{bio,medical} informatics
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Healthcare Informatics
Truth AND Consequences"Space has been called the last frontier. But now modern science has begun exploration of another new territory: the human genome. In mapping this instruction book of life, researchers are becoming able to pinpoint genes for a wide array of diseases and to guide creation of revolutionary new drug treatments.
But this new age of discovery also is resurrecting old issues of privacy and discrimination. Medicine can now accurately predict who will contract certain illnesses, such as Huntington's disease, but it still cannot save patients from its debilitating effects. On the other hand, a woman might test positive for a gene predisposing her to breast cancer but nevertheless live a long, cancer-free life.
How can medical records be protected so patients are free to be tested for genetic defects without losing health insurance or being unfairly eliminated on job applications? Those who work with medical records--whether electronic or paper-based--will undoubtedly come face-to- face with such privacy considerations very soon, if they haven't already."
redux [05.15.00]
[requires 'free' registration]
"Lawrence Berkeley National Laboratory in California has settled a class-action suit over genetic and medical testing for more than $2 million. The suit was brought by employees who charged that they were discriminated against and that their privacy was invaded when they were tested for pregnancy, syphilis, and genetic traits without their knowledge. Each of the plaintiffs will get $25,000, and other employees may get $2,000 each. The settlement also covers legal fees estimated at $440,000.Reference: Lehrman, S. 2000. Medical tests cost Lawrence Berkeley $2.2 million. Nature 405(6783):110."
redux [07.18.00]
"Privacy advocates, still reeling from last year's passage of legislation that allows banks and insurance companies to share personal information, are bracing against a new threat to the confidentiality of medical and financial information: The Human Genome Project.
"Latanya Sweeney, professor of computer science and public policy at Carnegie Mellon University, said currently more than 40 US states have laws requiring hospitals to make available to insurance companies and researchers certain information about each visit they receive, including the diagnosis, birth date, ethnicity, gender and Zip code of all patients discharged.
While state regulations say such categories are sufficiently anonymous to conceal the identity of patients, Sweeney said companies can and do match such information with personally identifiable data, using just a few publicly available resources."
""It may surprise some to know that 87 percent of the US population is uniquely identifiable today by just their birthday, gender and zip code," Sweeney said."
"Sweeney said the stakes become much higher when genetic information comes into play. For instance, she said, gender can usually be identified using just the base of a person's DNA sequence. Using a larger chunk of DNA information, researchers can infer particular diseases by catalogued and known sequence patterns. Link those sequences to publicly available hospital data, and you have an undeniably complete picture of an individual's most private information, Sweeney said."
redux [06.08.00]
"Unless they begin preparing now, health plan executives and medical directors could be blindsided by the revolution in medicine that will come with the mapping of the human genome, members of a managed care conference keynote panel warned on Monday."
"You think the genetic revolution is still 3-to-5 years off for your health plans," said Dr. Billings, who also serves as deputy director and chief medical officer of the Heart of Texas Veterans Health Care System. "I have to tell you, you better wake up. The tsunami is on the horizon," he warned.
For example, Schering-Plough's Dr. Haverty predicted that gene-based information could lead to the identification of many different types of asthma. As a result, health plans will need to develop many new codes and to upgrade their information systems, he said."
redux [03.30.00]
"I think one of the toughest things we all have to deal with is updating our dictionaries. In the simplest cases, the name of an organism is changed and we just have to do the maintenance. It is tougher, when, as with Citrobacter, they do genetic studies and say, "Oh, it's really six different organisms, not one." We have the human genome project coming very quickly. Even that is just the tip of the iceberg. We're not only going to see all the genes; we're then going to see clinical tests based on gene expression. Essentially, you'll be able to look at something on the order of 180,000 gene products and whether they're up or down regulated. How are we going to integrate such an incredible amount of data at a time when we're going to also be changing how we think about these processes? Classification and simple mapping are not going to work, because the lumpers and splitters are going to be arguing furiously on a daily basis."
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GenomeWeb
DeCode Plans to Commercialize Software, Double Informatics Staff"DeCode Genetics has piled up a mountain of data. Not only does it have legal access to the health records for the entire nation of Iceland, it has collected DNA from over 40,000 of the country’s inhabitants and genotyped over 33,000, according to CEO and founder Kari Steffanson.
