doi:10.1093/bioinformatics/bti650BIOINFORMATICS ORIGINAL PAPER Sequence analysis TARGET: a new method for predicting protein subcellular localization in eukaryotes

Motivation: There is a scarcity of efficient computational methods for predictingprotein subcellular localization in eukaryotes.Currentlyavail-ablemethodsare inadequate forgenome-scalepredictionswith several limitations. Here, we present a new prediction method, pTARGET that canpredict proteins targeted toninedifferent subcellular locations in the eukaryotic animal species. Results:The nine subcellular locations predicted by pTARGET include cytoplasm, endoplasmic reticulum, extracellular/secretory, golgi, lyso-somes, 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 predic-tion 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 ofproteinsubcellular localizationssince, it doesnot relyon thepresence of signal or target peptides. Availability: A public web server based on the pTARGET method is accessible at th