Cross-product extensions of the Gene Ontology

  • Authors:

  • Christopher J. Mungall;Michael Bada;Tanya Z. Berardini;Jennifer Deegan;Amelia Ireland;Midori A. Harris;David P. Hill;Jane Lomax

  • Affiliations:

  • Lawrence Berkeley National Laboratory, Mail Stop 64R0121, Berkeley, CA 94720, USA;University of Colorado Denver, Department of Pharmacology, Aurora, CO 80206, USA;Carnegie Institute for Science, 260 Panama Street, Stanford, CA 94555, USA;European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK;Lawrence Berkeley National Laboratory, Mail Stop 64R0121, Berkeley, CA 94720, USA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK;European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK;The Jackson Laboratory, Bar Harbor, ME, USA;European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2011

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Abstract

The Gene Ontology (GO) consists of nearly 30,000 classes for describing the activities and locations of gene products. Manual maintenance of ontology of this size is a considerable effort, and errors and inconsistencies inevitably arise. Reasoners can be used to assist with ontology development, automatically placing classes in a subsumption hierarchy based on their properties. However, the historic lack of computable definitions within the GO has prevented the user of these tools. In this paper, we present preliminary results of an ongoing effort to normalize the GO by explicitly stating the definitions of compositional classes in a form that can be used by reasoners. These definitions are partitioned into mutually exclusive cross-product sets, many of which reference other OBO Foundry candidate ontologies for chemical entities, proteins, biological qualities and anatomical entities. Using these logical definitions we are gradually beginning to automate many aspects of ontology development, detecting errors and filling in missing relationships. These definitions also enhance the GO by weaving it into the fabric of a wider collection of interoperating ontologies, increasing opportunities for data integration and enhancing genomic analyses.