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Automatic annotation of protein motif function with Gene Ontology terms

Authors:	Xinghua?Lu author-information" > author-information__contact u-icon-before" > mailto:lux@musc.edu" title=" lux@musc.edu" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,Chengxiang?Zhai,Vanathi?Gopalakrishnan,Bruce?G?Buchanan

Affiliation:	(1) Dept. of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon St. Suite 303, Charleston, SC 29425, USA;(2) Dept of Computer Science, University of Illinois at Urbana-Champaign, 1304 W. Springfield Avenue, Urbana, IL 61801, USA;(3) Center for Biomedical Informatics, University of Pittsburgh, 200 Lothrop Street, Suite 8084, Pittsburgh, PA 15213, USA

Abstract:	Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO) project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base.

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