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Bioinformatics. 2005 Nov 1;21(21):3963-9. Epub 2005 Sep 6.

pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes.

Author information

  • 1Gen*NY*sis Center for Excellence in Cancer Genomics, State University of New York, One Discovery Drive, Rensselaer, NY 12144-3456, USA. cguda@albany.edu

Erratum in

  • Bioinformatics. 2005 Dec 15;21(24):4434.

Abstract

MOTIVATION:

There is a scarcity of efficient computational methods for predicting protein subcellular localization in eukaryotes. Currently available methods are inadequate for genome-scale predictions with several limitations. Here, we present a new prediction method, pTARGET that can predict proteins targeted to nine different subcellular locations in the eukaryotic animal species.

RESULTS:

The nine subcellular locations predicted by pTARGET include cytoplasm, endoplasmic reticulum, extracellular/secretory, golgi, lysosomes, mitochondria, nucleus, plasma membrane and peroxisomes. Predictions are based on the location-specific protein functional domains and the amino acid compositional differences across different subcellular locations. Overall, this method can predict 68-87% of the true positives at accuracy rates of 96-99%. Comparison of the prediction performance against PSORT showed that pTARGET prediction rates are higher by 11-60% in 6 of the 8 locations tested. Besides, the pTARGET method is robust enough for genome-scale prediction of protein subcellular localizations since, it does not rely on the presence of signal or target peptides.

AVAILABILITY:

A public web server based on the pTARGET method is accessible at the URL http://bioinformatics.albany.edu/~ptarget. Datasets used for developing pTARGET can be downloaded from this web server. Source code will be available on request from the corresponding author.

PMID:
16144808
[PubMed - indexed for MEDLINE]
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