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PSLpred: prediction of subcellular localization of bacterial proteins.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title PSLpred: prediction of subcellular localization of bacterial proteins.
 
Creator Bhasin, Manoj
Garg, Aarti
Raghava, G.P.S.
 
Subject QR Microbiology
 
Description SUMMARY: We developed a web server PSLpred for predicting subcellular localization of gram-negative bacterial proteins with an overall accuracy of 91.2%. PSLpred is a hybrid approach-based method that integrates PSI-BLAST and three SVM modules based on compositions of residues, dipeptides and physico-chemical properties. The prediction accuracies of 90.7, 86.8, 90.3, 95.2 and 90.6% were attained for cytoplasmic, extracellular, inner-membrane, outer-membrane and periplasmic proteins, respectively. Furthermore, PSLpred was able to predict approximately 74% of sequences with an average prediction accuracy of 98% at RI = 5. AVAILABILITY: PSLpred is available at http://www.imtech.res.in/raghava/pslpred/
 
Publisher Oxford University press
 
Date 2005-05-15
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/190/1/raghava2005.1.pdf
Bhasin, Manoj and Garg, Aarti and Raghava, G.P.S. (2005) PSLpred: prediction of subcellular localization of bacterial proteins. Bioinformatics (Oxford, England), 21 (10). pp. 2522-4. ISSN 1367-4803
 
Relation http://bioinformatics.oxfordjournals.org/content/21/10/2522.full.pdf+html
http://crdd.osdd.net/open/190/