{bio,medical} informatics
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Stanford Medical Informatics Preprint Archive
Associating Genes with Gene Ontology Codes Using a Maximum Entropy Analysis of Biomedical Literature
"Functional characterizations of thousands of gene products from many species are described in the published literature. These discussions are extremely valuable for characterizing the functions not only of these gene products, but also of their homologs in other organisms. The Gene Ontology (GO) is an effort to create a controlled terminology for labeling gene functions in a more precise, reliable, computer-readable manner. Currently, the best annotations of gene function with the GO are performed by highly trained biologists who read the literature and select appropriate codes. In this study, we explored the possibility that statistical natural language processing techniques can be used to assign GO codes. We compared three document classification methods (maximum entropy modeling, naïve Bayes classification, and nearest-neighbor classification) to the problem of associating a set of GO codes (for biological process) to literature abstracts and thus to the genes associated with the abstracts. We showed that maximum entropy modeling outperforms the other methods and achieves an accuracy of 72% when ascertaining the function discussed within an abstract. The maximum entropy method provides confidence measures that correlate well with performance. We conclude that statistical methods may be used to assign GO codes and may be useful for the difficult task of reassignment as terminology standards evolve over time."
redux [03.17.02]
[requires 'free' registration]
"The great challenge in biological research today is how to turn data into knowledge. I have met people who think data is knowledge but these people are then striving for a means of turning knowledge into understanding. Knowledge and science are related words and to know, I believe, is to understand. Before rushing to convert genomics to 'genamics' and finding that it is another dead end, we should consider evacuating the Tower of Babel. We need a theoretical framework in which to embed biological data so that the endless stream of data, filled with the flotsam and jetsam of evolution, can be sifted and abstracted.
Very simply, the network we should be interested is not the network of names but the network of the objects themselves. The language of these objects is not the Oxford Dictionary of Molecular Biology—the Ontology Consortium's main source—but that of molecular recognition, the language of molecular biology itself."
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The Washington Post
Swiss Firm Plans to Share Rice Genome
"One of the world's largest agricultural companies is putting finishing touches on a plan to make public huge amounts of genetic information about the rice plant, an effort to accelerate research aimed at improving one of mankind's most important crops."
"The plan Syngenta is working on is, in part, an effort to stave off an incipient controversy."
"Syngenta's decision to share some data with the International Rice Genome Sequencing Project may help to quiet a growing controversy about public access to data gathered through privately funded sequence projects. But the decision by Science to allow Syngenta to publish without making its data available in Genbank will undoubtedly spur further debate."
redux [03.19.02]
"Prominent gene researchers fear that access to the complete DNA sequence of rice, the world's most important food crop, will be restricted when it is published in a scientific journal."
"Science says the issue is complex. "We have to weigh the benefit of publishing some data so that it is in the public domain or having it all deposited as privately held trade secrets," says Science spokesperson Ginger Pinholster. "In the case of the human genome it was felt that publishing was the best option - for rice, the case is even stronger.""
"Twenty leading geneticists are protesting against a deal that will allow a multinational company to control who has access to the complete DNA sequence of the rice genome – the most important food crop in the developing world.
The scientists, who include British Nobel laureates Sir Paul Nurse and Sir Aaron Klug, are up in arms against a plan to lock away the entire rice sequence on a company database rather than having it published in the open scientific literature."
redux [05.09.01]
"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."
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GenomeWeb
From Post-Dot-Com Doldrums, Traditional IT Courts Biology
"A crowd of 400 software entrepreneurs slumped into a lecture hall here this month to learn a few secrets of biology and drug discovery.
What they found was that unlike the traditional IT gigs they're more accustomed to, the land where informatics intersects with life sciences does not necessarily have a universal language."
redux [03.12.02]
"While other IT sectors are struggling to keep their heads above water, the Bio-IT sector is gaining rapid momentum, according to analysis from IDC's new research and advisory service, Bio-IT Infrastructure. In addition, the research suggests the Bio-IT market will increase at a compound annual growth rate (CAGR) of 24% to nearly $38 billion by 2006."
redux [12.05.01]
"The world's largest computer makers, faced with sagging consumer demand, are betting that the huge data crunching needs of nascent biotechnology firms will grow into a multi-billion dollar market for their equipment and consulting services over the next decade."
