Friday, September 28, 2001

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"The government has approved the first gene-based test to tell quickly whether an HIV patient's virus is mutating to make a particular drug therapy fail, important to know so the person can switch AIDS medications."

"With Trugene, a doctor sends a patient's blood sample to one of 130 labs where Visible Genetics so far has trained personnel. A computer decodes the HIV genes in that blood, identifying all the genetic mutations present. Then a software program matches those mutations to a list of more than 70 mutations currently linked to resistance in specific drugs."

redux [01.18.01]
The New York Times When Gene Sequencing Becomes a Fact of Life
[requires 'free' registration]

"The gene-sequencing machines that unraveled the human genome were nearly the size of refrigerators and cost $300,000 apiece. Richard T. Daly's sequencers fit easily on a desk ? and he is giving them away.

The reason is that Mr. Daly wants to move gene sequencing from research laboratories into daily medical practice. The company he heads, Visible Genetics, has developed a test to sequence genes of the virus that causes AIDS, providing information to help doctors choose which of the 15 or so available drugs will work best against a particular patient's infection.

"You've got a huge medicine cabinet to pick from and no good way to pick," said Mr. Daly, whose company is publicly traded and based in Toronto."

redux [07.06.00]
Proceedings of the National Academy of Sciences Production of resistant HIV mutants during antiretroviral therapy

"HIV drug therapy often fails because of the appearance of multidrug-resistant virus. There are two possible scenarios for the outgrowth of multidrug-resistant virus in response to therapy. Resistant virus may preexist at low frequencies in drug-naïve patients and is rapidly selected in the presence of drugs. Alternatively, resistant virus is absent at the start of therapy but is generated by residual viral replication during therapy. Currently available experimental methods are generally too insensitive to distinguish between these two scenarios. Here we use deterministic and stochastic models to investigate the origin of multidrug resistance. We quantify the probabilities that resistant mutants preexist, and that resistant mutants are generated during therapy. The models suggest that under a wide range of conditions, treatment failure is most likely caused by the preexistence of resistant mutants."

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]
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."

Thursday, September 27, 2001

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"DoubleTwist said Thursday that the European Bioinformatics Institute, an outstation of the European Molecular Biology Laboratory, now supports DoubleTwist's genomic annotation XML format, AGAVE."

"Researchers can use the data transformation tools to convert data from publicly available genomics databases such as GenBank, EMBL, and Swiss-Prot into AGAVE format. Converted data can then be used in viewers and programs that support the format."

XEMBL Project What is the XEMBL Project?

"XEMBL is all about bringing EMBL Nucleotide Sequence data to our users in a variety of formats. The publically available EMBL/GenBank/DDBJ data is kept at the EBI in an Oracle database, from which flatfiles are created at every release for the purpose of distribution. As you might be aware of, flat-files have severe limitations, and we have been asked various times if we are going to distribute the EMBL data in different formats as well, XML being the one most prominently mentioned. In short, the XEMBL project will bring to the user several alternative formats of EMBL data."

redux [07.10.01]
Individual.Com DoubleTwist Releases Genomic Annotation XML Format as Open Standard; New Web Site Launched to Provide Access to Data Format and Tools

"DoubleTwist, Inc. today announced that the genomic annotation XML format used to create its annotated human genome database is now freely available as an open standard to the life sciences community. AGAVE (Architecture for Genomic Annotation, Visualization and Exchange) allows users to manage, visualize and share annotations of genomic sequences using the document type definition (DTD) and associated tools available through www.agavexml.org."

"AGAVE was originally developed as part of DoubleTwist's bioinformatics architecture for high-throughput analysis of the human genome, which relies heavily on XML and Java technologies and tools. Central to AGAVE is a Java Object Model and a corresponding XML Document Type Definition (DTD) that facilitate data exchange, data integration and data transformation between components."

Agave.Org Introduction

"The design goals of AGAVE are to provide a comprehensive, extensible, open and readable markup language for genomic annotation. AGAVE is comprehensive because it can represent all the relevant biological data in public databases such as NCBI's GenBank, including the full sequence location format. It is extensible because it uses generic elements for computational results that can easily be used to capture results from new sequence annotation algorithms. Because AGAVE is XML-based, it is easy to use as an open standard for data storage and exchange. You can write programs to manipulate and extract genomic data using standard XML libraries, and you can easily transform data in the AGAVE format from and to other XML-based formats using tools such as XSLT (eXtensible Style Language Transformation). For example, you can easily transform data in GAME format to AGAVE format using XSLT templates. To aid readability, AGAVE focuses on biological data and uses standard biological terminology with a minimum of abbreviation."

