{bio,medical} informatics
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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]
"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."
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EyeforPharma
Physiome launches PACE program to promote biological simulations in research"Physiome Sciences ( http://physiome.com ) has implemented The Physiome Academic Centers of Excellence Program (The PACE Program) to enable biomedical researchers to use computer models in the design and interpretation of their research."
"The PACE Program will make its proprietary biological simulation technology available to academic collaborators. In addition, the technology will allow researchers to integrate gene, protein and functional data that are generated in their labs, to simulate and visualize how cells work and the mechanism of disease pathways."
redux [02.16.01]
"Computers capable of mimicking life have long been the stuff of sci-fi nightmares—think The Terminator or 2001's HAL 9000. But for researchers struggling to make sense of vast amounts of new biological data, and for drug companies anxious to cut costs and speed development, having accurate computer simulations of living systems is still a dream. To make that dream come true, they are turning to "in silico biology," building computer models of the intricate processes that take place inside cells, organs, and even people. The ultimate goal: an entire organism modeled in silicon, allowing researchers to test new therapies much as engineers "fly" new airplane designs on supercomputers."
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 [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 [02.24.00]
[summary - can be viewed for free once registered]
"Computer simulations give the impression of precision, but they are founded on a raft of assumptions, simplifications, and outright errors. New tools are needed, scientists say, to quantify the uncertainties inherent in calculations and to evaluate the validity of the models. But making uncertainties evident is a tough challenge, as evidenced by several recent workshops.”
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BioMedNet
New consortium to put microarray data into your hands[requires 'free' registration]
"Leaders of an effort to standardize and centralize gene expression data on tumor samples today described their vision for an international non-profit consortium to make such microarray data available to all researchers. The non-governmental project aims to increase the rate of discovery and improve patient care, said Jeffrey Trent, scientific director of the National Human Genome Research Institute speaking at the American Association for Cancer Research conference in New Orleans."
redux [05.24.00]
"With the advent of DNA microarray and 'chip' technologies...gene expression in an organism can be examined on a genomic scale, allowing the transcription levels of many genes to be measured simultaneously2. For instance, we can study the effects of a compound (such as a drug) on the level of expression of many genes...With gene expression, context is everything: without it, the information is meaningless. For example, the precise stage of a tumour sample could have a crucial bearing on the interpretation of expression measurements. This context can be infinitely detailed, and it is this detail that must be captured in gene-expression studies.
The bioinformatics underlying the management of these huge volumes of data are crucial if any sense is to be made of gene-expression experiments. A single microarray experiment looking at 40,000 genes from 10 different samples, under 20 different conditions, produces at least 8,000,000 pieces of information."
"It is time to create a public repository for microarray data, with standardized annotation (see Box 2, overleaf). But this is a complex and ambitious project, and is one of the biggest challenges that bioinformatics has yet faced. Major difficulties stem from the detail required to describe the conditions of an experiment, and the relative and imprecise nature of measurements of expression levels. The potentially huge volume of data only adds to these difficulties. However, it is this very complexity that makes an organized repository necessary.
Important tasks to be undertaken include: (1) agreement on the essential information that should be reported for a microarray experiment; (2) definition of ontologies and an extensible, structured document format to capture these data and their semantics; (3) production of a database to store these documents; and (4) development of tools for searching documents in a database and using the semantic context to allow comparisons and sophisticated queries."
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Yahoo! News
LION bioscience Launches Version 6.1 of the SRS Data Integration System"LION bioscience AG (Neuer Markt: LIO, WKN 504 350; Nasdaq: LEON) today introduced an updated version of it's unique data integration technology SRS. SRS 6.1 constitutes a major new release of the SRS system enabling the integration of flat-file, XML and relational databases into a single system that enables researchers to easily access all available data sources relevant for their work."