And this means the small-population genetics company is going to have to make a huge leap forward in the informatics realm.
“The big challenge of the future will be the development of knowledge from the data that already exists rather than the development of new data,” said Steffanson by phone from his office in Reykjavik, Iceland. “I’ll bet you any amount of money that over the next five to 10 years, our company will be much more an informatics company than a biology company.”"
redux [06.15.00]
"DNA molecules are entirely separate from medical records. In the future, however, the DNA molecule and the medical record are likely to merge into one when it becomes possible to sequence a person's entire genome and put that information on a computer chip or disk. This is not deCODE's current project, but we should not wait until this step is taken to explore its implications. The most important questions would then be who has the authority to make such a disk in the first place; who owns the disk; who controls the use of the disk; and whether the disk containing the genome should be treated as specially protected medical information, as is the case for psychiatric and drug-dependency records? In clinical settings, it seems reasonable to treat such a disk as containing particularly private and sensitive medical information. It also seems reasonable to permit patients to agree to have their entire genome scanned without detailing the tens of thousands of tests that would be run. This is akin to consent to a battery of tests during an annual physical examination.
On the other hand, in a research setting, or when a specific genetic disorder is suspected, the creation and use of an individual patient's genome disk should be subject to the informed consent of the patient. And since they can be both separated from the medical record and readily recreated, research subjects should retain the right to have the files containing their genetic information destroyed at any time.
Iceland's experience with deCODE provides a useful catalyst for formulating fair and ethical rules for research on genetic variation. The Icelandic experience demonstrates that people are concerned about how genetic research is done, that medical-records research and DNA-based research are not the same, that community consultation is necessary but not sufficient to justify DNA-based research ethically, that the probable benefits of such research should be spelled out as clearly as possible, and that international standards for consent to and withdrawal from research should apply directly to research on human genetic variation. Rules for such research will retain their relevance even after it becomes possible to transfer all the genetic-sequence information in a DNA molecule to a computer disk."
redux [02.13.00]
"By the spring of this year, the first draft of the human genome -- the sequence of all the genetic instructions needed to make up a human being -- will be published on the Web. But that is only the end of the beginning. Scientists still have very little idea of what most of the 100,000 or so human genes actually do, and finding out will take them into a very different area of research.
The raw material of the genome program has been anonymous samples of DNA, manipulated by complex laboratory machines that turn out information like a production line turns out widgets. But the new era of post-genome research involves analysing real people and their confidential medical records. The records are needed to match the genes that people carry with the diseases they may develop. Only then will gigabytes of genetic data into new treatments for cancer or heart disease. And that is why socialised healthcare is a vital part of post-genome research.
Countries such as the U.S., which provide healthcare through private enterprise, are useless for this sort of genetic inquiry. Only those countries which have organized the delivery of healthcare to their population in a way that is independent of the marketplace have built up the universal medical records necessary to make sense of the patterns of disease."
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BioresearchOnline
Universal gene expression software is being offered as freeware"Version 1.0 of Rosetta Inpharmatics’ Gene Expression Markup Language (GEML) Conductor tools is now available for downloading from the company website (http://www.rii.com.). This suite of applications, which employs an open-standard XML file format, enables researchers to visualize and exchange data between different gene expression databases and analysis systems.
The company refers to its GEML Conductor tool as a universal solution for visualizing and exchanging gene expression information produced by different technology platforms. It allows users to convert any well-formatted gene expression data file into a common, flexible data format.
Rosetta GEML Conductor tools' features include:
- File Conversion. Users can convert any gene expression data file, including Affymetrix GeneChip and BioDiscovery AutoGen, into the GEML format.
- Plot Viewer. Users can visualize and share data by turning any GEML profile into a plot. The Plot Viewer includes a Zoom feature, which allows magnification into or out of particular sections of a plot.
- Magic Lasso. Users can select specific plot areas for closer viewing.
- Intensity Plot Viewer. Users can measure the intensity of one channel of data against the intensity of another channel of data.
- Customizable Visualization. Users can customize groups, colors, and labels according to viewer preferences.
- InstaLink. Users can access built-in hotlinks to popular databases and information centers on the World Wide Web.
