Prediction of protein secondary structure content using support vector machine

被引：19

作者：

Chen, Chao ^{[1
]}

Tian, Yuanxin ^{[1
]}

Zou, Xiaoyong ^{[1
]}

Cai, Peixiang ^{[1
]}

Mo, Jinyuan ^{[1
]}

机构：

[1] Sun Yat Sen Univ, Sch Chem & Chem Engn, Guangzhou 510275, Peoples R China

来源：

TALANTA | 2007年 / 71卷 / 05期

基金：

中国国家自然科学基金;

关键词：

support vector machine; protein secondary structure content; pair-coupled amino acid composition;

D O I：

10.1016/j.talanta.2006.09.015

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

In this paper, the support vector machine was trained to grasp the relationship between the pair-coupled amino acid composition and the content of protein secondary structural elements, including alpha-helix, 3(10)-helix, pi-helix, beta-strand, beta-bridge, turn, bend and the rest random coil. Self-consistency and cross validation tests were made to assess the performance of our method. Results superior to or competitive with the popular theoretical and experimental methods have been obtained. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：2069 / 2073

页数：5

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