposed GeneSweep, a betting pool to guess the total number of human genes. All bets must be entered by hand, in person, in ink, in a book kept at the Cold Spring Harbor Laboratory. The winner of the pool, which now stands at a whopping $348, will be announced at the 2003 genome meeting."

redux [05.13.00]
Wired News Amped Geneticists Bet on Genome

"Well, they weren't all men, but mostly. The betting in the pub continued, the lowest bet being 29,800 genes placed by Pat Tome and the highest number coming from John Quackenbush at 118,259.

The pool was organized by Erwin Birney, a team leader at the European Bioinformatics Institute. He tried to convince the bartender to oversee the betting, but was told in no uncertain terms that no gambling was allowed in the Cold Spring bar.

Guesses on the number of genes in the human genome have lowered considerably since the mapping of chromosome 21, which researchers found to contain only 225 genes, far fewer than previously predicted. The researchers on the chromosome 21 study predicted their results could mean that there are as few as 40,000 genes in the entire human genome.

"Someone from Incyte will probably show up and bet 150,000," one gambler said."

Thursday, August 23, 2001

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"This report outlines recent activity in open source software development within the discipline of bioinformatics. I present the relevant highlights of two bioinformatics meetings held in July 2001 in Copenhagen, Denmark: the Bioinformatics Open Source Conference and the Intelligent Systems for Molecular Biology Conference. The report also describes a large number of projects and groups important to bioinformatics open source software development. The appendices include meeting programs, the currently accepted definition of open source software, and descriptions of important online biological data sources."

redux [08.18.01]
GenomeWeb Legal Pitfalls of Free Bioinformatics Software May Loom Large

"Steve Brenner, assistant professor and leader of a computational genomics research group at the University of California, Berkeley, said he fears that many academic bioinformaticists are unaware of a legal risk they face on a daily basis: contributing to open source software projects without explicit permission from their institutions.

While many employers have clauses in their employment contracts that restrict the creation and use of open source software, bioinformatics programmers at universities are often not as attuned to copyright issues as their industry counterparts. This fact, Brenner said, raises the possibility that a good portion of biological open source software is currently being produced illegally."

"The issue seems to be coming to a head in the academic world now, as more universities are exploiting the revenue stream made possible by their copyright and patent holdings. ?If you?re a software developer, the university holds rights to your software, but if you?re an English professor or Law professor and publish a book, they?re not the least bit interested in copyright,? said Thomas Field, an attorney at the Franklin Pierce Law Center affiliated with the Association of University Technology Managers."

redux [05.09.01]
IEEE Spectrum Open-Source Biology And Its Impact on Industry

"The toolbox of biochemistry, the parts list--"the kernel," to stretch the software analogy--is shared by all organisms on the planet. In general, organisms differ from one another because of their order of gene expression or because of relatively subtle perturbations to protein structures common to all forms of terrestrial life. That is, innovation in the natural world in some sense has always followed the idea of a service and flow economy. If the environment is static, only when an organism figures out how to use the old toolbox to provide itself, or another organism, with a new service is advantage conferred.

The analogy to future industrial applications of biology is clear: When molecular biologists figure out the kernel of biology, innovation by humans will consist of tweaking the parts to provide new services. Because of the sheer amount of information, it is unlikely that a single corporate entity could maintain a monopoly on the kernel. Eventually, as design tasks increase in number and sophistication, corporations will have to share techniques and this information will inevitably spread widely, reaching all levels of technical ability--the currency of the day will be innovation and design. As with every other technology developed by humans, biological technology will be broadly disseminated."

Technology based on intentional, open-source biology is on its way, whether we like it or not, and the opportunity it represents will just begin to emerge in the next 50 years."

redux [03.04.01]
The Washington Monthly Reboot! How Linux and open-source development could change the way we get things done

"Imagine a scale with all the advantages of a proprietary model on the left and all the advantages of an open-source model on the right. Pretend everybody who wants to solve a problem or build a project has a scale like this. If it tips to the left, the proprietary model is chosen; if it tips to the right, the open model is chosen. Now, as connectivity increases with the Internet, and computer power increases exponentially, more and more weight accumulates on the right. Every time computer power increases, another household gets wired, or a new simulator is built online, a little more weight is added to the right. Having the example of Linux to learn from adds some more weight to the right; the next successful open-source project will add even more.