"SRS 6.1 offers expanded capabilities of SRS in a number of important areas:
* Full XML server to easily integrate any XML data source, and to serve
any XML data structure, regardless of whether the data source is in XML
* Virtual libraries which provide users more flexibility in presenting
data to their customers
* Support for additional indexing technologies
* Improved application launching capabilities, providing more powerful
and intuitive access to applications and results
* A beta-version of a new module to integrate relational databases"
"Genomics Collaborative has hired GeneticXchange to provide data integration software to the company and its academic collaborators over a period of five-years, the companies said Monday."
" GX-Engine, according to Edwards, allows GCI to access disparate public and proprietary databases and algorithms, combine the information in a standard format, and perform multiple searches."
redux [03.11.01]
"Research by Silico Research concludes that the deployment of data warehousing technology is widespread in the pharmaceutical, biotechnology and genomic sectors, with 77% of companies surveyed currently deploying at least one data warehouse somewhere in the R&D pipeline. Virtually all those who are not deploying data warehousing technology today expect to be doing so by 2004. This implementational build-out will combine with the fact that individual biopharmaceutical companies are deploying more warehouses across more functions to increase the number of warehouses in the sector by 36% a year and by 150% over the next three to four years."
"Today, data warehouse deployment is focused at the departmental level. "Companies believe, as a article of faith, that they should link scientists and researchers across the enterprise. How they go about doing this is another matter. We're seeing a lot of testing of federated and virtual warehouses and other middleware solutions but no clear answers so far", continued Emmett Power."
redux [03.22.01]
"Besides the proposed query language, IBM has built an experimental "dataless" database system that gets the user the information needed from a variety of sources by breaking down a query into its parts. Each part is addressed to the database system or repository that can supply an answer, even though the data may reside in radically different systems and formats. When the results come back, they are assembled as one report or assembled view to the user."
"The system will be a "virtual database" or a federation of heterogeneous databases, and a pilot Discovery Link system has been in use for several months by pharmaceutical companies trying to research and manufacture new drugs.
"Pharmaceutical companies have the highest pain point" in trying to assemble diverse data, noted Jim Kleewein, developer of DataJoiner, an IBM predecessor product that extracts data from known sources. The drug companies are trying to combine information gleaned from the human genome, bio-informatic databases where human responses to chemical compounds are stored and new chemical interaction databases."redux [02.28.01]
"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."
"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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O'Reilly Network
Business Computing Isn't Where The Action Is Going to Be"The conjunction of hacker interest in science, the enormous commercial potential of genomics, proteomics and other bioinformatics disciplines, and the availability of cheaper supercomputing via distributed computation, seem to me to be an explosive mix."
"Every time we've had a radical lowering of the barriers of entry into a computing market, that market has exploded. The industry-standard IBM PC architecture liberated software developers from the need to work for hardware vendors; the open standards of the internet, plus the simplicity of HTML, and the power of scripting languages, allowed content providers to build the information applications that we now take for granted on the web. Now, hackers and scientists are working together to break down the barriers to discovery."
"Scientific computing is going to be where the action is."
redux [09.07.00]
"The mapping of the human genome is the tip of the iceberg that is the biological information revolution.
University of Idaho computer scientists and mathematicians are joining biologists to explore new ways to interpret the complex genetic information that describes all living things and their relationships.
Along the way, UI students returning to school this fall will find a new course few schools could hope to offer: building a new supercomputer."
"The students will work on every step of the project, from determining the requirements the supercomputer must meet, though the purchase, assembly, software selection and installation. "They are involved from start to finish. It should be a great experience for them," Heckendorn added." ""It's commodity computing. If you can only buy commodity computers and hook them together with the right stuff in the right way, you can get supercomputing power," he said. Although multi-million dollar specialty supercomputers still dominate the high end of the market, Beowulf-style supercomputers are gaining."
redux [07.25.00]
"Are you a hacker? Do you yearn for something more important to work on than yet-another-gnome-applet? Are you annoyed that you can't find a problem that is fun to code and stretches your brain in new ways... bioinformatics might be the answer."
