Integrating biological pathways in disease ontologies.
Anatomy, clinical features, etiology, and morphology are the major organizing principles in existing disease ontologies. Assuming that biological pathways (including protein physical interactions, metabolic reactions, regulatory networks) will be in the near future key components in classifications of diseases, we have analyzed how information about pathways can be integrated into disease ontologies. We designed a disease ontology in OWL. SNOMED CT was used to provide the initial disease descriptions. In a second step, we integrated information from the KEGG PATHWAY and the GO annotation data-bases into the disease ontology. In the last step, we analyzed the classification of diseases. For example glioma of brain shares 30 pathways with other cancers, and 19 pathways with Alzheimer's disease. As our knowledge about biological pathways is constantly evolving, this approach can be used for integrating automatically this knowledge in existing ontologies. Thanks to the automatic classification associated with formal ontologies, this approach helps identify physio-pathological classes and taxonomic relations in diseases ontologies. It can therefore be used to create new partitions, focusing on pathways, in biomedical ontologies.
Chabalier
Julie
J
EA 3888 - IFR 140, Faculté de Médecine, Université de Rennes I, 35033 Rennes, France. julie.chabalier@univ-rennes1.fr
Mosser
Jean
J
Burgun
Anita
A
D000544:Alzheimer Disease / Q000145:classification / Q000378:metabolism; D001932:Brain Neoplasms / Q000145:classification / Q000378:metabolism; D004194:Disease / Q000145:classification*; D015870:Gene Expression; D005910:Glioma / Q000145:classification / Q000378:metabolism; D051188:Knowledge Bases; D053858:Metabolic Networks and Pathways; D011381:Programming Languages; D039061:Systematized Nomenclature of Medicine; D018875:Vocabulary, Controlled