"Perhaps the next boom in open source will come from the law; perhaps from drug X; perhaps it will be something entirely different. Although it's difficult to tell, it is quite likely that the scale is going to tip for some projects and that there will be serious efforts at open-source development in the next decade. Moreover, it's quite likely some of these projects will work."

Tuesday, August 21, 2001

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"Cray's Conway says that typical bioinformatics algorithms approach problems, such as STR mapping, using statistical sampling rather than exhaustive, methods. In a statistical sampling approach, relatively large regions are examined in aggregate to produce a score. If this value is above some threshold value, then the region is examined in greater detail. If not, it is discarded. In contrast, exhaustive approaches examine each residue, one at a time. The disadvantage of statistical approaches is that important elements can be missed if they are in a region that fails to produce an adequate score. Although exhaustive approaches do not suffer from this drawback, they are usually computationally prohibitive. Nevertheless, according to Conway, initial benchmark comparisons of the SV1 to the ABCC's other supercomputers showed that, when using software written to take advantage of the computer's pattern-matching capabilities, the Cray was up to 2,000 times faster than otherwise comparable computers. Thus, a problem that ordinarily took days could be finished in minutes."

Monday, August 20, 2001

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"Like the Terrys, a rising number of patients, doctors and ethicists are questioning how the patent system handles genetic claims. Many say it awards too many patents, overly rewards their holders, and gives too little back to patients. Yet many industry voices complain the process is moving too slowly to keep up with galloping research and to yield medical care awaited by suffering patients.

The strains from both sides are apt to intensify. The run on genetic patents will grow fiercer in the next several years, spurred by longer lists of genes and derived proteins discovered by genomics and proteomics projects, according to patent experts in business and government.

"The gold rush days are about to begin,'' says Arthur Caplan, a bioethicist at the University of Pennsylvania. "There are so many targets that look so lucrative that they're falling all over one another to pursue opportunity after opportunity.""

redux [07.14.01]
Wired News Why Is Your DNA Their Secret?

"You probably don't realize that the DNA you carry inside your body is patented by companies, universities and government agencies.

There were more than 25,000 DNA-based patents by the end of 2000, but you aren't allowed to look at some of your own DNA sequences because researchers keep the information private in order to stay ahead of the competition and to sell the information as a trade secret."

"Dr. Robert Cook-Deegan, director of the National Cancer Policy Board and the National Academy of Sciences Commission on Life Sciences, said keeping DNA data secret stops up the flow of information and slows the discovery of potential treatments for disease.

But biotech companies and the U.S. Patent and Trademark Office defend themselves by saying that without patents there would be no innovation."

Science Celera human genome data not Wellcome
[summary - can be viewed for free once registered]

"In this policy forum, Cook-Deegan and McCormack urge that DNA sequence information contained in patents be made publicly available soon after patent applications are filed. This will speed access to valuable data without undermining investment in subsequent development of DNA-based inventions. The authors further suggest that federal agencies and nonprofit funds consider adopting this policy as a condition of accepting their funders; private firms could adopt it as a norm to reduce duplication of effort and to accelerate innovation."

redux [02.27.01]
The Financial Times Opinion: No price should be placed on the book of life

"Let me be frank here: my view is, and always has been, that the information in the genome is our genetic heritage and should not be profited from directly. It is not for sale. This is a pro partnership, not an anti-business, stance. We want to ensure that the entire world has equal access to the data, so that the potential health benefits are reaped by the many, rather than the few.

As Prime Minister Blair said: "The knowledge contained in the map of the human genome has the power to touch the lives of everyone on the planet." It is for precisely this reason that our commitment should be for the entire world to use this data so the benefits can be realised by all, and major killers such as malaria, tuberculosis, river blindness and leprosy will not be neglected."

