Semantic integration of physiology phenotypes with an application to the cellular phenotype ontology

Robert Hoehndorf*, Midori A. Harris, Heinrich Herre, Gabriella Rustici, Georgios V. Gkoutos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Motivation: The systematic observation of phenotypes has become a crucial tool of functional genomics, and several large international projects are currently underway to identify and characterize the phenotypes that are associated with genotypes in several species. To integrate phenotype descriptions within and across species, phenotype ontologies have been developed. Applying ontologies to unify phenotype descriptions in the domain of physiology has been a particular challenge due to the high complexity of the underlying domain. Results: In this study, we present the outline of a theory and its implementation for an ontology of physiology-related phenotypes. We provide a formal description of process attributes and relate them to the attributes of their temporal parts and participants. We apply our theory to create the Cellular Phenotype Ontology (CPO). The CPO is an ontology of morphological and physiological phenotypic characteristics of cells, cell components and cellular processes. Its prime application is to provide terms and uniform definition patterns for the annotation of cellular phenotypes. The CPO can be used for the annotation of observed abnormalities in domains, such as systems microscopy, in which cellular abnormalities are observed and for which no phenotype ontology has been created.

Original languageEnglish (US)
Article numberbts250
Pages (from-to)1783-1789
Number of pages7
JournalBioinformatics
Volume28
Issue number13
DOIs
StatePublished - Jul 2012
Externally publishedYes

Bibliographical note

Funding Information:
Framework Programme (FP7/2007-2013) under grant agreement number 258068, EU-FP7-Systems Microscopy NoE. G.V.G. is supported by the National Institute of Health, grant number R01 HG004838-02.

Funding Information:
Funding: Funding for R.H. is provided by the European Commission’s 7th Framework Programme, RICORDO project, grant number 248502. M.A.H. is supported by Wellcome Trust, grant WT090548MA. H.H. is supported by the Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig. Funding for G.R. is provided by the European Union’s Seventh

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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