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WoLF PSORT: protein localization predictor

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,...

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Autores principales: Horton, Paul, Park, Keun-Joon, Obayashi, Takeshi, Fujita, Naoya, Harada, Hajime, Adams-Collier, C.J., Nakai, Kenta
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933216/
https://www.ncbi.nlm.nih.gov/pubmed/17517783
http://dx.doi.org/10.1093/nar/gkm259
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author Horton, Paul
Park, Keun-Joon
Obayashi, Takeshi
Fujita, Naoya
Harada, Hajime
Adams-Collier, C.J.
Nakai, Kenta
author_facet Horton, Paul
Park, Keun-Joon
Obayashi, Takeshi
Fujita, Naoya
Harada, Hajime
Adams-Collier, C.J.
Nakai, Kenta
author_sort Horton, Paul
collection PubMed
description 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
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spelling pubmed-19332162007-07-31 WoLF PSORT: protein localization predictor Horton, Paul Park, Keun-Joon Obayashi, Takeshi Fujita, Naoya Harada, Hajime Adams-Collier, C.J. Nakai, Kenta Nucleic Acids Res Articles 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 Oxford University Press 2007-07 2007-05-21 /pmc/articles/PMC1933216/ /pubmed/17517783 http://dx.doi.org/10.1093/nar/gkm259 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Horton, Paul
Park, Keun-Joon
Obayashi, Takeshi
Fujita, Naoya
Harada, Hajime
Adams-Collier, C.J.
Nakai, Kenta
WoLF PSORT: protein localization predictor
title WoLF PSORT: protein localization predictor
title_full WoLF PSORT: protein localization predictor
title_fullStr WoLF PSORT: protein localization predictor
title_full_unstemmed WoLF PSORT: protein localization predictor
title_short WoLF PSORT: protein localization predictor
title_sort wolf psort: protein localization predictor
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933216/
https://www.ncbi.nlm.nih.gov/pubmed/17517783
http://dx.doi.org/10.1093/nar/gkm259
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