The Economist Science and profit

"ONCE upon a time, pure and applied science were the same. Sir Humphry Davy discovered seven chemical elements, and invented the miner?s safety lamp. Louis Pasteur investigated the properties of molecules, and worked out how to stop milk spoiling. Everybody thought that was admirable. Somehow, things have changed. Today the feeling is widespread that science and commerce should not?must not?mix. There is a queasy suspicion that the process of discovery is in some way corrupted if it is driven by profit."

"Far from compromising science, profit in both these cases - the development of new medicines and the elucidation of the genome?has animated it, and directed it towards meeting pressing human needs. It is a happy marriage. Davy and Pasteur would surely have approved."

redux [04.26.00]
Signals Homestead 2000: The Genome

""The analogy that I would use is that of a minefield," said Bob Levy, senior VP of science and technology for American Home Products. "We are spending an incredible amount of time now, when we find exciting targets and begin to validate them, in trying to define who has rights to what. And we're finding, in almost every product that we look at, that someone has patented the protein, the gene, a fragment, a diagnostic test." Levy noted that untangling patent rights, and determining which patents are dominant, are increasingly time-consuming and expensive tasks. And patent-holders must be paid. "The royalties that will be involved soon in some of the products that we are bringing to market, they're already up into the ten, fourteen, fifteen percent [range]," said Levy. "And that may increase with time.""

redux [08.26.00]
MIT Technology Review The Case for Gene Patents

"Nowhere are patents more central to the creative process than in genetic drug development, where human genes and their expressed proteins themselves are developed as therapies. The biotechnology industry in the United States has brought a handful of these crucial new products (recombinant human insulin, to name one of the most familiar) to market and is on the threshold of a bonanza of genetic drugs and vastly greater relief for ill and aging populations around the world.

Patent protection is the sine qua non of that bonanza."

Sunday, August 19, 2001

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"Biomedical researchers are decoding the human genome with astonishing speed, but the clinical significance of the massive volumes of data collected remains largely undiscovered. Progress requires communication and data sharing among scientists. These data may be in the form of (1) raw data, derived data, and inferences that result from computational analyses, or (2) text documents published by experts who present their conclusions in natural language. The World Wide Web provides a valuable infrastructure for enabling researchers to share the rapidly growing knowledge about biology and medicine, and a fully functional Semantic Web is necessary to support data submission and retrieval, the sharing of knowledge, and interoperation of related resources."

The Second International Workshop on the Semantic Web Proceedings

"The "Semantic Web", a term coined by Tim Berners-Lee, is used to denote the next evolution step of the Web. Associating meaning with content or establishing a layer of machine understandable data would allow automated agents, sophisticated search engines and interoperable services, will enable higher degree of automation and more intelligent applications. The ultimate goal of the Semantic Web is to allow machines the sharing and exploitation of knowledge in the Web way, i.e. without central authority, with few basic rules, in a scalable, adaptable, extensible manner. With RDF as the basic platform for the Semantic Web, a multitude of tools, methods and systems have just appeared on the horizon. The goal of the workshop is to share experiences about these systems, exchange ideas about improvements of existing tools and creation of new systems, principles and applications. Also an important goal is to develop a cooperation model among Semantic Web developers, and to develop a common vision about the future developments."

redux [05.10.00]
The XML Cover Pages XML and Semantic Transparency

"We may rehearse this fundamental axiom of descriptive markup in terms of a classical SGML polemic: the doubly-delimited information objects in an SGML/XML document are described by markup in a meaningful, self-documenting way through the use of names which are carefully selected by domain experts for element type names, attribute names, and attribute values. This is true of XML in 1998, was true of SGML in 1986, and was true of Brian Reid's Scribe system in 1976. However, of itself, descriptive markup proves to be of limited relevance as a mechanism to enable information interchange at the level of the machine.

As enchanting as it is to contemplate the apparent 'semantic' clarity, flexibility, and extensibility of XML vis-à-vis HTML (e.g., how wonderfully perspicuous XML <bookTitle> seems when compared to HTML <i>), we must reckon with the cold fact that XML does not of itself enable blind interchange or information reuse. XML may help humans predict what information might lie "between the tags" in the case of <trunk> </trunk>, but XML can only help. For an XML processor, <trunk> and <i> and <booktitle> are all equally (and totally) meaningless. Yes, meaningless.