- Table Viewer. Users can convert GEML data into customizable tables with resizable and reorderable columns.
redux [10.13.00]
"Imagine that your co-worker in the next cubicle has some information you need for a report that's due soon. She e-mails it to you, but the data are from a spreadsheet program, and all you have is a word processor, so there's no possibility of your cutting and pasting it into your document. Instead you have to print it out and type it in all over again. That's roughly the situation facing biologists these days. Although databases of biological information abound--especially in this post-genome-sequencing era--many researchers are like sailors thirsting to death surrounded by an ocean: what they need is all around them, but it's not in a form they can readily use.
To solve the problem, various groups made up of academic scientists and researchers from biotechnology and pharmaceutical companies are coming together to try to devise computer standards for bioinformatics so that biologists can more easily share data and make the most of the glut of information resulting from the Human Genome Project. Their goal is to enable an investigator not only to float seamlessly between the enormous databases of DNA sequences and those of the three-dimensional protein structures encoded by that DNA. They also want a scientist to be able to search the databases more efficiently so that, to use an automobile metaphor, if someone typed in "Camaro," the results would include other cars as well because the system would be smart enough to know that a Camaro is another kind of car."
"Eric Neumann, a member of both the Bio-Ontologies and BioPathways consortia, is a neuroscientist who is now vice president for life science informatics at the consulting firm 3rd Millennium in Cambridge, Mass. (no relation to Millennium Pharmaceuticals). He says Extensible Markup Language (XML) is shaping up to be the standard computer language for bioinformatics."
redux [09.15.00]
"With XML has come a proliferation of consortia from every industry imagineable to populate structured material with standard terms (see Appendix B). By one estimate, a new industry consortium is founded every week, perhaps one in four of which can collect serious membership dues. Rising in concert are intermediary groups to provide a consistent dictionary in cyberspace, in which each consortium's words are registered and catalogued.
Having come so far with a syntactic standard, XML, will E-commerce and knowledge organization stall out in semantic confusion?"
"How are semantic standards to come about?"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."
The XML Cover Pages XML and Semantic Transparency
"We may rehearse this fundamental axiom of descriptive markup in terms of a classical SGML polemic: the doubly-delimited information objects in an SGML/XML document are described by markup in a meaningful, self-documenting way through the use of names which are carefully selected by domain experts for element type names, attribute names, and attribute values. This is true of XML in 1998, was true of SGML in 1986, and was true of Brian Reid's Scribe system in 1976. However, of itself, descriptive markup proves to be of limited relevance as a mechanism to enable information interchange at the level of the machine.As enchanting as it is to contemplate the apparent 'semantic' clarity, flexibility, and extensibility of XML vis-à-vis HTML (e.g., how wonderfully perspicuous XML <bookTitle> seems when compared to HTML <i>), we must reckon with the cold fact that XML does not of itself enable blind interchange or information reuse. XML may help humans predict what information might lie "between the tags" in the case of <trunk> </trunk>, but XML can only help. For an XML processor, <trunk> and <i> and <booktitle> are all equally (and totally) meaningless. Yes, meaningless.
Just like its parent metalanguage (SGML), XML has no formal mechanism to support the declaration of semantic integrity constraints, and XML processors have no means of validating object semantics even if these are declared informally in an XML DTD. XML processors will have no inherent understanding of document object semantics because XML (meta-)markup languages have no predefined application-level processing semantics. XML thus formally governs syntax only - not semantics."
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BioMedNet
Expression: gene by gene[requires 'free' registration]
"C. elegans has yielded large amounts of data for developmental biologists. And the worm continues to be an extraordinary research model. Most recently, researchers have succeeded in tracking the expression of 98% of the nematode's genes as it develops, matures, and eventually ages. The study provides an estimate of the number of genes expressed and the relationships between them. It could also lead to the characterization of unfamiliar genes.
Reference: Hill, A.A., Hunter, C.P., Tsung, B.T. et al. 2000. Genomic analysis of gene expression in C. elegans. Science 290(5492):809-812."
"Scientists using a “gene chip” and a beakerful of ground-up roundworms say they have been able to watch genes turn on and off as the worms were born, grew and died. The experiment is the first in which researchers have been able to watch, almost live, the genetic activity in an entire animal, and document how it changes as the animal lives and grows."