"The amount of data is growing faster than anyone expected and only a handful of people can both remain with academic ideals and coding potential. We need hackers to join any number of projects out there. And there are a host to join. If you just liking hacking perl or you prefer compiler technology, there is something to suit you."
redux [09.20.00]
"We often mention distributed computing models: JavaSpaces, Sash, BizTalk, WebL, and so on. Our lead column in August gave particular attention to the technical prospects for Microsoft's .NET initiative. Piper is an alternative to those models, and .NET in particular, on both engineering and business levels.
Microsoft, for example, has specific business motivations with .NET that involve licensing issues and how the company is paid for its products. Crudely, Microsoft wants to use .NET capabilities to ensure it receives payment every time its software is used. Piper, in contrast, is a free software project to make "anything and everything buildable by linking small components," even across a network, according to J.W. Bizzaro, director of Bioinformatics.org. "
"Moreover, Piper's connections are considerably richer than Unix's pipes. Rather than just a one-way, unstructured datafeed, Piper "[l]inks can depict protocol-independent data flow, procedural steps, and relationships," according to one Piper document. Moreover, those links "can merge or split streams."
Most compelling of all, perhaps, is the opportunity to escape the confines of a single desktop and access resources throughout a rich network. Piper knows how to do that, too."
redux [04.05.00]
"A researcher working on the Human Genome Project is using Napster technology, and he's not looking for T3 connections to download Moby.
Dr. Lincoln Stein, an associate professor of bioinformatics at the Cold Spring Harbor Lab in New York, is investigating ways to use Napster-type technology to allow scientists to share their discoveries of the genome.
"I was very interested when I saw Napster," Stein said. "It has a similar architecture (to what we use now), but it allows for 'peer-to-peer' data exchange and it dawned on me that it would be marvelous for our annotation system.""
"The pace of human genomic sequencing has outstripped the ability of sequencing centers to annotate and understand the sequence prior to submitting it to the archival databases. Multiple third-party groups have stepped into the breach and are currently annotating the human sequence with a combination of computational and experimental methods. Their analytic tools, data models, and visualization methods are diverse, and it is self-evident that this diversity enhances, rather than diminishes, the value of their work."
"The solution that we advocate allows sequence annotation to be decentralized among multiple third-party annotators and integrated on an as-needed basis by client-side software. A single server is designated the "reference server." It serves essential structural information about the genome: the physical map which relates one entry to another (where an "entry" is an arbitrary segment of the sequence, such as a sequenced BAC or a contig), the DNA sequence for each entry, and the standard authorship information. Multiple sites then act as third-party "annotation servers." Using a web browser-like application, researchers can interrogate one or more annotation servers to retrieve features in a region of interest. The servers return the results using a standard data format, allowing the sequence browser to integrate the annotations and display them in graphical or tabular form. No attempt is made to automatically resolve contradictions between different third-party annotations. Indeed, it is the ability to facilitate comparison among different centers' annotations that distinguish this proposal. We currently have a working prototype of this system based on ACeDB servers and CGI scripts, and are now generalizing this architecture to support other client and server combinations."
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BioMedNet
Celera human genome data not Wellcome[requires 'free' registration]
"The Wellcome Trust has told its grantees that they may not use Wellcome money to subscribe to the Celera Genomics human genome database. Since Wellcome helped provide funding for the public Human Genome Project, it wants researchers to use the free public databases. Celera says no problem; scientists can still access the free portion of the company's data. A Wellcome official says that the policy is just a way of getting value for its money, because there's no evidence that the private database is better than the public one.
Reference: Adam, D. 2001. No Wellcome money for Celera. Nature 410(6827):397."
redux [01.11.01]
"A new chapter in the storied and stormy relationship between the National Institutes of Health and Celera Genomics has apparently begun, as NIH officials are now negotiating with Celera for terms of access to its genome database, a NIH spokesman told GenomeWeb Friday."
"If NIH scientists do gain access to Celera's database - at the price of between $7,000 and $15,000 per head - they would effectively be paying for a souped-up version of their own Human Genome Project research published in GenBank, plus Celera's own sequencing research."
