Integrating phenotype ontologies with PhenomeNET.

Journal: Journal of biomedical semantics
Published Date:

Abstract

BACKGROUND: Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast.

Authors

  • Miguel Ángel Rodríguez-García
    Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia.
  • 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.
  • Paul N Schofield
    Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK. pns12@cam.ac.uk.
  • 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.