Just like its parent metalanguage (SGML), XML has no formal mechanism to support the declaration of semantic integrity constraints, and XML processors have no means of validating object semantics even if these are declared informally in an XML DTD. XML processors will have no inherent understanding of document object semantics because XML (meta-)markup languages have no predefined application-level processing semantics. XML thus formally governs syntax only - not semantics."

redux [05.10.00]
The Rand Corporation : Scaffolding the New Web: Standards and Standards Policy for the Digital Economy The Emerging Challenge of Common Semantics

"With XML has come a proliferation of consortia from every industry imagineable to populate structured material with standard terms (see Appendix B). By one estimate, a new industry consortium is founded every week, perhaps one in four of which can collect serious membership dues. Rising in concert are intermediary groups to provide a consistent dictionary in cyberspace, in which each consortium's words are registered and catalogued.

Having come so far with a syntactic standard, XML, will E-commerce and knowledge organization stall out in semantic confusion?"

"How are semantic standards to come about?"

SemanticWeb.Org Tutorial on Knowledge Markup Techniques

"There is an increasing demand for formalized knowledge on the Web. Several communities (e.g. in bioinformatics and educational media) are getting ready to offer semiformal or formal Web content. XML-based markup languages provide a 'universal' storage and interchange format for such Web-distributed knowledge representation. This tutorial introduces techniques for knowledge markup: we show how to map AI representations (e.g., logics and frames) to XML (incl. RDF and RDF Schema), discuss how to specify XML DTDs and RDF (Schema) descriptions for various representations, survey existing XML extensions for knowledge bases/ontologies, deal with the acquisition and processing of such representations, and detail selected applications. After the tutorial, participants will have absorbed the theoretical foundation and practical use of knowledge markup and will be able to assess XML applications and extensions for AI. Besides bringing to bear existing AI techniques for a Web-based knowledge markup scenario, the tutorial will identify new AI research directions for further developing this scenario."

Saturday, August 18, 2001

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"Steve Brenner, assistant professor and leader of a computational genomics research group at the University of California, Berkeley, said he fears that many academic bioinformaticists are unaware of a legal risk they face on a daily basis: contributing to open source software projects without explicit permission from their institutions.

While many employers have clauses in their employment contracts that restrict the creation and use of open source software, bioinformatics programmers at universities are often not as attuned to copyright issues as their industry counterparts. This fact, Brenner said, raises the possibility that a good portion of biological open source software is currently being produced illegally."

"The issue seems to be coming to a head in the academic world now, as more universities are exploiting the revenue stream made possible by their copyright and patent holdings. ?If you?re a software developer, the university holds rights to your software, but if you?re an English professor or Law professor and publish a book, they?re not the least bit interested in copyright,? said Thomas Field, an attorney at the Franklin Pierce Law Center affiliated with the Association of University Technology Managers."

MIT Technology Review Origin of the Patents

"The adjective "Darwinian" is often applied to the dog-eat-dog software industry. But get ready for software that orchestrates natural selection among computer programs so that researchers can harvest the surviving code."

"At Stanford, genetic programming research seeks to produce results that are competitive with human problem solving, and to test that by evaluating success in duplicating or infringing upon existing U.S. patents. The research effort now has accomplished just that for patents generated as recently as last year. The work may eventually deliver automated "invention machines," says John Koza, genetic computing guru and consulting professor of biomedical informatics at Stanford."

redux [07.27.00]
Informatics Review Open Source Software in Healthcare

"Good software forms seamless connections; as George Orwell said of prose, the best is like a window pane: transparent. The obscurity of commercial binaries is an obstacle to good quality communication between systems. In healthcare, good communication is too important to remain proprietary. Software developers should remain confident that there will always be work for the future in discovering, providing, and adapting applications for organizations, and training people to use them. This, rather than the sharp-suited gouging of Bill Gates wannabees, should become the predominant business model for software in the British NHS. Software engineering will become a profession more like medicine and the law: in which practitioners earn a fair hourly reward for their experience at interpreting, evaluating and applying knowledge from a specialized domain to the benefit of their clients. Current models, which restrict the sharing and development of knowledge, are certainly counterproductive and arguably unethical. Open source is the future: all we have to do is built it."

