title: pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  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.
authors.affiliation: Gen*NY*sis Center for Excellence in Cancer Genomics, State University of New York, One Discovery Drive, Rensselaer, NY 12144-3456, USA. cguda@albany.edu
authors.forename: Chittibabu
authors.initials: C
authors.lastname: Guda
authors.forename: Shankar
authors.initials: S
authors.lastname: Subramaniam
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D005057:Eukaryotic Cells / Q000378:metabolism*; D006801:Humans; D008969:Molecular Sequence Data; D020543:Proteome / Q000737:chemistry* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013329:Structure-Activity Relationship; D013347:Subcellular Fractions / Q000378:metabolism*
chemical_list: D020543:Proteome