Support vector machines for prediction of protein domain structural class

被引：39

作者：

Cai, YD

Liu, XJ

Xu, XB

Chou, KC

机构：

[1] Chinese Acad Sci, Shanghai Res Ctr Biotechnol, Shanghai 200233, Peoples R China

[2] Univ Edinburgh, Inst Cell Anim & Populat Biol, Edinburgh EH9 3JT, Midlothian, Scotland

[3] Univ Wales Coll Cardiff, Dept Comp Sci, Cardiff CF2 3XF, S Glam, Wales

[4] Pfizer, Upjohn Labs, Kalamazoo, MI 49001 USA

来源：

JOURNAL OF THEORETICAL BIOLOGY | 2003年 / 221卷 / 01期

关键词：

D O I：

10.1006/jtbi.2003.3179

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The support vector machines (SVMs) method was introduced for predicting the structural class of protein domains. The results obtained through the self-consistency test, jack-knife test, and independent dataset test have indicated that the current method and the elegant component-coupled algorithm developed by Chou and co-workers, if effectively complemented with each other, may become a powerful tool for predicting the structural class of protein domains. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：115 / 120

页数：6

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