[summary - can be viewed for free once registered]
"Until now, genome-wide transcriptional profiling has been limited to single-cell organisms. The nematode Caenorhabditis elegans is a well-characterized metazoan in which the expression of all genes can be monitored by oligonucleotide arrays. We used such arrays to quantitate the expression of C. elegans genes throughout the development of this organism. The results provide an estimate of the number of expressed genes in the nematode, reveal relations between gene function and gene expression that can guide analysis of uncharacterized worm genes, and demonstrate a shift in expression from evolutionarily conserved genes to worm-specific genes over the course of development.”
redux [08.29.00]
"Since I am a computer scientist by training, I tend to think of the current situation in which the field of genomics is being driven forward by rapid technological advances as quite analogous to the sequence of events in computing that were triggered by advances in microcomputer and network technologies. I distinctly remember the early period in which it seemed clear to most computer scientists (including myself) that technical advances were very desirable and interesting, but could have little impact on either the fundamental research issues or the overall advance of the field. Most of us completely underestimated the impact of exponential price improvements in key-enabling technologies. Certainly no one that I know of foresaw in any detail the current world of computing (although a few had rare insights into the potential). As we face the world generated by the web, we should remember that as late as the early 1990s common wisdom indicated that 'movies on demand' would be the application that drove increased network bandwidth."
"As microarray data from genomic sequences become increasingly available, the expression data that will be produced will obviously be directly relevant. There will probably be other forms of data, as well, but these adequately illustrate the point: the generation of hypotheses will flow from integrating a number of such sources of data. The existence of a growing number of hypotheses will guide the rate-limiting 'wet' lab efforts."
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."
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BioMedNet
Advanced genomics promise fruit fly
exposure[requires 'free' registration]
"According to Gos Micklam, a bioinformatics expert who joined the group from industry last year, "Drosophila is a terrific model organism to work on." Despite its complexity, he notes, the fly has only twice as many genes as yeast. It is also backed by huge research interest worldwide that goes back a century or more, which has produced detailed phenotypic data.
In particular however, he draws a distinction between "deterministic" and "algorithmic" developmental mechanisms. For instance, he says, those mechanisms that create the nematode, Caenorhabditis elegans, are deterministic in that the fate of every cell is more or less pre-determined and specified from the start. But Drosophila's mechanisms are algorithmic, he notes; the cells do not have a fixed lineage, and their developmental fate is partly the result of communication between cells.
The task of integrating the huge amounts of data to produce a comprehensive profile of gene expression, which Micklam describes as "the real challenge of genomics," will take many years, he says."
"The Human Genome Project has amounted to piles and piles of information so far.
Scientists convened at the BioSilico 2000 conference here Thursday morning to talk about the best ways to make those piles useful."
""It's not who's got the best technology, but who knows best how to share the information," [Friedrick von Bohlen, chairman and CEO of LionBioscience] said."
redux [09.20.00]
"How should biomedical research be communicated? How should research be assessed and validated?"
"Below are abstracts, transcripts, and biographies from the conference. Some presentations did not lend themselves to transcription. Where possible we have supplemented them with editorials from the speakers.
We have also commissioned editorial articles from several speakers and delagates at the meeting.
All thoughts, comments, and suggestions are welcome on our email discussion list"
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Scientific Computing World
The human genome still keeps a number of secrets "The burgeoning field of bioinformatics is increasingly well served with software, including many commercial offerings. However, most of it is applied to database searching or the analysis of of the sequences for the identification of genes. The GenoStar consortium, a public/private collaboration, is a bold French attempt to develop a modular environment for wider in silico genome exploration. A computer workbench for molecular biologists studying the genetic blueprints of living organisms, not just the human genome. The modularity of the system should enable it to grow and evolve more easily as new categories of data appear and older methods of analysis are replaced."
"The consortium will market products resulting from its development effort to the pharmaceutical and biotechnology industries. Privileged access to a basic version of the platform will be available to academic laboratories for internal research purposes. 'This kind of project may add a lot of value to what people can do with the genome and the functional information coming from high throughput experiments,' says Schacter. 'I don't see other projects that would go this deep.'"
redux [09.20.00]
"Several months ago I was given a task of writing a very fast genetic sequence alignment software. For people that dont know, this software takes two gene sequences of arbitrary lenght and produces all of their possible alignments (see chapter four of this tutorial)..."
