A New Method for Remote Protein Classification

被引：0

作者：

Li, YuGang ^{[1
]}

Liu, ZhiYong ^{[2
]}

Zhang, Fa ^{[2
]}

Qiu, ZhenGe ^{[2
]}

机构：

[1] Beijing Inst Technol, Sch Comp Sci & Technol, Beijing Key Lab Intelligence Informat Technol, Beijing 100081, Peoples R China

[2] Chinese Acad Sci, Comp Technol Inst, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4 | 2009年

基金：

国家高技术研究发展计划(863计划); 中国国家自然科学基金;

关键词：

Bioinformatics; LS_StaticEField; SVM; SCOP; HIDDEN MARKOV-MODELS; SEQUENCE; SEARCH; DATABASE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Protein classification is an important research topic in Bioinformatics. The Support Vector Machine (SVM) based methods, e.g. the SVM-PSV algorithm, are among the most successful ones. Based on our current work, this paper presents an alternative algorithm, the LS_StaticEField algorithm, for protein classification. The LS_StaticEField algorithm is more efficient to compute than SVM based ones and provides satisfying accuracy performance when compared with the SVM-PSV method in the experiments of homology detection based on the SCOP database.

引用

页码：1545 / +

页数：3

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