title: Using an integrated ontology and information model for querying and reasoning about phenotypes: The case of autism.
abstract: The Open Biomedical Ontologies (OBO) Foundry is a coordinated community-wide effort to develop ontologies that support the annotation and integration of scientific data. In work supported by the National Database of Autism Research (NDAR), we are developing an ontology of autism that extends the ontologies available in the OBO Foundry. We undertook a systematic literature review to identify domain terms and relationships relevant to autism phenotypes. To enable user queries and inferences about such phenotypes using data in the NDAR repository, we augmented the domain ontology with an information model. In this paper, we show how our approach, using a combination of description logic and rule-based reasoning, enables high-level phenotypic abstractions to be inferred from subject-specific data. Our integrated domain ontologyinformation model approach allows scientific data repositories to be augmented with rule-based abstractions that facilitate the ability of researchers to undertake data analysis.
authors.affiliation: Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
authors.forename: Samson W
authors.initials: SW
authors.lastname: Tu
authors.forename: Samson
authors.initials: S
authors.lastname: Tu
authors.forename: Lakshika
authors.initials: L
authors.lastname: Tennakoon
authors.forename: Martin
authors.initials: M
authors.lastname: O'Connor
authors.forename: Martin
authors.initials: M
authors.lastname: Connor
authors.forename: Ravi
authors.initials: R
authors.lastname: Shankar
authors.forename: Amar
authors.initials: A
authors.lastname: Das
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001321:Autistic Disorder; D003198:Computer Simulation; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D010641:Phenotype; D012107:Research Design; D013358:Subject Headings; D018511:Systems Integration; D014481:United States