An extension of the PSORT II program for protein subcellular location prediction. WoLF PSORT converts protein amino acid sequences into numerical localization features; based on sorting signals, amino acid composition and functional motifs such as DNA-binding motifs. After conversion, a simple k-nearest neighbor classifier is used for prediction. Using html, the evidence for each prediction is shown in two ways: (i) a list of proteins of known localization with the most similar localization features to the query, and (ii) tables with detailed information about individual localization features. WoLF PSORT not only provides subcellular localization prediction with competitive accuracy, but also provides detailed information relevant to protein localization to help users to form their own hypotheses.
Computational Biology Research Center, AIST, Tokyo, Japan; Center for Genome Science, National Institute of Health, Korea Center for Disease Control & Prevention, Nokbeon-Dong, Eunpyung-Gu, Seoul, Korea; Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan; Collier Technologies, Everett, WA, USA