"The real problem arises in lab use where a scientist has to compare a new gene sequence to an existing database of hundreds of thousands of sequences. There are already a lot of web sites to do this but this particular piece of software was supposed to be "ours" (sigh). At first I didnt know much about the whole subject so I decided to conduct an experiment using a dynamic programming algorithm. To be fast, C was the programming language choice. The sequential version of the algorithm worked smoothly, however wasnt nearly as fast for what we wanted to do. So I decided to try and parallelize the algorithm. Writing threaded applications that work under different platforms can be a pain, no matter how much standardization people have thrown in it. Soon, my parallelized version worked on a two-cpu Alpha machine and I was pleased (it was faster too). However, when compiled under Linux or Solaris or FreeBSD it trashed the memory and then the painful task of debugging a multi-threaded application started. Due to lack of time and proper tools(my finals were coming) I abandoned the code.
"For now, I am stuck to solving matters on a single machine and telling it to do exactly what it has to, no matter what the complexity of the problem attacked is. Many people observe that Open Source usually produces tools and methods that are (better) copies of commercial originals. Perhaps an Open Source tool such as the above proposed would be a good thing to do. Give people the power, for free."
"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." [via bioinformatics.org]
"Piper is a system for managing multi-protocol connections between Internet-distributed objects. Networks, programs, files, widgets, and so on, are all treated as objects and represented in a graphical user interface (GUI) as the nodes of a flow chart (with the Pied/Piper user interface). The user can join nodes via lines that depict links for data flow, procedural steps, relationships, and so forth.
The Internet-distributed nature of Piper lets the user work in a unique way: Only the graphical representation of an object resides on a local workstation. Compute-intensive programs and large data sets can reside remotely on high-performance, high-capacity computers.
Joining nodes across the Internet can also be used to form world-wide collaboratives (such as The Loci Project) and provide an almost limitless collection of objects for the user. "
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Taipei Times
Computing power used in mapping of human genome pushing new frontiers"While commercials featuring sweaty young dancers and hip music have been the mainstay for many industries, computer server makers discovered long ago that a metal box stuffed with microchips and wires simply lacked sex appeal. So they turned to tests of raw computing power to prove their superiority, like when IBM's Deep Blue put chess champion Garry Kasparov in checkmate four years ago.
While IBM's muscle machine stood as a monument in its time, Compaq computer may have found the ultimate ad in this battle for computing power, the Human Genome project."
redux [09.14.00]
"With the completion of a "rough draft" of the entire human genome in June, government and corporate scientists have assembled enough genetic code to fill 2,000 computer diskettes.
Now, the scientific footrace shifts from spelling out the seemingly endless string of "A's," "C's," "T's," and "G's" that make up our DNA, to actually understanding what it means.
That's where a new field of "bioinformatics" comes in."
"Researchers at the University of Idaho are building their own "super" computer using parts from 40 to 100 desktop PCs. The hardware will cost only about $44,000, but with the proper connections, the system will be sophisticated enough to run experiments on "jumping genes," bits of genetic material that migrate along the DNA double helix like microscopic hitchhikers.
James Foster, the computer scientist at the University of Idaho directing the project, said that building better programs called algorithms is more important to understanding biological data than just building bigger computers.
"Nature can always defeat brute-force approaches," says James Limpan, director of the National Center for Biotechnology Information in Rockville, Md.
"We need the most clever ways of measuring things and not more CPU power," he says."
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The Dallas Morning News
Right down to the letter""If we understood the diseases better, we'd be in a better position to target therapies," said David Altshuler, a geneticist at the Whitehead Institute for Biomedical Research in Cambridge, Mass.
Traditionally, scientists have looked for disease-causing genes by studying large families afflicted with a certain condition. But given enough SNPs, researchers hope they won't have to rely on finding just the right family to study.Theoretically, researchers could simply compare the SNPs of unrelated people with high blood pressure, for instance, to those of people without the condition.
But researchers don't have proof yet that the new approach will work, said Eric Boerwinkle, a geneticist at the University of Texas Health Science Center in Houston.