redux [04.28.00]
Nature Open-source work even more vital to genome project than to software

"We note with dismay and alarm the controversy concerning access, distribution and patenting of the human genome sequence (Nature 404, 317; 2000 & Nature 404, 324; 2000). We wish to point out some analogies between the human genome sequencing efforts and 'open-source' software development, which have implications for the data-release policy of the public sequencing effort."

"The reasons why the Linux project could succeed against commercial wisdom have been analysed by Eric S. Raymond in his book The Cathedral and the Bazaar (O'Reilly, 1999). Most of these findings are of relevance to academic and commercial benefits arising from human genome sequencing."

[via bioinformatics.org]

Thursday, August 16, 2001

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"Some of the weirdest genetic phenomena have very little to do with the genes themselves. True, as the units of DNA that define the proteins needed for life, genes have played biology's center stage for decades. But whereas the genes always seem to get star billing, work over the past few years suggests that they are little more than puppets. An assortment of proteins and, sometimes, RNAs, pull the strings, telling the genes when and where to turn on or off."

""The unit of inheritance, i.e., a gene, [now] extends beyond the sequence to epigenetic modifications of that sequence," explains Emma Whitelaw, a biochemist at the University of Sydney, Australia."

""[Epigenetic effects] give you a mechanism by which the environment can very stably change things," says Rudolph Jaenisch, a developmental biologist at the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts. Researchers are hoping to harness these effects to design drugs that correct cancer and other diseases brought on by gene misregulation."

redux [11.09.00]
New England Journal of Medicine Pharmacogenomics -- Teaching Old Drugs New Tricks

"Traditionally, cancer treatments have been selected on the basis of tumor type, pathological features, clinical stage, the patient's age and performance status, and other nonmolecular considerations. We have generally accepted with a certain fatalism that some patients pigeonholed into a given category will have a response to a particular therapy, whereas others will not. The difference is often viewed as a matter of luck, like the result of a coin toss, but in fact, treatment response can be predicted in some cases, whereas it is close to impossible to predict the results of a coin toss. The field of pharmacogenomics, through the study of large numbers of genes that influence drug activity, toxicity, and metabolism, provides the opportunity to tailor drug treatments and to eliminate many of the uncertainties of current therapy for cancer. "

"In this issue of the Journal, Esteller and colleagues (2) provide clinical evidence of an intriguingly different sort of mechanism -- an epigenetic one that does not involve any change in DNA sequence -- to explain the resistance of some gliomas to nitrosourea alkylating agents."

"Such comprehensive approaches to biology can be characterized as "omic" research (6) -- that is, research in which one generates large resources of information on biologic molecules in aggregate without necessarily knowing in advance which pieces of information and which correlations will prove most important. (7) "Omic" research is hypothesis-driven, but the hypothesis relates to information and its usefulness, rather than to particular molecules or processes. "Omics" began with genomics and the Human Genome Project. Then, as coined by various researchers, there came proteomics, kinomics (for the kinases in aggregate), CHOmics (for the carbohydrates), metabolomics, immunomics, toxicomics, and clinomics -- as well as compound forms, such as functional genomics, structural genomics, and pharmacogenomics. In view of the study by Esteller et al., (2) and as we search for other clinically relevant instances in which promoter methylation affects therapy, can "pharmacomethylomics" be far behind?"

redux [07.11.00]
Wired News Following Cancer's Red Flags

"Genes are tricksters. They can be turned on or off -- and whether they're on or off decides whether the gene-owner will develop disease.

Gene researchers have embarked on a new field of research, called epigenomics, to determine whether genes are in the on or off position. This type of marker could prove an important diagnostic or therapeutic tool for all types of cancer.

