Format

Send to

Choose Destination
Bioinformatics. 2005 May 15;21(10):2522-4. Epub 2005 Feb 4.

PSLpred: prediction of subcellular localization of bacterial proteins.

Author information

1
Institute of Microbial Technology, Sector 39A, Chandigarh, India.

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/

PMID:
15699023
DOI:
10.1093/bioinformatics/bti309
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center