Aber-OWL: a framework for ontology-based data access in biology.

Journal: BMC bioinformatics
Published Date: Jan 28, 2015

Abstract

BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning.

Authors

  • Robert Hoehndorf
    Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia. robert.hoehndorf@kaust.edu.sa.
  • Luke Slater
    Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia. luke.slater@kaust.edu.sa.
  • Paul N Schofield
    Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK. pns12@cam.ac.uk.
  • Georgios V Gkoutos
    Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom; Institute of Translational Medicine, University of Birmingham, Birmingham, United Kingdom; NIHR Surgical Reconstruction and Microbiology Research Centre, University Hospital Birmingham, Birmingham, United Kingdom; MRC Health Data Research UK (HDR UK), London, United Kingdom; NIHR Experimental Cancer Medicine Centre, Birmingham, United Kingdom; NIHR Biomedical Research Centre, University Hospital Birmingham, Birmingham, United Kingdom.

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