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Conference
BIOKDD, 2001:Workshop on Data Mining in Bioinformatics"Bioinformatics is the science of storing, extracting, organizing, analyzing, interpreting, and utilizing information from biological sequences and molecules. It has been mainly fueled by advances in DNA sequencing and mapping techniques. The Human Genome Project has resulted in an exponentially growing database of genetic sequences. Knowledge Discovery and Data mining (KDD) techniques will play an increasingly important role in the analysis and discovery of sequence, structure and functional patterns or models from large sequence databases. High performance techniques are also becoming central to this task."
"We solicit papers with important new insights and experiences on knowledge discovery and data mining from the modeling and simulation of complex biological systems. Topics of interest lie at the intersection of KDD and Bioinformatics."
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ZDNet
IBM Experiments With XML"Besides the proposed query language, IBM has built an experimental "dataless" database system that gets the user the information needed from a variety of sources by breaking down a query into its parts. Each part is addressed to the database system or repository that can supply an answer, even though the data may reside in radically different systems and formats. When the results come back, they are assembled as one report or assembled view to the user."
"The system will be a "virtual database" or a federation of heterogeneous databases, and a pilot Discovery Link system has been in use for several months by pharmaceutical companies trying to research and manufacture new drugs.
"Pharmaceutical companies have the highest pain point" in trying to assemble diverse data, noted Jim Kleewein, developer of DataJoiner, an IBM predecessor product that extracts data from known sources. The drug companies are trying to combine information gleaned from the human genome, bio-informatic databases where human responses to chemical compounds are stored and new chemical interaction databases."
redux [03.11.01]
"Research by Silico Research concludes that the deployment of data warehousing technology is widespread in the pharmaceutical, biotechnology and genomic sectors, with 77% of companies surveyed currently deploying at least one data warehouse somewhere in the R&D pipeline. Virtually all those who are not deploying data warehousing technology today expect to be doing so by 2004. This implementational build-out will combine with the fact that individual biopharmaceutical companies are deploying more warehouses across more functions to increase the number of warehouses in the sector by 36% a year and by 150% over the next three to four years."
"Today, data warehouse deployment is focused at the departmental level. "Companies believe, as a article of faith, that they should link scientists and researchers across the enterprise. How they go about doing this is another matter. We're seeing a lot of testing of federated and virtual warehouses and other middleware solutions but no clear answers so far", continued Emmett Power."
"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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Conference
Bioinformatics Open Source Conference 2001"The first Bioinformatics Open Source Conference, BOSC2000, convened last August in San Diego, just before ISMB2000. BOSC2001 will take place in Copenhagen on July 19-20, 2001, just before ISMB2001, and concurrent with the BioPathways meeting.
BOSC2000 featured keynote talks by Ewan Birney, Lincoln Stein, and Tim O'Reilly, as well as presentations chosen from submitted abstracts. This year, BOSC will be organized around existing open source bioinformatics projects, providing time for projects to meet personally and also to exchange ideas between projects. The mornings will feature technical talks selected from submitted abstracts. In the afternoons, project groups will be given access to computers and ethernet hubs for collaborative coding, and small across-projects meetings can be organized.