""The average individual can't comprehend what has happened in the last half dozen years, where the two greatest medical discoveries, the genome and the microchip, have converged," said Cal Stiller, chief executive of the $250 million Canadian Medical Discoveries Fund."
"We need companies that are on the informatics side that say 'holy cow', we have just stumbled onto the mother lode! We know nothing about mining that area, but we can build the best drilling equipment out there," added Stiller."
redux [06.26.01]
"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 [08.14.01]
"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."
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Fairfax Station Times
BioinfoWhat?
"Nancy-Jo Manney still chuckles when asked to recall her first brush with bioinformatics. "When we first started exploring it a year ago, it was 'BioinfoWhat?' That's what we called it," said Manney, executive director of the Springfield Chamber of Commerce."
"So what exactly do bioinformatics companies do?"
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The Economist
Deviations from the mean
"AT SOME point during their education, biology students are told about a conversation in a pub that took place over 50 years ago. J.B.S. Haldane, a British geneticist, was asked whether he would lay down his life for his country. After doing a quick calculation on the back of a napkin, he said he would do so for two brothers or eight cousins. In other words, he would die to protect the equivalent of his genetic contribution to the next generation."
"All of these examples fit economists' arguments that Homo sapiens is also Homo economicus —maximising something that economists call utility, and biologists fitness. But there is a residuum of human activity that defies such explanations: people contribute to charities for the homeless, return lost wallets, do voluntary work and tip waiters in restaurants to which they do not plan to return. Both economic rationalism and natural selection offer few explanations for such random acts of kindness. Nor can they easily explain the opposite: spiteful behaviour, when someone harms his own interest in order to damage that of another. But people are now trying to find answers."
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The Scientist
The Rise of Biological Databases
[requires 'free' registration]
"The genomics revolution and the Internet have changed science in ways impossible to imagine 20 years ago. Among other advances, these forces have allowed the latest research to be routinely gathered, organized, and disseminated, typically at little or cost, through online biological information databases.
Arduous to use and filled with mostly unanalyzed data early on, these computer databases are now packed with valuable, up-to-date information made easily accessible with improved search engines. They have become so ubiquitous and integral to science today that almost every molecular biologist consults one when initiating research projects. "It would be impossible to do molecular biology properly these days without access to them."
redux [05.09.01]
"It may seem surprising, considering the amount of publicity the Human Genome Project has garnered over the past year, but a recent Wellcome Trust survey indicates that only half of biomedical researchers using genome databases are familiar with the services provided by Ensembl and other freely available options.
Although the number of hits on the Ensembl website has doubled since the publication of the Human Genome Project’s findings in Nature in February, a questionnaire sent to 777 individuals funded by the Wellcome Trust found that only 82 used Ensembl regularly, 189 used it occasionally, and only 50 percent of those who used DNA databases regularly used Ensembl at all.
Even more surprising was the finding that of those who didn’t use Ensembl, 50 percent had never heard of it.""
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New Scientist
Fears over rice genome access
"Prominent gene researchers fear that access to the complete DNA sequence of rice, the world's most important food crop, will be restricted when it is published in a scientific journal."
"Science says the issue is complex. "We have to weigh the benefit of publishing some data so that it is in the public domain or having it all deposited as privately held trade secrets," says Science spokesperson Ginger Pinholster. "In the case of the human genome it was felt that publishing was the best option - for rice, the case is even stronger.""
"Twenty leading geneticists are protesting against a deal that will allow a multinational company to control who has access to the complete DNA sequence of the rice genome – the most important food crop in the developing world.
The scientists, who include British Nobel laureates Sir Paul Nurse and Sir Aaron Klug, are up in arms against a plan to lock away the entire rice sequence on a company database rather than having it published in the open scientific literature."
redux [05.09.01]
"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."
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digitalMASS
Compaq chief's comment stuns biotech crowd
"It's one of the toughest questions in biotechnology: Should businesses obtain patents on genetic information about plants, animals or humans? Michael Capellas, CEO of Compaq Computer Corp., surprised an audience of biotechnology specialists yesterday when he suggested that the answer should be "no.""
