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. 2005 May 15;21(10):2522-4.
doi: 10.1093/bioinformatics/bti309. Epub 2005 Feb 4.

PSLpred: prediction of subcellular localization of bacterial proteins

Manoj Bhasin  1 , Aarti Garg, G P S Raghava
Affiliations

PSLpred: prediction of subcellular localization of bacterial proteins

Manoj Bhasin et al. Bioinformatics. .

Abstract

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/

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