We expect the leaders of most of the major bioinformatics open source projects to be at the meeting, including:
- Matt Pocock (BioJava)
- Andrew Dalke (BioPython)
- Ewan Birney (BioPerl)
- Jason Stajich (BioPerl and BioCorba)
- Alan Bleasby (EMBOSS)
- Chris Mungall (FlyBase)
- Lincoln Stein (DAS)"
redux [04.28.00]
"We note with dismay and alarm the controversy concerning access, distribution and patenting of the human genome sequence (Nature 404, 317; 2000 & Nature 404, 324; 2000). We wish to point out some analogies between the human genome sequencing efforts and 'open-source' software development, which have implications for the data-release policy of the public sequencing effort.""The reasons why the Linux project could succeed against commercial wisdom have been analysed by Eric S. Raymond in his book The Cathedral and the Bazaar (O'Reilly, 1999). Most of these findings are of relevance to academic and commercial benefits arising from human genome sequencing." [via bioinformatics.org]
redux [10.20.00]
"As computer hardware becomes an ever cheaper commodity with ever increasing power, it is clear that software is the rate limiting step in system development. Software is slippery stuff: its possibilities seem almost limitless, but implementing a system competently is a difficult activity that commands premium rates of pay. A lot of its cost lies in planning, implementing, and monitoring and enforcing exchanges between the parties involved, who might be, for example, a hospital wanting to buy an information system and a system supplier. Such exchanges have high transaction costs. The relationship between an information systems supplier and its clients has, according to transaction cost economists, the quality of "information impactedness": a state in which one of the parties to an exchange is much better informed than the other, and the other cannot achieve information parity, except at great cost.
Even when a system is successfully commissioned, the costs can remain high. Once a customer is "locked into" proprietary software, its makers can demand premium prices, safe in the knowledge that the client would find it even more expensive to change.
It is such forces that have led to the rise of free softwaremost notably the GNU/Linux operating system, which is freely available for download from the internet."
"Free software concepts make particular sense in medicine: although peer review has its problems, medical knowledge is becoming more open, not less, and the idea of locking it up in proprietary systems is untenable. And professional staff should not invest time learning the user interface of proprietary systems that may change, be withdrawn, or be arbitrarily "upgraded" for commercial reasons. Much better instead to invest time on a system licensed under the General Public License that will always be free." [via LinuxMedNews]
redux [07.27.00]
"Good software forms seamless connections; as George Orwell said of prose, the best is like a window pane: transparent. The obscurity of commercial binaries is an obstacle to good quality communication between systems. In healthcare, good communication is too important to remain proprietary. Software developers should remain confident that there will always be work for the future in discovering, providing, and adapting applications for organizations, and training people to use them. This, rather than the sharp-suited gouging of Bill Gates wannabees, should become the predominant business model for software in the British NHS. Software engineering will become a profession more like medicine and the law: in which practitioners earn a fair hourly reward for their experience at interpreting, evaluating and applying knowledge from a specialized domain to the benefit of their clients. Current models, which restrict the sharing and development of knowledge, are certainly counterproductive and arguably unethical. Open source is the future: all we have to do is built it."
redux [09.21.00]
"Imagine a scale with all the advantages of a proprietary model on the left and all the advantages of an open-source model on the right. Pretend everybody who wants to solve a problem or build a project has a scale like this. If it tips to the left, the proprietary model is chosen; if it tips to the right, the open model is chosen. Now, as connectivity increases with the Internet, and computer power increases exponentially, more and more weight accumulates on the right. Every time computer power increases, another household gets wired, or a new simulator is built online, a little more weight is added to the right. Having the example of Linux to learn from adds some more weight to the right; the next successful open-source project will add even more.
"Perhaps the next boom in open source will come from the law; perhaps from drug X; perhaps it will be something entirely different. Although it's difficult to tell, it is quite likely that the scale is going to tip for some projects and that there will be serious efforts at open-source development in the next decade. Moreover, it's quite likely some of these projects will work."
"Wayne Wilson on the openhealth-list has a profoundly interesting summary (reprinted here with permission) of a lecture given by Lawrence Lessig, Professor for Entrepreneurial Legal Studies at Harvard. His bio and a collection of his thoughtful articles can be found here. Wilson writes: 'Lessig is a legal scholar and it is not immediately obvious that legal arguments would be appealing to us, but I think they are.' "
"The Openhealth mailing list is a place for IT professionals and members of the public who are interested in health care and open source software to gather and discuss the issues of this field. This list is provided as a public service by Minoru Development Corporation. While Minoru staff are participants of the list, they do not direct list content. Areas of discussion include:- Deployment stories
- Discussion of open source projects and products
- Question and answer
- Open source licences and their applicability to health care
- Authentication and privacy issues for data over the Internet
- Obstacles for open source software in health care ”
""An army of LinuxMedNews correspondents (me and my Chihuahua Cindy) combed the Internet to form an alphabetized, comprehensive list of medical open source medical projects resulting in 17(!) such projects and many other interesting sites. If your project or site isn't listed, please e-mail. We have opened a new section on medical software companies that support Linux.""
