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{bio,medical} informatics

Monday, August 13, 2001

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find rt skeptics saw something entirely different in today's announcement. One fund manager, an Humelated articles. powered by google. Milwaukee Journal Sentinal Using genetics to personalize medical care

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

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

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

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

redux [08.01.01]
find related articles. powered by google. Stanford Medical Informatics Preprint Archive Challenges for Biomedical Informatics and Pharmacogenomics

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

redux [08.06.01]
find related articles. powered by google. Science Defining Disease in the Genomics Era
[ summary can be viewed for free once registered]

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

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

redux [05.31.01]
find related articles. powered by google. Wired News Fingering Cancer Genes

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

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

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

find related articles. powered by google. Family Physicians? Electronic Network Diagnostic Algorithms: results at last!

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

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

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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