WoLF PSORT: protein localization predictor

Paul Horton, Kyungjoon Park, Takeshi Obayashi, Nobuko FUJITA, Hideaki Harada, C.J. Adams-Collier, Kenta Nakai

Nucleic Acids Research · 2007 · 4.2K citations · 13 references

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Concepts

TL;DR

WoLF PSORT is an extension of the PSORT II program for protein subcellular location prediction. WoLF PSORT transforms protein amino‑acid sequences into numerical localization features based on sorting signals, amino‑acid composition, and functional motifs, then applies a k‑nearest‑neighbor classifier and presents evidence via HTML tables and links to similar proteins, UniProt, and Gene Ontology. The integrated evidence allows users to assess the support for each prediction and understand the basis of the localization calls. WoLF PSORT is available at wolfpsort.org.

Abstract

WoLF PSORT is 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. For convenience, sequence alignments of the query to similar proteins and links to UniProt and Gene Ontology are provided. Taken together, this information allows a user to understand the evidence (or lack thereof) behind the predictions made for particular proteins. WoLF PSORT is available at wolfpsort.org

References

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