Improving the classification of cardinality phenotypes using collections.

Journal: Journal of biomedical semantics
Published Date:

Abstract

MOTIVATION: Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is collected in a clinical context to characterize disease, and is also collected in model organisms and stored in model organism databases where they are used to understand gene functions. Phenotype data is also used in computational data analysis and machine learning methods to provide novel insights into disease mechanisms and support personalized diagnosis of disease. For mammalian organisms and in a clinical context, ontologies such as the Human Phenotype Ontology and the Mammalian Phenotype Ontology are widely used to formally and precisely describe phenotypes. We specifically analyze axioms pertaining to phenotypes of collections of entities within a body, and we find that some of the axioms in phenotype ontologies lead to inferences that may not accurately reflect the underlying biological phenomena.

Authors

  • Sarah M Alghamdi
    King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, 23955-6900, Saudi Arabia.
  • 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.