"I think there's some skepticism," he said. "I don't know of an example where that's been carried out.""
redux [02.18.00]
[summary - can be viewed for free once registered]
"The genetic markers called SNPs have been widely touted as the key to personalized medicine, with drugs tailored to an individual's genotype and simple tests to determine one's risk of specific diseases. But a closed meeting held last week, sponsored by the SNP Consortium and the U.S. National Human Genome Research Institute, concluded that those promises may be harder to achieve than expected, and that more SNPs may be required to track down a particular disease gene than previously estimated.”
redux [08.01.00]
GeneLetter Inequalities and individualized medicine
"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."
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Seattle Times
Bioinformatics is next big thing in genetics work"Get out the flame thrower. Bioinformatics, a pairing of computer science with biology, is the next big thing in genetics. The new science takes us from knowing about the genetic code to understanding what it means - how genes make proteins, regulate cell function and cause disease.
Researchers on college campuses are the early entrants in this field, but there may be as many as 50 companies, such as Celera Genomics and Human Genome Sciences, selling bioinformatic products and services. The $300 million industry is expected to shoot up, perhaps to $2 billion annually, within five years."
redux [09.19.00]
"If job searching were a poker game, Alan Williams would be sitting pretty with a full house.
Fresh out of graduate school, he happens to have a rare combination of skills that drives employers to offer hefty salaries, stock options and bonuses. And it's not even a dot-com job.
Williams has a combination of computer programming and molecular biology know- how. His job is to use computers to mine the vast store of data in the human genome model."
redux [09.01.00]
[requires paid registration]
"Since Next Wave last covered bioinformatics, in our July 1996 Profiles of Bioinformaticians and February 1997 Bioinformatics Skills features, the prominence of the bioinformatician's role in modern biology has only increased. This month, Next Wave provides a comprehensive picture of the current state of bioinformatics, from the funding situation in Europe and the U.S. to the new bioinformatics degree programs and the immediate hiring needs of industrial and academic labs around the world.”
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 [06.27.00]
"A fast-growing field known as bioinformatics uses computing to analyze the vast amount of biological, genomic, and related research to make sense of things too complex for the human brain to fathom.
But bioinformatics is also a bottleneck for many drug and biotech companies that can't find enough talented software engineers who combine sophisticated analysis tools with an understanding of genomics.
''We resolve the bioinformatics issue [by hiring] two people: one who understands computer science and the biologist or researcher,'' said Kenneth Fasman, vice president and global head of informatics of AstraZeneca LLC in Waltham."
"...according to Dr. Donald Johnson, a pathologist at the Nebraska University Medical Center. He estimated there are about 60,000 jobs available to scientists and managers versed in bioinformatics."
redux [05.10.00]
"As expected, salaries for the most part climb as the level of training rises, starting in the $40,000-$50,000 range for BAs and reaching over $100,000 for one post doc. But there are exceptions. For example, two of the three undergraduates who were placed received salaries between $50,0000 to $60,000. This is higher than that earned by seven of the masters students, although ten of the nineteen masters students for whom we have salary information earn more than $60,000. One masters student received a starting salary of over $100,000. Reported salaries for five hires at the doctorate level are over $70,000. One is between $80,000 to $90,000; another is over $100,000; yet another is between $60,000 to $70,000. Three post docs received placements with a salary between $80,000 to $90,000. One post doc was placed at a salary of over $100,000. One institution reported that one or more masters student(s) received a signing bonus.""The results of our current survey make it clear that the majority of these jobs are not being filled by graduates of formal programs—who by our count represent about 15 percent of the positions advertised in 1997. And, we believe the 15 percent figure to be an overestimate given that ads have been growing over time and our most recent ad count is for 1997, a year earlier than our hiring data. This leads us to infer that most of the advertised positions are being filled by individuals trained in informal programs and by individuals who change jobs. The distinct possibility exists that a number of these jobs remain vacant for a period of time, an issue not studied here. Furthermore, our pipeline estimates (see Table 2) lead us to conclude that the number of individuals currently enrolled in formal programs falls far short of the number of positions that have recently been advertised."
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Science
The Babel of Bioinformatics[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 [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 [07.25.00]
[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 dictatorial rigidity."