"At Johns Hopkins, researchers are performing clinical trials on about 15 patients with leukemia and other cancers to find out if epigenomics might give pharmaceutical companies a lead for developing cancer drugs.

The research, like all epigenomics research, is studying a chemical found in everyone's DNA called cytosine. Cytosine is the only chemical of the four that make up human DNA (the others are adenine, thymine, and guanine) that is prone to a phenomenon called methylation. When cytosine is methylated, it tuns off its gene. "

Biospace.Com Big Picture Biology

"For most of us, formal biology education begins with complex systems--the traditional dissection of a frog in high school biology class is virtually a rite of passage in the U.S.

But the way many people learn about and invest in biotechnology is at the smallest end of the spectrum--the genome, now often described as the "periodic table" of biology. Genomics and all its related buzzwords have been responsible for much of the media attention, government grants, and investment capital heaped on the biotech industry over the past decade.

But just as there is a whole lot of chemistry that happens in between the periodic table and a birthday cake, there is a lot of biology in between the genome and a living organism. With the completion of biology's periodic table within sight, academics and industry players alike are pondering the best way to apply our hard won knowledge.

The only problem is, the path from genome to system seems to get harder the more we learn."

Wednesday, August 15, 2001

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"A new study of the proteomics market forecast that the proteomics market would grow nearly six-fold to $5.6 billion by 2006 from $963 million in 2000.

In its report, consultancy firm Frost & Sullivan said the increase would be driven by a shift towards the analysis of proteomes following the discovery that the human genome contains fewer genes than originally predicted.

"Proteomics adds value to drug discovery by charting the distribution of proteins, identifying and characterizing proteins of interest, and elucidating the participation of proteins in biochemical pathways boosting the number of potential targets around which lead compounds can be designed and screened," Eric Gay, a Frost & Sullivan analyst, said in a statement."

redux [07.11.01]
Scientific American The Post-Genome Project

"Their bold proclamation has raised a few eyebrows in the scientific community. "It's easy to say that you'll complete a comprehensive proteome map," notes Marc Vidal of the Dana-Farber Cancer Institute in Boston. "But none of us knows what that means." There may be only one genome, but when it comes to the proteome, different proteins can be more or less active in different cells at different times during development, under different physiological conditions or in different disease states. The proteome's nature "makes it hard to define what we're doing--not just Myriad, but all of us," remarks Joshua LaBaer, director of the Institute of Proteomics at Harvard Medical School. "There's no such thing as a human proteome," adds Keith L. Williams, CEO of Proteome Systems, headquartered in Sydney, Australia. Look at the liver, for example, he says: "After a glass of red wine, you'll have a different proteome."

redux [06.20.01]
Forbes Proteins Are Back To Confuse Investors

"Scientists thought about trying to catalogue all the proteins in the body a decade ago.

But it seemed impossible, and was therefore impossible to fund. Researchers moved on to the much simpler job of sequencing the human genome.

They were right to do so. Cataloguing proteins turns out to be downright confusing. Lately, more and more biotech companies are entering a field they call "proteomics," an ugly word searching for a focus group."

redux [03.31.01]
The Scientist Is a Human Proteome Project Next?
[requires 'free' registration]

"A commonly expressed opinion is that a single Human Proteome Project can never match HGP's success. Eric S. Lander , director of the Whitehead Center for Genome Research in Cambridge, Mass., notes that biologists simply don't know how to characterize the proteome "from end to end, nailing every protein. The tools are not ready. And it's not clear that [such a project] makes sense." He contrasts proteomics to HGP where "there is a certain fixed number of base pairs--about three billion--and we were going to get them all. And so it had a beginning and an end to it."

redux [01.31.01]
GenomeWeb Proteomics Effort Shouldn't Mimic Genome Project, Experts Say

"Can sequencing do for the proteome what it did for the genome?

On Wednesday, a number of world-renowned researchers in the field of proteomics issued a resounding " no."

Instead of devoting their efforts to decoding the human proteome, proteomics researchers should focus on developing a larger picture of protein structure, function, and pathways within cells and organisms, panelists said at a New York Academy of Sciences briefing entitled "The Promise of Proteomics."

