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{bio,medical} informatics


Monday, April 30, 2001

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find related articles. powered by google. New Scientist Biologists in Norway use a computer program to "read" the scientific literature and successfully predict gene interactions
"Biologists in Norway have used a computer program to "read" the scientific literature and successfully predict gene interactions.

This data-mining of the "biobibliome" provides a way of dealing with the ever-increasing torrent of biological data - millions of papers a year. But even more impressively, the completely automated process can make new genetic discoveries - essentially free research."
find related articles. powered by google. Stanford Medical Informatics Preprint Archives Improving Biological Literature Improves Homology Search
"Annotating the tremendous amount of sequence information being generated requires accurate automated methods for recognizing homology. Although sequence similarity is only one of many indicators of evolutionary homology, it is often the only one used. Here we find that supplementing sequence similarity with information from biomedical literature is successful in increasing the accuracy of homology search results. We modified the PSI-BLAST algorithm to use literature similarity in each iteration of its database search. The modified algorithm is evaluated and compared to standard PSI-BLAST in searching for homologous proteins. The performance of the modified algorithm achieved 32% recall with 95% precision, while the original one achieved 33% recall with 84% precision; the literature similarity requirement preserved the sensitive characteristic of the PSI-BLAST algorithm while improving the precision."

find related articles. powered by google. MIT Technology Review Emerging Technologies That Will Change the World: Data Mining
"And the future of data-mining technology? Wide open, says Fayyad—especially as researchers begin to move beyond the field's original focus on highly structured, relational databases. One very hot area is "text data mining": extracting unexpected relationships from huge collections of free-form text documents. The results are still preliminary, as various labs experiment with natural-language processing, statistical word counts and other techniques. But the University of California at Berkeley's LINDI system, to take one example, has already been used to help geneticists search the biomedical literature and produce plausible hypotheses for the function of newly discovered genes."


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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.

BIOINFORMATICS IN THE 21st CENTURY

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