redux [02.28.01]
PENN Database Research Group K2/Kleisli and GUS: Experiments in integrated access to genomic data sources

"The integration of heterogeneous data sources and software systems is a major issue in the biomedical community and several approaches have been explored: linking databases, "on-the-fly" integration through views, and integration through warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: an integration system called K2, which has primarily been used to provide views over multiple external data sources and software systems; and a data warehouse called GUS which downloads, cleans, integrates and annotates data from multiple external data sources. Although the view and warehouse approaches each have their advantages, there is no clear "winner". Therefore, users must consider how the data is to be used, what the performance guarantees must be, and how much programmer time and expertise is available to choose the best strategy for a particular application. Our experiences also point to some practical tips on how updates should be published by the community, and how XML can be used to facilitate the processing of updates in a warehousing environment."

redux [03.22.01]
Peter Karp A Vision of DB Interoperation

"To realize the full potential of biological databases requires more than the interactive, hypertext flavor of database interoperation that is now so popular in the bioinformatics community. Interoperation based on declarative queries to multiple network-accessible databases will support analyses and investigations that are orders of magnitude faster and more powerful than what can be accomplished through interactive navigation. I present a vision of the capabilities that a query-based interoperation infrastructure should provide, and identify assumptions behind, and requirements of, this vision. I then propose an architecture for query-based interoperation that identifies a number of novel components of an information infrastructure for molecular biology. Those components include: A knowledge base that describes relationships among the conceptualizations used in different biological databases; a module that can determine what known DBs are relevant to a particular query; a module that can translate a query, or the results of a query, from one conceptualization to another; a family of DB drivers that provide uniform physical access to different DBMSs; a family of translators that can interconvert among different database schema languages; and a database that describes the network location and access methods for biological databases. A number of the components are translators because biological databases exhibit heterogeneity at several different levels, including the conceptual level, the data model, the query language, and data formats."

Wednesday, September 26, 2001

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"Sounding an awful lot like the genomics gurus of yesteryear, proponents of proteomics declare that a "global understanding" of proteins will reveal the underlying mechanisms of disease, leading drugmakers to treatments that ablate causes rather than mask symptoms. Companies will discover a bounty of natural proteins that can serve as injectable drugs, the advocates assure, as well as an abundance of new protein targets for the "small-molecule" pills that are the cornerstone of the pharmaceutical industry. Side effects will plummet as the precision of treatments increases. A finer appreciation of the differences between the proteomes of individuals will allow doctors to tailor treatments to specific populations. And as new technologies emerge - your entire proteome on a chip? - medicine will advance in ways that even the most farsighted visionaries cannot imagine."

"Still, not everyone shares the excitement. Some leading scientists worry that yet another bill of goods is being writ before their eyes. Sydney Brenner, who helped launch the Human Genome Project, says the proteomics craze is not about new knowledge but about amassing data?most of which he predicts will have no impact on drug discovery. "I think there will be a backlash," says Brenner, now at the Salk Institute for Biological Studies in La Jolla, CA. "I really think people will come to their senses. Science will just walk around them. [Proteomics] will prove to be irrelevant.""

redux [08.15.01]
GenomeWeb Study Foresees Proteomics Market Growing to $5.6B by 2006

"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."

Monday, September 24, 2001

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"Intellectual property is the lifeline of the biomedical sciences industry and Asia will have to embrace the concept to move forward, experts said on Friday.

"Intellectual property rights for medicine is the foundation upon which drug research is built," Klaus Leisinger, executive director of the Novartis Foundation for Sustainable Development, told the BioMedical Asia 2001 conference in Singapore."

redux [08.30.01]
BioMedNet Chinese president meets with Human Genome Project scientists
[requires 'free' registration]

"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."

Sunday, September 23, 2001

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"IBM is spending $100 million building the world's fastest supercomputer to do cutting-edge medical research, but a distributed computing effort running on ordinary PCs may have beaten Big Blue to the punch.

IBM's proposed Blue Gene , a massively parallel supercomputer, in hopes to help diagnose and treat disease by simulating the ultra-complex process of protein folding.