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BreastLink
Both Genes and Environment Play Role in Causing Cancer"The study’s analysis suggests that having a gene associated with a particular cancer does not mean that the individual carrying that gene will inevitably develop cancer. Even a person whose identical twin develops cancer has less than a 15 percent chance of having the same kind of cancer. This study thus introduces a much needed shot of reality into the media portrayal of fatalism and inevitability surrounding the issue of genetic heritage.
The study also points to a need for accelerated research into the extent to which genes interact with the environment to affect an individual’s susceptibility to disease. Most importantly, this and similar studies make it abundantly clear that the nature-versus-nurture argument is based on a false and arbitrary separation."
redux [07.13.00]
[requires 'free' registration]
"Genes may cause more than one-quarter of three major types of cancer, more than previously thought, a group of researchers says.
Scandinavian researchers concluded that genes account for 42 percent of the risk for prostate cancer, 35 percent for colorectal cancer and 27 percent for breast cancer.
The rest of the cases are caused by what people do, such as smoking and diet, or what happens to them, such as on-the-job hazards or viral infections, the researchers said."
"...the conclusion runs contrary to the widespread belief that scientists "will find solutions or cures to all diseases in the genes," Dr. Lichtenstein said. "That won't be the case."
redux [04.25.00]
"In the current issue of Advances in Complex Systems (February-April), Dr. Yaneer Bar-Yam, president of the New England Complex Systems Institute and an expert on the application of mathematical analysis to complex systems, contends that the selfish-gene theory of evolution is fatally flawed.
If his mathematical proof gains general acceptance, it will shut the door on controversial "gene-centered" views of evolution.
Bar-Yam, in the upcoming article, proves that the "selfish gene" approach is not valid in the general case. He demonstrates that the gene-centered view, expressed in mathematical form, is only an approximation of the dynamics actually at work."
"The key to Bar-Yam's analysis lies in recognizing three levels of structure in nature: the gene, the organism and the group (or network) of organisms."
redux [05.26.00]
"Research in disease aetiology has shifted towards investigating genetic causes, powered by the human genome project. Successful identification of genes for monogenic disease has led to interest in investigating the genetic component of diseases that are often termed complex, that is, they are known to aggregate in families but do not segregate in a mendelian fashion. Genetic epidemiology has permitted identification of genes affecting people's susceptibility to disease, although progress has been much slower than many people expected. While the role of genetic factors in diseases such as hypertension, asthma, and depression is being intensively studied, family studies and the large geographical and temporal variation in the occurrence of many diseases indicate a major role of the environment. Thus, it is necessary to consider findings about susceptibility genes in the context of a population and evaluate the role of genetic factors in relation to other aetiological factors. This article discusses some approaches used to resolve the genetic architecture of disease and to study the relation of genes to environmental factors in the population. "
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BioMedNet
UK biotech company focuses on "land grab proteomics"[requires 'free' registration]
"Biotechnology company Oxford Glycosciences is hoping to apply for patents over 4,000 proteins by the end of the year, as part of a "land grab" to corner the rights to promising areas of research. The firm, which yesterday announced a 62% jump in full-year losses to £16.8 million, sells information about proteins to other drugs companies. It has already made applications covering 1,500 proteins which it believes to be associated with disease. Chief executive Michael Kranda said: "We're focusing on land grab proteomics. We're really in a very good position to attack this technology."
Proteins are governed by genes in the body, and their activity is central to the maintenance of good health. Some biotechnology companies are targeting genes in the race to create new medicines but the completion of the Human Genome Project revealed that there are only about 30,000 genes in the body, rather than the expected 150,000. As a result, Kranda said proteins are becoming the new battleground: "There are 300,000 to 500,000 proteins out there. The value is really going to be in understanding the protein world."
