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The representation of protein complexes in the Protein Ontology (PRO)

  • Carol J. Bult
  • , Harold J. Drabkin
  • , Alexei Evsikov
  • , Darren Natale
  • , Cecilia Arighi
  • , Natalia Roberts
  • , Alan Ruttenberg
  • , Peter D'Eustachio
  • , Barry Smith
  • , Judith A. Blake
  • , Cathy Wu
  • Jackson Laboratory
  • Georgetown University
  • University of Delaware
  • SUNY Buffalo
  • New York University

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Background: Representing species-specific proteins and protein complexes in ontologies that are both human- and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because proteins are often functional only as members of stable protein complexes, the PRO Consortium, in collaboration with existing protein and pathway databases, has launched a new initiative to implement logical and consistent representation of protein complexes.Description: We describe here how the PRO Consortium is meeting the challenge of representing species-specific protein complexes, how protein complex representation in PRO supports annotation of protein complexes and comparative biology, and how PRO is being integrated into existing community bioinformatics resources. The PRO resource is accessible at http://pir.georgetown.edu/pro/.Conclusion: PRO is a unique database resource for species-specific protein complexes. PRO facilitates robust annotation of variations in composition and function contexts for protein complexes within and between species.

Original languageEnglish
Article number371
JournalBMC Bioinformatics
Volume12
DOIs
StatePublished - Sep 19 2011

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