"In a comment that stunned the audience into several seconds of silence, Capellas responded to a question on the issue by flatly saying that companies shouldn't be able to patent genes. But he quickly backed away from the comment, pleading ignorance of all the ramifications of the issue. "If you're asking me what should be patentable," Capellas said, "I don't know.""
redux [02.07.02]
"Patents may make some genetic tests so expensive that ordinary labs cannot afford to offer them, says a team of researchers who interviewed staff at 119 US facilities.
Patents are meant to provide an incentive for companies to put their discoveries into the public domain. But some researchers wonder if prohibitive costs could in fact have the opposite effect, by keeping standard genetic tests out of the reach of all but a few laboratories. That would have far-reaching consequences not only for health care, but for clinical research and quality control, the researchers say."
redux [08.20.01]
""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 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 [02.27.01]
"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 [08.26.00]
"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."
redux [04.26.00]
""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.""
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The Scientist
Life Sentences
[requires 'free' registration]
"The great challenge in biological research today is how to turn data into knowledge. I have met people who think data is knowledge but these people are then striving for a means of turning knowledge into understanding. Knowledge and science are related words and to know, I believe, is to understand. Before rushing to convert genomics to 'genamics' and finding that it is another dead end, we should consider evacuating the Tower of Babel. We need a theoretical framework in which to embed biological data so that the endless stream of data, filled with the flotsam and jetsam of evolution, can be sifted and abstracted.
Very simply, the network we should be interested is not the network of names but the network of the objects themselves. The language of these objects is not the Oxford Dictionary of Molecular Biology—the Ontology Consortium's main source—but that of molecular recognition, the language of molecular biology itself."
redux [01.08.02]
"Research directed toward discovering how genetic factors influence a patient’s response to drugs requires coordination of data produced from laboratory experiments, computational methods, and clinical studies. A public respository of pharmacogenetic data to which investigators from different centers can contribute will facilitate hypothesis generation for further research. We are developing a pharmacogenetics knowledge base (PharmGKB) that will support storage and retrieval of experimental data and conceptual knowledge. We are confronted with the challenge of designing an Internet-based resource that integrates complex biological, pharmacological, and clinical data in such a way that researchers can submit their data and users can retrieve information that supports genotype phenotype correlations. Successful management of the names, meaning, and organization of concepts used within the system is crucial. We have selected a frame-based knowledge-representation system for development of an ontology of concepts and relationships that represent the domain and that will permit storage of experimental data. Preliminary experience shows that the ontology we have developed for gene-sequence data submissions is appropriate for experimental data that researchers will enter."
"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."
redux [05.10.00]
"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 [03.22.01]
"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."
redux [02.28.01]
"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 [01.17.01]
"Personal bibliography on query mediation, database integration, database interoperability and related topics, concentrating on projects in genomic research."
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Stanford Medical Informatics Preprint Archive
PharmGKB: the Pharmacogenetics Knowledge Base
"The Pharmacogenetics Knowledge Base (PharmGKB; http://www.pharmgkb.org) contains genomic, phenotype and clinical information collected from ongoing pharmacogenetic studies. Tools to browse, query, download, submit, edit and process the information are available to registered research network members. A subset of the tools is publicly available. PharmGKB currently contains over 150 genes under study, 14 Coriell populations and a large ontology of pharmacogenetics concepts. The pharmacogenetic concepts and the experimental data are interconnected by a set of relations to form a knowledge base of information for pharmacogenetic researchers. The information in PharmGKB, and its associated tools for processing that information, are tailored for leading-edge pharmacogenetics research. The PharmGKB project was initiated in April 2000 and the first version of the knowledge base went online in February 2001."
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Dr. Dobbs's TechNetCast
O'Reilly Bioinformatics Technology Conference
"Select audio proceedings from 2002 O'Reilly and Associates Bioinformatics Technology Conference. Over 700 scientists, researchers, programmers and bioinformaticians come together to examine the state of computational biology and learn from each other's study and practice.
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Wired News
The Whole Critter Catalog
"When it comes to cataloging the earth's inventory of living organisms, it turns out that scientists know relatively little. Taxonomists have identified fewer than 2 million species out of the 10-to-100 million that may exist on the planet.