Reference: The Guardian, 16 March 2001"
redux [12.16.00]
"For years, Dr. J. Craig Venter has been saying that the human genome probably had fewer than 60,000 genes. Heck, Dr. C. nailed most of them when he worked in partnership with Human Genome Sciences (which said back in 1996 that they'd found 96% of the human genes). Now Eric Lander of the famed Whitehead Institute at M.I.T. --- a man who has had his differences with Craig --- has also come out and said that there are fewer than 50,000 genes in the human genome.
The fact that these words have been on the airwaves for years doesn't mean that most investors have heard them. (The axiom "there are 100,000 genes in the human genome" has been pretty deeply drilled into a lot of our brains.) So at our shop, we've been proceeding under the assumption that the big genome land grab happened years ago but a large number of investors haven't noticed that fact. We also assume that most of what will transpire over the next few years will be lawsuits and cross-licensing: We refer to it as the coming "litigation conflagration."
What I'm thinking through at the moment are the implications: Specifically, how will investors react when a critical mass of them realize there are fewer than 50,000 genes -- and most of them are already spoken for?"
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.""
redux [02.27.01]
"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."
"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."
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The Atlantic Online
The Genetic Archaeology of Race"Genetics research is demonstrating that the differences in appearance among groups are profoundly incidental, but these differences do have a genetic basis. And although it's true that all people have inherited the same genetic legacy, the genetic differences among groups have important implications for our understanding of history and for biomedical research. These complications in an otherwise reassuring story have thoroughly spooked the leaders of the public and private genome efforts. The NIH has been collecting information about genetic variants from different ethnic groups in the United States, but it has refused to link specific variants with ethnicity. Celera has been sequencing DNA from an Asian, a Hispanic, a Caucasian, and an African-American, but it, too, declines to say which DNA is which.
This strategy of avoiding the issue is almost sure to backfire. It seems to imply that geneticists have something to hide. But the message emerging from laboratories around the world should be hailed, not muzzled. It is one of great hope and promise for our species."
redux [08.23.00]
[requires 'free' registration]
"Scientists have long suspected that the racial categories recognized by society are not reflected on the genetic level.
But the more closely that researchers examine the human genome -- the complement of genetic material encased in the heart of almost every cell of the body -- the more most of them are convinced that the standard labels used to distinguish people by "race" have little or no biological meaning.""
"Through transglobal sampling of neutral genetic markers -- stretches of genetic material that do not help create the body's functioning proteins but instead are composed of so-called junk DNA -- researchers have found that, on average, 88 percent to 90 percent of the differences between people occur within their local populations, while only about 10 percent to 12 percent of the differences distinguish one population, or race, from another.
To put it another way, the citizens of any given village in the world, whether in Scotland or Tanzania, hold 90 percent of the genetic variability that humanity has to offer."
""Ethnicity is a broad concept that encompasses both genetics and culture," Dr. Anand said. "Thinking about ethnicity is a way to bring together questions of a person's biology, lifestyle, diet, rather than just focusing on race. Ethnicity is about phenotype and genotype, and, if you define the terms of your study, it allows you to look at differences between groups in a valid way."
redux [08.01.00]
"Over the next few years a number of competing groups - my own company, Sequenom, among them -- will sort through the diverse genetic material of the human species to find those variations called single nucleotide polymorphisms (SNPs, pronounced SNIPS) that predispose individuals to major clinical disorders."
“At present the overwhelming bulk of the effort to identify these natural variations is in the private sector. This is inevitable because SNPs that associate with major diseases are patentable, by traditional standards."
"Whatever ensues, it is clear that the rate of discovery of medically important SNPs and their conversion into clinically useful tools will not progress equally fast or uniformly for all segments of mankind."