"But Folding@Home , a modest distributed computing project run by Dr. Vijay Pande and a group of graduate students at Stanford University, has already managed to simulate how proteins self-assemble, something that computers, until now, have not been able to do."

redux [07.13.01]
Wired Magazine Gene Machine

"Ambuj Goyal, IBM Research's general manager for software, solutions, and strategy, was more ambitious than that. Why not build a machine to model molecular dynamics using general-purpose chips rather than specialized ones? That way you'd produce a prototype for a whole new family of supercomputers. Not only would it be great technology development, it would be great marketing, too. Whereas the Department of Energy has the greatest interest in top-end supercomputing - with its need to understand how nuclear weapons work - focusing on the life sciences rather than the death sciences could make supercomputing more widely appealing. What's more, a biology program would be a way of telling one of the newest markets for big iron - the post-genome biotech world - that IBM took its interests seriously. "We believe that the life sciences are going to be a rapidly growing area," says Blue Gene project manager Bill Pulleyblank, "a huge growth area for IBM."

Scientific American The Do-It-Yourself Supercomputer

"Our solution was to construct a computing cluster using obsolete PCs that ORNL would have otherwise discarded. Dubbed the Stone SouperComputer because it was built essentially at no cost, our cluster of PCs was powerful enough to produce ecoregion maps of unprecedented detail. Other research groups have devised even more capable clusters that rival the performance of the world's best supercomputers at a mere fraction of their cost. This advantageous price-to-performance ratio has already attracted the attention of some corporations, which plan to use the clusters for such complex tasks as deciphering the human genome. In fact, the cluster concept promises to revolutionize the computing field by offering tremendous processing power to any research group, school or business that wants it."

"Above all, the Beowulf concept is an empowering force. It wrests high-level computing away from the privileged few and makes low-cost parallel-processing systems available to those with modest resources. Research groups, high schools, colleges or small businesses can build or buy their own Beowulf clusters, realizing the promise of a supercomputer in every basement. Should you decide to join the parallel-processing proletariat, please contact us through our Web site (http://extremelinux.esd.ornl.gov/) and tell us about your Beowulf-building experiences."

redux [08.29.01]
Nature: Science Update Parasite corrals computer power

"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 [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."

redux [04.05.00]
egroups : Decentralization Description

""*Is decentralization ever a good idea? If so, when? Is there non-anecdotal evidence on costs and benefits?

*What protocol issues are there? Can we begin assembling a good protocol for decentralized messaging? To what degree do the protocols for Freenet, Gnutella or WorldOS meet the need? Do we need an application protocol or something lower level? Can HTTP do the job? Can we implement peer routing as an add-on to existing protocols? Is there a call to develop an IETF working group?

* Given that authoring and versioning are critical but hard in a decentralized environment, how can we approach the job? Is it possible to integrate WebDAV with peer networking?

* What are the business issues? Who are the players? Who else stands to win or lose, and why?

At present many people and groups are working on the issues in isolation, some for competitive reasons and some for lack of an alternative. My belief is that a communal approach will be more productive."

Friday, September 21, 2001

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"A proteomics company has hired Compaq to create database systems to organize and compute data on thousands of memory-heavy protein images.

Structural Genomix (SGX), of San Diego, California, uses X-ray crystallography to take pictures of protein structures on an industrial scale. These three-dimensional images take up huge amounts of memory, which is where Compaq comes in."

"The deal was worth between $2 and $3 million, which includes upgrades and special access to Compaq's latest and greatest life sciences technologies, Chad Smith, associate director of information technology at SGX, said."

redux [08.14.01]
Business 2.0 6,160,717,289 Cures for Cancer

"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..."

Thursday, September 20, 2001

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"Cycorp Inc. is planning to release an open-source subset of its Cyc knowledge base, which will let programmers and developers infuse common sense into everything from search engines to CRM apps."

"Users who install the OpenCyc knowledge base will have the freedom to develop proprietary applications, which is not the case with most open-source software. They will, however, have to share any general knowledge they add to the database. De Oliveira says that, over time, Cycorp will release the bulk of the Cyc knowledge base, but it will always keep the most recent additions under wraps so it can develop some proprietary technologies of its own."

The Molecular Biology Ontology Working Group An Evaluation of Ontology Exchange Languages for Bioinformatics

"Ontologies are specifications of the concepts in a given field and the relationships among those concepts. The development of ontologies for molecular-biology information and the sharing of those ontologies within the bioinformatics community are central problems in bioinformatics. If the bioinformatics community is to share ontologies effectively, ontologies must be exchanged in a form that uses standardized syntax and semantics. This paper reports on an effort among the authors to evaluate a number of alternative ontology-exchange languages, and to recommend one or more languages for use within the larger bioinformatics community. The study selected a set of candidate languages, and defined a set of capabilities that the ideal ontology-exchange language should satisfy. The study scored the languages according to the degree to which they provided each capability. In addition, the authors performed several ontology-exchange experiments with the two languages that received the highest scores: OML and Ontolingua. The result of those experiments, and the main conclusions of this study, was that the frame-based semantic model of Ontolingua is preferable to the conceptual graph model of OML, but that the XML-based syntax of OML is preferable to the Lisp-based syntax of Ontolingua."