To remedy this, a group of tech gurus and scientists launched the All Species Inventory , an initiative with a simple yet ambitious goal: to discover, name and classify every living species on Earth within one generation, or 25 years."
redux [07.02.01]
"Earlier this month, 18 nations agreed to establish the Global Biodiversity Information Facility (GBIF) in Copenhagen, which will establish a standard method for data exchange about such specimens for researchers in different countries. By developing a kind of online phone book of the world's major plant and animal collections, the potential for new scientific discoveries could be huge."
"But the big task right now is just getting the stuff online. As a database project, it could make the Human Genome Project look simple by comparison."
""Man has been collecting biological data for centuries," said Dr. John Curran, assistant chief of the Commonwealth Scientific and Industrial Research Organization's division of Entomology (aka insects). "The genome people had the advantage in that they started collecting and working with their data after computers existed.""
redux [10.01.00]
[ summary can be viewed for free once registered ]
"Bioinformatics and biodiversity are terms so recently added to the scientific lexicon that they feature in none but the very latest dictionaries. "Bioinformatics" gained common currency in the early 1990s to describe the tools and techniques for storing, handling, and communicating the massive and ever-increasing amounts of biological data emerging principally from genomics research. Made possible by dramatic improvements in computational power and accessibility, bioinformatics has become a major growth industry almost in its own right. Edward O. Wilson, whose guest Editorial appears on page 2279, coined the term "biodiversity" in the 1980s, to encompass the taxonomic and functional diversity of living organisms. Although not a new field in itself, it represented the realignment and closer relationships between the existing sciences of systematics, ecology, and evolution; it also provided a unified rallying cry for conservation.
"In a sense, bioinformatics and biodiversity were made for each other."
[ summary can be viewed for free once registered ]
"In our Special Issue of 29 September 2000, we take a look at the emerging science of "biodiversity informatics" -- the efforts under way to make the vast, decentralized resources of global biodiversity information available in digital form, and the enormous challenge of imposing consistency and compatibility among the scores of searchable databases on the world's biota.
For the browsing pleasure of our readers, we've collected the various Websites discussed in the Special Issue Viewpoints by Bisby and Edwards et al. -- along with some other sites related to the union of information technology and biodiversity studies -- together in this special supplement."
"It is not surprising that information about biodiversity forms the basis of one of our most important knowledge domains, vital to a wide range of scientific, educational, commercial, and government uses. Unfortunately, most biodiversity information now exists in forms that are not easily accessed or used. From traditional paper-based libraries to scattered databases of varying size and physical specimens preserved in natural-history collections throughout the world, our record of biodiversity is uncoordinated and poorly integrated, and large parts of it are isolated from general use. We lack the technologies needed to effectively gather, analyze, and synthesize these data into new discoveries. As a result, this information is not being used as effectively as it could by scientists, resource managers, policy-makers, or other potential client communities. The good news is that research activities are being conducted around the world that could improve our ability to manage biodiversity information, and the emerging field of biodiversity informatics is attempting to meet the challenges posed by this domain."
"This paper supports the OECD Megascience Forum for Biological Informatics on the technical aspects of its plan for the Global Biological Information Facility. The paper identifies the capacity to produce homepages for all species of organisms as the main goal of GBIF, but in such a way that the homepages are dynamically derived from online databases. GBIF should lead to an accelerated rate of describing new species and to new information markets on biodiversity, and complement the Clearing House Mechanism of the Convention of Biological Diversity. It is seen as the critical success factor that an infrastructure is erected for biodiversity similar to what exists for molecular biology. Its cornerstones are regional centres that provide longevity and co-ordination, a distributed object-oriented database architecture based on co-operating agents, data interchange with XML, and seamless use of both existing and new databases. At the heart of the infrastructure, a new Biological Addressing System is suggested that maps the volatile but commonly used scientific names to stable Biodiversity Identifiers that are derived from IPv6. A separate treatment for the name and taxon concepts is deemed essential in this architecture. Finally, issues for research and education are discussed."
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News.Com
Compaq, Singapore plan bio-supercomputer
"Compaq Computer Corp and Singapore's Nanyang Technological University (NTU) agreed on Tuesday to invest S$12.4 million ($6.8 million) to develop the largest life sciences supercomputing facility in the region.