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British Medical Journal
Medical software's free future"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.' "redux [06.17.00]
"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 ”
"Basic biological science has always had an impact on clinical medicine (and clinical medical information systems), and is creating a new generation of epidemiologic, diagnostic, prognostic, and treatment modalities. Bioinformatics efforts that appear to be wholly geared towards basic science are likely to become relevant to clinical informatics in the coming decade. For example, DNA sequence information and sequence annotations will appear in the medical chart with increasing frequency. The algorithms developed for research in bioinformatics will soon become part of clinical information systems. In this paper, I briefly review the intellectual roots of bioinformatics and how the field has evolved in the last few years. Fortunately, a core set of scientific paradigms have provided a focus to the field. Even in this short period, however, there has been a change in the nature of the questions being asked and the types of experiments being attempted. These changes are consistently leading bioinformatics towards problems of clinical relevance. Some molecular biology information systems already have important clinical implications. I will discuss the differences in the culture and approach to science of clinical informatics and bioinformatics, but will argue that the two disciplines share important intellectual challenges which make them very closely allied fields (despite the cultural differences). Finally, I will identify a few areas common to both disciplines where developments in one field may help catalyze faster progress in the other. For example, useful database integration technologies have (arguably) matured more rapidly within bioinformatics than in clinical informatics. At the same time, clinical informatics embraced the idea of controlled terminologies relatively early, and offers lessons to those in bioinformatics attempting similar tasks."
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]
""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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Wired News
The Science of E-Publishing""Publishers are reluctant to give away content because they are concerned that advertisers may go away," said Jerome Kassirer, former editor-in-chief of the New England Journal of Medicine. "Advertisers pay more attention to the number of subscriptions to paper journals than to the number of eyeballs on any given website."
"There's a lot of anxiety that if (print journals) have an electronic offering, people will migrate online and they will lose their paper subscription revenues," agreed Tony Delamothe, editor of BMJ Online, a medical association journal that, unlike most journals, does not charge to access its electronic content.
Some insist that simply publishing electronically is not enough --and that open, free access is necessary to disseminate global research."
redux [09.20.00]
"How should biomedical research be communicated? How should research be assessed and validated?"
"Below are abstracts, transcripts, and biographies from the conference. Some presentations did not lend themselves to transcription. Where possible we have supplemented them with editorials from the speakers.
We have also commissioned editorial articles from several speakers and delagates at the meeting.
All thoughts, comments, and suggestions are welcome on our email discussion list"
"What if you could wave a wand, in this very Harry Potter decade, and make libraries - at least digital libraries - more open, more easy to manage, cheaper, and even more eclectic and democratic? What if content contributors could submit, catalog, index, manage, rate and rank materials in large collections themselves? I believe that, thanks to the innovations from the Open Source community and perhaps more importantly the Free Software community, that we can have a contributor-run library at this very moment.
In fact, there are several very successful examples from which we can draw not only best practices, but also - that grail of the programmer - working code. But better still, these projects are also examples of vibrant, lively, noisy, democratic communities. "
"Librarians are increasingly called upon not only to collect information in electronic form but also to organize it into digital libraries. The materials may be created and held locally, or they may be created and accessed in a distributed fashion as a virtual library. Digital libraries can provide material on a variety of topics, from children's games to high-energy physics. Their scope may be local, national, or even international; the audience may be a small group with specialized interests or the broader public. Essential to the successful implementation and use of any digital library is the organization of that library, either directly or indirectly, by one or more knowledge organization systems (KOS).
The term knowledge organization systems is intended to encompass all types of schemes for organizing information and promoting knowledge management. Knowledge organization systems include classification and categorization schemes that organize materials at a general level, subject headings that provide more detailed access, and authority files that control variant versions of key information such as geographic names and personal names. Knowledge organization systems also include highly structured vocabularies, such as thesauri, and less traditional schemes, such as semantic networks and ontologies. Because knowledge organization systems are mechanisms for organizing information, they are at the heart of every library, museum, and archive. "
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GeneLetter
Physiologic, not genetic, factors dominate in p53-associated lung cancer"Physiologic stresses, not genetic mutations, represent the main risk factors in p53-associated lung cancer, according to a report in the online early edition of the Proceedings of the National Academy of Sciences."
