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Nucleic Acids Research 2005 33(Database Issue):D147-D153; doi:10.1093/nar/gki120
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Nucleic Acids Research, 2005, Vol. 33, Database issue D147-D153
© 2005, the authors
Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved

PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization

Paul Lu*, Duane Szafron, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Brett Poulin, Roman Eisner, Danny Ngo and Nicholas Lamb

Department of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8

* To whom correspondence should be addressed. Tel: +1 780 492 7760; Fax: +1 780 492 1071; Email: paullu{at}cs.ualberta.ca

Received August 15, 2004; Revised and Accepted October 20, 2004

PA-GOSUB (Proteome Analyst: Gene Ontology Molecular Function and Subcellular Localization) is a publicly available, web-based, searchable and downloadable database that contains the sequences, predicted GO molecular functions and predicted subcellular localizations of more than 107 000 proteins from 10 model organisms (and growing), covering the major kingdoms and phyla for which annotated proteomes exist (http://www.cs.ualberta.ca/~bioinfo/PA/GOSUB). The PA-GOSUB database effectively expands the coverage of subcellular localization and GO function annotations by a significant factor (already over five for subcellular localization, compared with Swiss-Prot v42.7), and more model organisms are being added to PA-GOSUB as their sequenced proteomes become available. PA-GOSUB can be used in three main ways. First, a researcher can browse the pre-computed PA-GOSUB annotations on a per-organism and per-protein basis using annotation-based and text-based filters. Second, a user can perform BLAST searches against the PA-GOSUB database and use the annotations from the homologs as simple predictors for the new sequences. Third, the whole of PA-GOSUB can be downloaded in either FASTA or comma-separated values (CSV) formats.


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