The costs, shared equally by both parties, will go mainly towards hardware and software for the newly launched Bioinformatics Research Centre (BIRC) at NTU."
"While other IT sectors are struggling to keep their heads above water, the Bio-IT sector is gaining rapid momentum, according to analysis from IDC's new research and advisory service, Bio-IT Infrastructure. In addition, the research suggests the Bio-IT market will increase at a compound annual growth rate (CAGR) of 24% to nearly $38 billion by 2006."
redux [12.05.01]
"The world's largest computer makers, faced with sagging consumer demand, are betting that the huge data crunching needs of nascent biotechnology firms will grow into a multi-billion dollar market for their equipment and consulting services over the next decade."
""The average individual can't comprehend what has happened in the last half dozen years, where the two greatest medical discoveries, the genome and the microchip, have converged," said Cal Stiller, chief executive of the $250 million Canadian Medical Discoveries Fund."
"We need companies that are on the informatics side that say 'holy cow', we have just stumbled onto the mother lode! We know nothing about mining that area, but we can build the best drilling equipment out there," added Stiller."
redux [11.09.01]
"Celera Genomics, the first company to successfully sequence the human genome, announced a deal with Compaq Canada Corp. yesterday that will give Canadian non-profit researchers access to its genomic database."
""This is the first time we've entered into an agreement where the computing environment and the data will go hand in hand," said Dr. Craig Venter, president of Celera and one of world's foremost genome researchers. "There's been interest in giving Canada access to this information for some time, it just hasn't been possible to get it together.""
redux [06.26.01]
"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 [08.14.01]
"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."
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GenomeWeb
DoubleTwist Crashes and Burns; Assets Are Put on the Block
"After months of layoffs and near-death spasms, DoubleTwist has closed its doors.
"It was decided that the money wasn't there to continue operations," said Nicole Litchfield, a former spokesperson for the beleaguered bioinformatics company. "The plan is to sell intellectual property assets and anything else that they can get value out of. [The company] is looking for buyers.""
"The emerging field of bioinformatics, the use of computers to analyze the inner workings of biology, is transforming an industry that just a decade ago relied on the manual labor of chemists and biologists. But even as it does so, bioinformatics is floundering as a business.
Shares of public companies that sell biological data or software are trading at a fraction of what they did two years ago. Dozens of companies have crowded into the field. Some have folded; others have survived only by morphing into drug-discovery companies.
''It's a hard market to build a business around,'' said Oliver Fetzer, a vice president at Boston Consulting Group."
redux [02.11.02]
"LIKE EVERY BUBBLE, this one had to burst. Stock prices of many bioinformatics firms have fallen sharply in recent years. LION Biosciences of Germany went public at $40 a share and now trades at about $13. Iceland’s DeCode is worth a fourth of its former high. Even Celera, the U.S. firm that helped decode the human genome, is off its peak.
Falling stock prices are a symptom of a greater disappointment in bioinformatics. A few years ago the laborious and quirky process of drug discovery seemed on the verge of giving way to new streamlined, data-driven methods. Some firms organized the blizzard of genetic data into databases that researchers could mine with search engines from still other firms. Software companies built computer programs that modeled what goes on in human cells and even whole organs. Many investors came to believe that bioinformatics would open a new avenue to the discovery of drugs. But this avenue simply hasn’t materialized. Says biotech analyst Earling Refsum at Nomura Bank in London: “Bioinformatics has not helped Big Pharma get more drugs into the pipeline.”"
redux [01.15.02]
"The deal, anticipated to close before April, gives Lion control of NetGenics' DiscoveryCenter platform, its 60 scientists and bioinformaticists, and a deal the privately held informatics firm has recently struck with Schering."
"The company, based in Cleveland, has been hurting recently: It earned $2.3 million during the first nine months of 2001 and spent $11.7 million during the same period."
"Its current cash position is "negligible," Glynias said in an interview, and Michael Clulow, who covers Lion for UBS Warburg, said that "NetGenics has an unhealthy balance sheet.""
redux [01.03.02]
"Inside the laboratories of the world's major pharmaceutical companies and biotechnology start-ups, an emerging science is quietly transforming the drug industry. Bioinformatics -- the use of computers to analyze the inner workings of biology -- is helping researchers pinpoint the roots of diseases and design sophisticated medicines to treat them.
