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

被引：3

作者：

Dandekar, T

Du, FL

Schirmer, RH

Schmidt, S

机构：

[1] European Mol Biol Lab, D-69012 Heidelberg, Germany

[2] Heidelberg Univ, Abt Parasitol, D-69120 Heidelberg, Germany

[3] Univ Freiburg, Inst Mol Med, D-79106 Freiburg, Germany

[4] Biochem Ctr BZH, D-69120 Heidelberg, Germany

来源：

COMPUTERS & CHEMISTRY | 2001年 / 26卷 / 01期

关键词：

genome analysis; structure prediction; Mycobacterium tuberculosis; drug design; sequence comparison;

D O I：

10.1016/S0097-8485(01)00095-X

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

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. (C) 2001 Elsevier Science Ltd. All rights reserved.

引用

页码：15 / 21

页数：7

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