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Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search.
 
Creator Garg, Aarti
Bhasin, Manoj
Raghava, G.P.S.
 
Subject QD Chemistry
 
Description Here we report a systematic approach for predicting subcellular localization (cytoplasm, mitochondrial, nuclear, and plasma membrane) of human proteins. First, support vector machine (SVM)-based modules for predicting subcellular localization using traditional amino acid and dipeptide (i + 1) composition achieved overall accuracy of 76.6 and 77.8%, respectively. PSI-BLAST, when carried out using a similarity-based search against a nonredundant data base of experimentally annotated proteins, yielded 73.3% accuracy. To gain further insight, a hybrid module (hybrid1) was developed based on amino acid composition, dipeptide composition, and similarity information and attained better accuracy of 84.9%. In addition, SVM modules based on a different higher order dipeptide i.e. i + 2, i + 3, and i + 4 were also constructed for the prediction of subcellular localization of human proteins, and overall accuracy of 79.7, 77.5, and 77.1% was accomplished, respectively. Furthermore, another SVM module hybrid2 was developed using traditional dipeptide (i + 1) and higher order dipeptide (i + 2, i + 3, and i + 4) compositions, which gave an overall accuracy of 81.3%. We also developed SVM module hybrid3 based on amino acid composition, traditional and higher order dipeptide compositions, and PSI-BLAST output and achieved an overall accuracy of 84.4%. A Web server HSLPred (www.imtech.res.in/raghava/hslpred/ or bioinformatics.uams.edu/raghava/hslpred/) has been designed to predict subcellular localization of human proteins using the above approaches.
 
Publisher ASBMB
 
Date 2005-04-15
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/193/1/raghava2005.pdf
Garg, Aarti and Bhasin, Manoj and Raghava, G.P.S. (2005) Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search. The Journal of biological chemistry, 280 (15). pp. 14427-32. ISSN 0021-9258
 
Relation http://www.jbc.org/content/280/15/14427.long
http://crdd.osdd.net/open/193/