"The number of G:C to T:A transversions from the coding part of the p53 gene was substantially higher among smokers than among nonsmokers and in smoke-accessible tissue compared with smoke-inaccessible tissue, the report indicates.
The strand-specific patterns of p53 mutations, however, were indistinguishable between the smokers and nonsmokers, whether nontranscribed (coding) strands (NTS) or transcribed (noncoding) strands (TS) were examined.
"This unambiguously suggests that the major shaper of specific G to T spectra is not smoking-induced adducts but something else entirely, namely, selection," the researchers assert."
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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The Scientist
N.Y. Panel Explores Genomics Issues[requires 'free' registration]
"What can people expect from biotechnology and genomics? Ten luminaries from the biomedical arena, law, and journalism grappled with issues related to that question at the City University of New York's Graduate Center on Sept. 20. In attendance was an audience of 350 whose research, medical, and counseling careers could hinge on how such issues are resolved. Syracuse University's Gene Media Forum (www.genemedia.org) sponsored the event.
The recurring theme was biological predictability. Eric Lander, director of the Whitehead Institute Center for Genome Research, in Cambridge, Mass., noted that in the past century, biologists "worked out a disease by being clever enough to figure out what was wrong." The systematic approach of genomics, he continued, would render research largely predictable.
Panelists stressed, nevertheless, that genomics would not yield answers easily. Harold Varmus, president of Memorial Sloan-Kettering Cancer Center in New York, said that biologists were used to studying one gene at a time. Now, he added, "you've got all the parts of the clock dumped on the table, and you can look at them. But, you know, it's a lot harder to put back together, too."
A consensus emerged that much of the public--including many journalists, behavioral scientists, and physicians--either were unaware of this newfound complexity or twisted it into misguided support for genetic determinism. "
redux [06.26.00]
""How it's going to help me develop drugs or do anything, I really don't have a clue," said Craig Rosen, executive vice president for research and development at Human Genome Sciences."
""It's like being given the best book in the world, but it's in Russian, and it's incredibly boring to read," said Ewan Birney, a team leader at the European Bioinformatics Research Institute, part of the Sanger Centre, one of the major labs working on the Human Genome Project."
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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CBC
IBM's presence shines spotlight on marriage of genetics and information technology"When a company as rich and well-known as IBM Corp. gets behind something as cutting-edge as First Genetic Trust, a new repository for all your most personal DNA secrets, it's clear something big is happening.
That something is bioinformatics, the use of computers to sift through the mind-boggling amounts of data collected in the study of genetics."
"In the long run, perhaps 20 years from now, individuals may be able to sit with their doctor, download some of the genetic information over the Internet and use it to select a treatment or drug, Holden says.
But for the next few years, First Genetic will be mainly a buffer between pharmaceutical companies doing genetic research and individuals - guaranteeing to protect the people who have agreed to DNA analysis.
It remains to be seen whether Holden can convince the public of First Genetic's independence. The company's main source of revenues for the foreseeable future will be fees paid by drug companies for access to the information in First Genetic's database."
redux [10.10.00]
"A new company, First Genetic Trust, Inc., has been formed to protect the privacy and security of individuals' genetic information, while also supporting the application of such data to advance medical research, diagnosis and treatment."
"Founded by leaders in the fields of pharmacogenetics, bioinformatics, and information systems technology, First Genetic Trust will provide genetic data handling and bioinformatics services to pharmaceutical companies, medical researchers, and health care providers engaged in genetic research. The company also will be a leading on-line portal for genetic information, education and counseling services, to facilitate individuals' decision-making regarding the use of their private genetic information."redux [06.15.00]
"The incentive for patients to open a genetic bank account is not simply a free toaster. As personalized medicine moves from theory to the doctor’s office, First Genetic Trust will " take your information and the information from [a drug response] profile, BLAST the two together and informatically provide that diagnostic back to the provider," said Holden. He noted that initially the data gathered would be used for research purposes only.
The bank account model is an alternative to what Holden called " the ludicrous concept of having this information on a credit card, which they can lose or it can become encrypted."
The business model counts on revenue from pharmaceutical companies, healthcare providers, and, yes—insurance companies."