"It will be easier to discover medically important SNPs in geographically isolated and inbred populations in which good familial records and where migration has not introduced confounding genetic variation. Iceland and Finland are strong early candidates."
redux [07.17.00]
"The idea of using genetics to determine ethnic heritage has been growing in popularity over recent years. When Rick Kittles, a geneticist at Howard University, offered to trace tribal roots via a $350 DNA test, African Americans flooded his telephone line with requests.
"Even if an identifying marker shows up, the result isn't necessarily definitive. While certain markers may be more common to one ethnic group, most also can be found in other populations as well.
"Because of the tremendous genetic variation within populations, it would be biologically impossible to settle on a limited number of genetic markers that could define "Native Americans," says Morris Foster, an anthropologist at the University of Oklahoma who has wrestled with the risks faced by Indian tribes interested in genetic research.
Furthermore, Foster added in an e-mail interview with GeneLetter, "it is absurd to try to define what is essentially a social identity by using biological characteristics. This, though, is how racism has historically worked."
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GenomeWeb
Beyond Genomics Takes a Gamble on Systems Biology"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 [08.12.00]
"The flood of data from genome-wide analysis is transforming biology. We need to develop new, interdisciplinary approaches to convert these data into information about the components and structures of individual biological pathways and to use the resulting information to yield knowledge about general principles that explain the functions and evolution of life."
"Genomics increases the chance that biology will experience a split like the one in physics, between those who collect and those who analyze data. This will challenge the majority of biologists who believe that modeling, simulation, and theory have little to contribute to biology. This prejudice rests on insecurity engendered by most biologists' weakness in mathematics (including my own) and previous efforts to model systems using more variables than there were data points. If we keep clinging to this prejudice, we will drown in a sea of data."
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 [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 [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 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."
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BioMedNet
Species data wants to be free, too[requires 'free' registration]
"The Global Biodiversity Information Facility plans a centralized database of information on the millions of species held in museum collections. The data will be housed on its Web site and will be freely available. The project is a collaboration among 12 countries, each of which contributed to the $2 million pot that supports the project.
Reference: Kenyon, G. 2001. Network aims to link species data from global collections. Nature 410(6826):290."
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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MIT Technology Review
Gene Babel"Small DNA-laden wafers have transformed biology. Using these DNA chips, geneticists can see which genes are turned on, or expressed, in a cell at a particular time. Such gene expression experiments allow bioscientists to diagnose different diseases, quickly screen thousands of drug candidates for efficacy and safety and even learn the functions of newly discovered genes.
Sharing this information over the Web could lead to an explosion in biological knowledge. But each experiment generates gigabytes of data written in one of several formats, depending on the type of chip used. And with dozens of chips on the market and hundreds of ways to analyze the data, the Web is in danger of becoming a genetic Tower of Babel."
"Companies and academics have begun creating uniform formats for representing gene expression data, designed to work on any computer."
redux [10.21.00]
[summary - can be viewed for free once registered]
"As more and more genomes are sequenced, it is becoming clear that deciphering the clues latent in these sequences is anything but trivial. In this Techview, Attwood analyzes the current state of the art in sequence-structure-function bioinformatics. She highlights the need for precise terminology, and argues that a holistic view of complex biological systems will be an essential next step for bioinformatics.”
redux [07.25.00]
[requires 'free' registration]
"Once the world had a single language and not too many words, but then clarity deteriorated into clamor. Today in the small but prolific world of bioinformatics, another Tower of Babel is rising up, with the miscommunication due as much to the rapid expansion of information as to basic changes in how it is processed. "Horrible problems" crop up as more information is computed on instead of read by a human researcher, according to Ewan Birney, a group leader in the Ensembl genome annotation project at the European Bioinformatics Institute (EBI) in Cambridge, England.
In the early days of bioinformatics, human-readable data exchange formats such as ASN.1, the format adopted for GenBank by the National Center for Biotechnology Information (NCBI) 10 years ago, were the norm. Easily editable with a text utility, ASN.1's syntactic looseness makes it congenial to the human user, but not to the machine, which likes its inputs defined with dicta