Predicting Gram-positive bacterial protein subcellular localization based on localization motifs

被引：15

作者：

Hu, Yinxia ^{[1
]}

Li, Tonghua ^{[1
]}

Sun, Jiangming ^{[1
]}

Tang, Shengnan ^{[1
]}

Xiong, Wenwei ^{[1
]}

Li, Dapeng ^{[1
]}

Chen, Guanyan ^{[1
]}

Cong, Peisheng ^{[1
]}

机构：

[1] Tongji Univ, Dept Chem, Shanghai 200092, Peoples R China

来源：

JOURNAL OF THEORETICAL BIOLOGY | 2012年 / 308卷

基金：

中国国家自然科学基金;

关键词：

Subcellular location prediction; Motif finding; Position-specific frequencies encoding; Support vector machine (SVM); SUPPORT VECTOR MACHINES; NEGATIVE BACTERIA; SORTING SIGNALS; UNITED-STATES; INFECTIONS; EPIDEMIOLOGY; CLASSIFIER; LOCATION; SEQUENCE; CANCER;

D O I：

10.1016/j.jtbi.2012.05.031

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The subcellular localization of proteins is closely related to their functions. In this work, we propose a novel approach based on localization motifs to improve the accuracy of predicting subcellular localization of Gram-positive bacterial proteins. Our approach performed well on a five-fold cross validation with an overall success rate of 89.5%. Besides, the overall success rate of an independent testing dataset was 97.7%. Moreover, our approach was tested using a new experimentally-determined set of Gram-positive bacteria proteins and achieved an overall success rate of 96.3%. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：135 / 140

页数：6

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