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This article is part of the supplement: First International Workshop on Text Mining in Bioinformatics (TMBio) 2006

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Framework for a Protein Ontology

Darren A Natale1*, Cecilia N Arighi1, Winona C Barker1, Judith Blake2, Ti-Cheng Chang1, Zhangzhi Hu1, Hongfang Liu3, Barry Smith4 and Cathy H Wu1

Author Affiliations

1 Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St., NW, Washington, DC, 20007, USA

2 The Jackson Laboratory, 600 Main St., Bar Harbor, ME, 04609, USA

3 Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Room 176, Building D, Washington, DC, 20057, USA

4 Department of Philosophy, State University of New York at Buffalo, Park Hall, Buffalo, NY, 12460, USA

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BMC Bioinformatics 2007, 8(Suppl 9):S1  doi:10.1186/1471-2105-8-S9-S1

Published: 27 November 2007

Abstract

Biomedical ontologies are emerging as critical tools in genomic and proteomic research, where complex data in disparate resources need to be integrated. A number of ontologies describe properties that can be attributed to proteins. For example, protein functions are described by the Gene Ontology (GO) and human diseases by SNOMED CT or ICD10. There is, however, a gap in the current set of ontologies – one that describes the protein entities themselves and their relationships. We have designed the

    PR
otein
    O
ntology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modifications). PRO will allow the specification of relationships between PRO, GO and other ontologies in the OBO Foundry. Here we describe the initial development of PRO, illustrated using human and mouse proteins involved in the transforming growth factor-beta and bone morphogenetic protein signaling pathways.