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Data mining and the human genome
Author(s) -
Henry Abarbanel,
Curtis G. Callan,
William J. Dally,
Freeman J. Dyson,
Terence Hwa,
S. E. Koonin,
Herbert Levine,
O. S. Rothaus,
Roy F. Schwitters,
C. W. Stubbs,
P. Weinberger
Publication year - 2000
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1183979
Subject(s) - data science , computer science , genetic data , genomics , data mining , genome , biology , population , biochemistry , demography , sociology , gene
: As genomics research moves from an era of data acquisition to one of both acquisition and interpretation, new methods are required for organizing and prioritizing the data. These methods would allow an initial level of data analysis to be carried out before committing resources to a particular genetic locus. This JASON study sought to delineate the main problems that must be faced in bioinformatics and to identify information technologies that can help to overcome those problems. While the current influx of data greatly exceeds what biologists have experienced in the past, other scientific disciplines and the commercial sector have been handling much larger datasets for many years. Powerful data mining techniques have been developed in other fields that, with appropriate modification, could be applied to the biological sciences.

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