"When a company has phenomenal success with strategy A, you want to do strategy A on the next subject," said John Richards, a professor of organic and biochemistry at California Institute of Technology, referring to current corporate attempts to map the proteome.

"This doesn't work," he said."

Tuesday, August 14, 2001

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"For years, technologists have dreamed that information technology and biotechnology would someday converge into one seamless superscience that could crack the molecular code of disease and yield a gold mine of new treatments and cures. It always seemed so logical, even if it never quite seemed to happen. Some very big names in tech -- Bill Gates ( MSFT ), Paul Allen, and Jim Clark, among others -- for years have been placing bets on so-called convergence companies that promised to exploit the merging of computing and biotech. Allen alone has investments in more than 50 of them, mostly obscure companies that use words like "genomics," "bioinformatics," and "proteomics" to describe what they do. This industry is so new it hasn't settled on a single name yet."

"Now, like a middle-age actor who has just been discovered, convergence has hit the big time. Corporate giants such as IBM ( IBM ) and Compaq ( CPQ ) are pouring $100 million dollops of cash into "life science" projects that mesh computers and biotech."

GenomeWeb Physiome Buys IBM's Power4-Based Supercomputer, Announces Research Pact

"IBM and Physiome Sciences have entered into a non-exclusive alliance that will combine IBM's supercomputing technology with Physiome?s biological modeling software, the companies announced."

"IBM, which beat out Compaq, Sun Microsystems and other IT giants with broad life-science partnerships, said that its Power4 technology will feature the world's first computer chip containing two processors."

""I was really impressed with their life sciences group," Maida said, explaining why Physiome chose IBM. "I think they keep it fairly quiet that they have these researchers in there. People forget about the research side of IBM.""

redux [06.26.01]
Forbes IBM's Biotech Resurgence

"In 1998, biotech upstart Celera Genomics needed a supercomputer to help it map the human genome. It didn't turn to IBM , which built 204 of the 500 fastest supercomputers. Both Celera and its academic competition, the Human Genome Project, used machines built by Compaq Computer. Two years later, Compaq is the leading seller of supercomputers to biological researchers.

But IBM noticed that biologists now need microprocessors as much as microscopes. A year ago, it used $100 million to start a division that sells computers, software and services to biotechnology and drug companies. This life sciences division has had some success; pulling into second place behind Compaq, it must do better."

redux [05.21.01]
Business 2.0 Tech Giants Court The Genome Crowd

"According to scientists, decoding the human genome is the most complicated civilian computational problem ever tackled, and the data generated by genomics has been doubling every six months. Proteomics eventually will generate 100 times more data than genomics and require 1,000-times more computing power.

"We don't need an evolution in computing, we need a revolution . The normal increase in CPU power is just not enough," says Marshall Peterson, vice president of infrastructure development for Celera. "This is what we call Venter's law-it states that biology will outpace Moore's law. Fast makes the difference in the very beginning of a market, but we won't be at this stage for long.""

redux [03.14.01]
ABCNews.Com The Next Bubble: Is Bioinformatics the Next Big Boom...and Bust?

"The story proclaimed in its lead, "Move over Information Age. Make room for the age of bioinformation." You could picture bleary eyes opening all over the Bay Area. The story went on to note that a San Jose consulting firm was predicting a 10 percent annual growth in the bioinformatics market for years to come; and that the National Science Foundation estimated that 20,000 new jobs in the field would be created in the field in just the next four years.

If that wasn't enough, the rest of the section was filled with page after page of biotech firms listing job openings - in powerful juxtaposition to the endless lists of dot-com layoffs just a few pages earlier. Picture Starbucks spit-takes from Marin to Santa Cruz.

Wow! Rewrite that resumé to emphasize that biology course you took in college. Roll your Aeron chair down to the nearest lab. Trade that black turtleneck for a white lab coat..."

Monday, August 13, 2001

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"A new company being formed in conjunction with the Medical College of Wisconsin hopes to combine powerful computers with growing knowledge about human genes to create new treatments that could profoundly change health care and tap a market potentially worth billions of dollars.

