@article{open190,
          volume = {21},
          number = {10},
           month = {May},
          author = {Manoj Bhasin and Aarti Garg and G.P.S. Raghava},
            note = {Copyright of this article belongs to OUP.
Supplementary information
http://www.imtech.res.in/raghava/pslpred/supl.html},
           title = {PSLpred: prediction of subcellular localization of bacterial proteins.},
       publisher = {Oxford University press},
            year = {2005},
         journal = {Bioinformatics (Oxford, England)},
           pages = {2522--4},
             url = {http://crdd.osdd.net/open/190/},
        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/}
}