Wednesday, September 19, 2001

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"Future understanding of genomic data may be severely limited unless bioinformaticists gain a better understanding of knowledge representation, according to Peter Karp, director of SRI International's Bioinformatics Research Group."

"As biological research grows more and more dependent on information technology to make sense of increasing amounts of genomic data, Karp wrote, it will be crucial for bioinformaticists to keep up with new developments in symbolic computing. "The genome revolution is increasing the need for pathway databases in the biological sciences, and similar developments will occur in other sciences. However, effective implementation of this paradigm is hampered because most biologists (and most other scientists) receive essentially no education in databases or knowledge representation."

According to Karp, equipping scientists with a better understanding of knowledge representation concepts--such as data models, ontologies, database query languages, logical inference, database design, and formal grammars--will be necessary in order to carry the field forward."

redux [08.19.01]
Stanford Medical Informatics Preprint Archive Management of Data, Knowledge, and Metadata on the Semantic Web: Experience with a Pharmacogenetics Knowledge Base

"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."

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."

redux [05.01.00]
Stanford Medical Informatics Preprint Archives Ontology-Oriented Design and Programming

"In the construction of both conventional software and intelligent systems, developers continue to seek higher level abstractions that both can aid in conceptual modeling and can assist in implementation and maintenance. In recent years, the artificial intelligence community has placed considerable attention on the notion of explicit ontologies -- shared conceptualizations of application areas that define the salient concepts and relationships among concepts. Such ontologies, when joined with well defined problem-solving methods, provide convenient formalisms for modeling and for implementing solutions to application tasks. This chapter reviews the motivation for seeking such high-level abstractions, and summarizes recent successes in building systems from reusable domain ontologies and problem-solving methods. As the environment for software execution moves from individual workstations to the Internet at large, casting new software applications in terms of these high-level abstractions may make complex systems both easier to build and easier to maintain."

redux [02.07.01]
BioLisp.Org Intelligent applications in BioComputing

"BioLisp.org is a public resource supporting scientists who use Lisp to develop intelligent applications in the biological sciences. We collect and disseminate Lisp biocomputing code, and gather pointers to Lisp and other Intelligent BioComputing methods. Please contribute, or make suggestions by writing the editor."

Monday, September 17, 2001

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"India has the potential to garner 8-10 per cent of the global software market in the next few years from the current levels of just 1.5 per cent, but the country?s planners need to focus on improving computer penetration and use of Indian made software in the industry.

This was the view of FC Kohli, chairman, Tata Consultancy Services, while speaking at Connect 2001, an international conference and exhibition on information technology, communication technologies and bioinformatics, which opened on Thursday. Currently, India's IT exports are about $8.7 billion."

redux [08.27.01]
GenomeWeb Indian Software Giant Strikes Bioinformatics Deal With Government

"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."

Friday, September 14, 2001

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"SRI International, a leading research institute based in Silicon Valley, has developed a novel software system that uses artificial intelligence and symbolic computing to better understand and manipulate the overwhelming information produced by genome data. SRI's software, Pathway Tools, encodes large and complex scientific theories that are the basis of systems biology, leading to a greater understanding of biological systems, improved scientific collaboration, and more rapid integration of disparate sources of bioscience knowledge.

Pathway Tools is a software environment that supports query, analysis, and visualization operations for pathway/genome databases. Systems biology studies the complex interactions between all levels of biological information -- genomic DNA, informational pathways, and informational networks -- to understand how they work together."

Thursday, September 13, 2001

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"The term was introduced by Conrad H. Waddington in 1942.1 To paraphrase an erudite epistolary exchange in Science, he is said to contrast genetics with epigenetics , the study of the processes by which genotype gives rise to phenotype. In 1942 we had barely any clue as to what those processes are, so "epigenetic" had no connotation of the underlying chemical mechanism, whatever it was that modulated cell differentiation.

In 1994, as cited in the same issue of Science, Robin Holliday voiced a commonly apprehended drift in meaning, and redefined epigenetic as "Nuclear inheritance which is not based on differences in DNA sequence." These two memes are freely circulating and can cause muddle or mischief mainly when they recombine, namely when epigenetic-H is automatically applied to epigenetic-W."

