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J Theor Biol. 2010 May 21;264(2):326-33. doi: 10.1016/j.jtbi.2010.01.018. Epub 2010 Jan 20.

Gneg-mPLoc: a top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins.

Author information

1
Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai 200240, China. hbshen@sjtu.edu.cn

Abstract

By incorporating the information of gene ontology, functional domain, and sequential evolution, a new predictor called Gneg-mPLoc was developed. It can be used to identify Gram-negative bacterial proteins among the following eight locations: (1) cytoplasm, (2) extracellular, (3) fimbrium, (4) flagellum, (5) inner membrane, (6) nucleoid, (7) outer membrane, and (8) periplasm. It can also be used to deal with the case when a query protein may simultaneously exist in more than one location. Compared with the original predictor called Gneg-PLoc, the new predictor is much more powerful and flexible. For a newly constructed stringent benchmark dataset in which none of proteins included has >or=25% pairwise sequence identity to any other in a same subset (location), the overall jackknife success rate achieved by Gneg-mPLoc was 85.5%, which was more than 14% higher than the corresponding rate by the Gneg-PLoc. As a user friendly web-server, Gneg-mPLoc is freely accessible at http://www.csbio.sjtu.edu.cn/bioinf/Gneg-multi/.

PMID:
20093124
DOI:
10.1016/j.jtbi.2010.01.018
[Indexed for MEDLINE]

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