The company is among a handful across the nation seeking to develop ways to lasso the nearly infinite amount of information associated with the human genome, manage it and translate it into precise medical treatments."

"Tonellato said Insilico Med hopes by next year to be able to begin offering hospitals and clinics detailed information on the best way to treat patient diseases based on a combination of genetic information, personal and family histories, laboratory tests and clinical data."

"The heart of Insilico Med is technology that has been developed by the Medical College's Bioinformatics Research Center."

redux [08.01.01]
Stanford Medical Informatics Preprint Archive Challenges for Biomedical Informatics and Pharmacogenomics

"Pharmacogenomics requires the integration and analysis of genomic, molecular, cellular, and clinical data, and thus offers a remarkable set of challenges to biomedical informatics. These include infrastructural challenges such as the creation of data models and data bases for storing this data, the integration of these data with external databases, the extraction of information from natural language text, and the protection of databases with sensitive information. There are also scientific challenge in creating tools to support gene expression analysis, three-dimensional structural analysis, and comparative genomic analysis. In this review, we summarize the current uses of informatics within pharmacogenomics, and show how the technical challenges that remain for biomedical informatics are typical of those that will be confronted in the post-genomic era."

redux [08.06.01]
Science Defining Disease in the Genomics Era
[ summary can be viewed for free once registered]

"The human genome sequence will dramatically alter how we define, prevent, and treat disease. As more and more genetic variations among individuals are discovered, there will be a rush to label many of these variations as disease-associated. We need to define the term disease so that it incorporates our expanding genetic knowledge, taking into account the possible risks and adverse consequences associated with certain genetic variations, while acknowledging that a definition of disease cannot be based solely on one genetic abnormality."

"In thinking about how clinicians use the term disease, we think that three elements should be considered: disease is a state that places individuals at increased risk of adverse consequences. Treatment is given to those with a disease to prevent or ameliorate adverse consequences. The key element in this definition is risk: deviations from normal that are not associated with risk should not be considered synonymous with disease. Our definition has three definable elements and should serve clinicians well. Of course, its success will depend on whether it becomes clinically useful."

redux [05.31.01]
Wired News Fingering Cancer Genes

"Genes have fingerprints just like fingers, which got one cancer researcher thinking.

Since the FBI uses neural networks -- a type of artificial intelligence built to imitate neuron function in the brain -- to sift through masses of computerized fingerprint data to solve crimes, why not do the same for genetic fingerprint data?"

""We trained (the neural networks) to recognize this is one cancer and this is another and this is not a cancer," Kahn said. "Eventually it learned to recognize particular features that were particular for cancer.""

Family Physicians? Electronic Network Diagnostic Algorithms: results at last!

"We seem to forget, sometimes, that the first researchers in AI that chosen medicine as a problem domain did so, not because of an interest in medicine, but because of an interest in diagnosis as an example of intelligent behavior. Medical diagnosis was one example (perhaps a poor one given that there are much simpler and easier models in other physical systems). Automated diagnosis has rarely interested the medical community, not because of a fear of removing the human element (we've already done that with our reimbursement system) or of replacing humans with machines but, more simply, because diagnosis (as most people view it), is not really the problem. Most clinicians manage some form of diagnosis and most patients are treated appropriately. What is needed is better information on the utility of information and the means to obtain it which least stresses the system. The best source of this information may, in fact, be pooled knowledge of real patients, not compiled knowledge of some particular problem domain.

Of course there are probably not 10 people in NIH who have read Krakauer's article so I don't expect to see any sorely needed policy shifts in NIH funding in the next few years."

Friday, August 10, 2001

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"An unprecedented amount of computational analysis is used for genetics discovery. The entire field of bioinformatics has partially evolved around the genomics industry. This presents a wealth of computational inventions that many people in the genomics industry may not recognize as an invention. These overlooked inventions may represent an even larger treasure than is first apparent because many are based upon algorithms that are more widely adaptable to other industries than are traditional research tools.