But even as it becomes a vital part of drug research, bioinformatics as a business is losing favor with investors. Shares of publicly traded firms that sell biological data and software tools are slumping, and venture capitalists are increasingly wary of investing in such companies.
"Don't call Protein Pathways a bioinformatics company. At least not anymore."
"In the "bioinformatics business model [there] is not enough money to interest venture capitalists," said Matteo Pellegrini, Protein Pathways' president and co-founder. "So to grow a company beyond a niche software company you have to move to drug discovery. We don't see the database software model as viable for us. We see informatics as internal to drug discovery.""
redux [12.18.01]
"There comes a point in the life cycle of every organism when it must change or perish. For bioinformatics, the time for metamorphosis is now. Though computational biology is already an intrinsic part of the drug discovery process, the business models adopted by most bioinformatics firms have failed to produce profits. Competition -- from the IT industry and big pharma itself -- is growing and investors, both public and private, are unimpressed. While some companies are hoping persistence pays off, many are pursuing new business models that should allow them to retain a bigger share of the profits they are helping to create."
redux [11.27.01]
The bioinformatics industry - broadly defined as using computers in drug discovery - generated revenue of $1.38 billion in 2000, analysts at Frost & Sullivan figure. That number will reach at least $6.9 billion by 2007, analysts predict.
Although computers have been used by biotechnology and drug companies for at least a decade, the bioinformatics segment has taken off only in the last three years. And most believe it isn't anywhere near its potential.
``It's an exciting area, but it's an area that will come into its own in the next three to five years,'' said Brad Peters, Frost & Sullivan senior industry analyst.
redux [11.20.01]
"A new Frost & Sullivan report augurs an explosion in the U.S. bioinformatics market from $1.38 billion in 2000 to $6.9 billion in 2007. The industry is full of players, and there's almost certain to be consolidation. The friendly capital markets of 1999 and 2000 allowed many to raise enough cash to hold out for the best bid."
redux [07.16.01]
"A year after the deciphering of the human genome boggled the world, investors are realizing that manipulating genes to fight disease is still in its infancy -- and far from profitable."
Nowhere is that more clear than in the industry for genetic information, or bioinformatics."
redux [03.14.01]
"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..."
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The New York Times
'Digital Biology': Is This Chip Educable?
[requires 'free' registration]
"Biologists tolerate a level of mystery in their work that would drive your average engineer or computer programmer crazy. They've put together a complete rough draft of the human genome but they have little understanding of how those 40,000 or so genes work together to make a human. They've mapped every muscle and nerve in a fly's wings, yet still struggle to explain how it keeps from crashing into a wall. No engineer would build a DVD player without knowing what every circuit was for; no programmer would let a computer write its own code. Or at least that's how things used to be. As Peter J. Bentley demonstrates in ''Digital Biology,'' the cool, rational temple of technology is becoming infested with biology's weedy enigmas.
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Science
Systems Biology: A Brief Overview
[ summary can be viewed for free once registered ]
"To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism. Properties of systems, such as robustness, emerge as central issues, and understanding these properties may have an impact on the future of medicine. However, many breakthroughs in experimental devices, advanced software, and analytical methods are required before the achievements of systems biology can live up to their much-touted potential."
redux [02.26.02]
"Over the last few years, there’s been an explosion of information in biology. The mapping of the human genome gave biologists unprecedented detail about some 30,000 to 40,000 genes. Efforts are also under way to identify the thousands—and potentially millions—of proteins encoded by those genes. Researchers are now pursuing the next logical step in integrating all this data: systems biology.
The goal is to understand not just the functions of individual genes, proteins and smaller molecules like hormones, but to learn how all of these molecules interact within, say, a cell. Biologists hope to then use this information to generate more accurate computer models that will help unravel the complexities of human physiology and the underlying mechanisms of disease. The biggest payoff: faster development of more-effective drugs."
redux [04.05.00]
[requires 'free' registration]
"I suspect that although the new enthusiasm for computers in biology is genuine, it overlooks some basic problems in implementation. The basic difficulty, as I see it, is that although biologists use computers, they do not trust everything that comes out of them. It is one thing to use them to print up nice-looking graphs, but it is an entirely different matter to use them to think better."
