Medical target prediction from genome sequence: combining different sequence analysis algorithms with expert knowledge and input from artificial intelligence approaches.

T Dandekar; F Du; R H Schirmer; S Schmidt

doi:10.1016/s0097-8485(01)00095-x

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Medical target prediction from genome sequence: combining different sequence analysis algorithms with expert knowledge and input from artificial intelligence approaches.

T Dandekar·F Du·R H Schirmer·S Schmidt

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Abstract

By exploiting the rapid increase in available sequence data, the definition of medically relevant protein targets has been improved by a combination of: (i) differential genome analysis (target list): and (ii) analysis of individual proteins (target analysis). Fast sequence comparisons, data mining, and genetic algorithms further promote these procedures. Mycobacterium tuberculosis proteins were chosen as applied examples.

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Algorithms Artificial Intelligence Bacterial Proteins Expert Systems Genomics Models, Molecular Mycobacterium Predictive Value of Tests Protein Structure, Secondary Journal Article Research Support, Non-U.S. Gov't

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T Dandekar, F Du, R H Schirmer, S Schmidt. 2001. Medical target prediction from genome sequence: combining different sequence analysis algorithms with expert knowledge and input from artificial intelligence approaches.. https://doi.org/10.1016/s0097-8485(01)00095-x

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