"This neology of nucleic, epinucleic, extranucleic, has attracted few followers, I think largely because so few people had really thought through the distinctions. There is much merit in Ben Johnson's caution about unbridled proliferation of terms: "A man coins not a new word without some peril, and less fruit; for if it happen to be received, the praise is but moderate; if refus'd, the scorn is assur'd." But is a polysemy to be preferred, with thought-muddling as a further peril?"

redux [08.16.01]
Science Behind the Scenes of Gene Expression
[ summary can be viewed for free once registered]

"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, September 12, 2001

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"Copyright your DNA for just $1,500, plus shipping and handling. A San Francisco entrepreneur has launched a new company offering this service. His target market is celebrities who fear that insatiable fans will try to clone replicants from their sweat and shed skin cells. But can DNA be copyrighted? The US Copyright Office says no; a person's DNA "is not an original work of authorship."

Reference: 2001. Celebs: Guard your DNA. Science 293(5536)"

Tuesday, September 11, 2001

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"Sun Microsystems, Inc. today announced that it will grant hardware, including servers and a secure storage system, to the Open Bioinformatics Foundation, which distributes, develops and supports standards-based open source tools for life science research and data integration. The foundation will use the hardware to update its infrastructure, enabling more reliable and secure distribution of its tools and collaborative services over the Web."

""The grant from Sun puts us at a milestone in our project's history. With Sun hardware at the heart of our third-generation infrastructure, our users will benefit from superior performance, data integrity and security," said Chris Dagdigian, systems manager and project administrator for the Open Bioinformatics Foundation. "This will allow us to meet the growing demand for open-source bioinformatics tools, and continue to build international support for the open standards approach to life sciences research."

The Open Bioinformatics Foundation About

"The Open Bioinformatics Foundation is an umbrella group for the various bio*.org projects that grew out of the original BioPerl project. The goal of the foundation is to provide financial, administrative and technical assistance for our various open source life science projects."

Monday, September 10, 2001

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"One of the oldest forms of life on Earth has been revealed as a natural born computer programmer.

Scientists studying a species of single-celled protozoans called Ciliates have found that the organisms are experts at sorting, shuffling and splicing DNA when they reproduce.

Some of the repertoire of tricks Ciliates use to untangle their DNA resemble the techniques that computer programmers use to make software more elegant and robust."

Thursday, September 06, 2001

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"As the pharmaceutical industry looks for new ways to increase productivity and capitalize on the growing number of new drug targets emerging thanks to the explosion in genomics data, a new and potentially powerful tool is emerging and catching the eye of many of R&D directors across the industry. Distributed computing is quickly becoming more than a "buzz word." In fact, it's becoming a reality at some of pharma's biggest companies."

""We're intrigued by the potential of grid computing technology," said Richard Vissa, Executive Director of Global Core Technologies, Informatics, at Bristol-Myers Squibb's Pharmaceutical Research Institute. "Even a PC network of modest size has the potential to deliver the computational power comparable to some of our large supercomputers. Given the number of PCs throughout our organization, we could see a significant increase in computing performance for certain applications..""

redux [08.29.01]
Nature: Science Update Parasite corrals computer power

"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."

Wednesday, September 05, 2001

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"Publishers of established scientific journals have thus far resisted demands for freer access. In its campaign to make biomedical research literature available free online, Public Library of Science is now taking a new tack: It hopes to publish peer-reviewed, electronic journals.

"If we really want to change the publication of scientific research, we must do the publishing ourselves," says an announcement posted Sept. 1 on the group's Web site. "It is time for us to work together to create the journals we have called for."

redux [08.03.01]
BioMedNet Information wants to be free?
[requires 'free' registration]

"The boycott of scientific publishers is planned and led by a grassroots organization known as the Public Library of Science. The group has published an open letter signed by some 25,000 scientists. Signatories vowed to quit buying, publishing in, or reviewing for journals that decline to make papers available free six months after publication. The group says that it may also publish journals itself as the next step in its campaign."

Reference: Butler, D. 2001. Public library set to turn publisher as boycott looms. Nature 412(6846):469.

GenomeWeb Public Library of Science Prepares to Boycott Journals with Launch of Publishing Effort

"With the September deadline drawing nearer, Eisen told the ISMB audience that the group has "been met with hostility" by most journal publishers and is "faced with the likelihood that there will be nowhere to be published" after September 1.

"The only alternative is to create a way to publish our own journals," Eisen said.

redux [04.24.01]
Scientific American Publish Free or Perish

"When a molecular biologist or a biochemist has made a discovery - often after many months or even