"Francis Crick was once quoted as saying that no biologist had ever made a discovery using a mathematical model. I would reply that no biologist has ever made a discovery by running an electrophoretic gel. They make discoveries by using their brains. Computers, like all scientific tools, are only as good as the person who uses them. If biologists don't understand how computer models are constructed, they won't know their strengths and limitations. Without some foundation of trust, biologists will be unlikely to utilize or accept this powerful method of data analysis."
redux [02.05.02]
"The project has been a pet of Gov. Gray Davis, who helped seed QB3 with $75 million in state funding. Intel co-founder Gordon Moore has quietly pledged an additional $10 million to launch this novel high-tech/biotech collaboration."
"Kelly said the future will involve figuring out how millions upon millions of interactions between inanimate genes and proteins somehow give rise to life at the cellular level -- a field called systems biology."
redux [01.19.02]
"The integration of bioinformatics with these systems approaches is an integral, essential feature. One of the things that we stress is that in the future it's going to be increasingly important for people in bioinformatics to be intimately associated with data producers, because no matter how smart you are you can't model biological complexity--it's just too complex. The only way we're going to understand it is through the integration of these global experimental observations, together with powerful computational tools for analysis, and ultimately, for modeling.
A mistake that a lot of people in bioinformatics have tended to make is thinking that you can set up a bioinformatics center and it can work in isolation from the biology, and it can study all these great databases and learn lots and lots about biology. In vitro biology and in silico biology are all popular terms, but it isn't true, and it isn't going to be true in the future."
redux [04.18.01]
[requires 'free' registration]
"Systems biology is a loosely defined term, but the main idea is that biology is an information science, with genes a sort of digital code. Moreover, while much of molecular biology has involved studying a single gene or protein in depth, systems biology looks at the bigger picture, how all the genes and proteins interact. Ultimately the goal is to develop computer models that can predict the behavior of cells or organisms, much as Boeing can simulate how a plane will fly before it is built.
But such a task requires biologists to team up with computer scientists, engineers, physicists and mathematicians. The structure of universities makes that difficult, Dr. Hood said."
redux [03.17.01]
"When Lee Hood started the Institute for Systems Biology, a project to build an integrated research supercenter for the biological sciences, few doubted the validity of the concept, but many wondered whether the technology existed to make it work.
Now, in a sign that others are also willing to gamble on the idea, systems biology is attracting commercial attention. Beyond Genomics (BG), a startup based in Cambridge, Mass., is attempting to glean medically-relevant information from multiple systems simultaneously, from genes to metabolites, by using software that identifies patterns in these systems caused by disease."
redux [07.13.00]
"A new mathematical biology is emerging. Building on experimental data from developing organisms, it uses the power of computational methods to explore the properties of real gene networks."
"Our understanding of gene networks is at an early stage. We perceive their complexity only after it has been filtered by the limitations of the techniques used to study them. Genome databases and DNA-chip technology, which enables huge numbers of genes to be screened for activity, will undoubtedly provide more, and much more complicated, data than anything produced by Drosophila genetics. If a relatively simple gene network such as the segment-polarity system is hard to understand intuitively, we can be certain that modelling will be essential to make sense of the flood of new data.
But this will not be elegant theoretical modelling: rather, it will be rooted in the arbitrary complexity of evolved organisms. The task will require a breed of biologist–mathematician as familiar with handling differential equations as with the limitations of messy experimental data. There will be plenty of vacancies, and, on present showing, not many qualified applicants."
redux [05.15.01]
"Our Mission is to develop an integrated, easy-to-use environment, the workbench , which will enable biologists to create, manipulate, display and analyze biological models at molecular, cellular and multicellular levels. We are focusing on biochemical networks including mass action kinetics, metabolic pathways, stochastic simulation, gene expression and regulation."
"One of the key aspects of out project is to facilitate collaboration among existing developers and users of system biology software. We aim to do this by providing an open-source software infrastructure which will enable collaborators to freely use and share each other's computational resources."
redux [07.11.00]
"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