title: Ontology-based annotation and query of tissue microarray data.
abstract: The Stanford Tissue Microarray Database (TMAD) is a repository of data amassed by a consortium of pathologists and biomedical researchers. The TMAD data are annotated with multiple free-text fields, specifying the pathological diagnoses for each tissue sample. These annotations are spread out over multiple text fields and are not structured according to any ontology, making it difficult to integrate this resource with other biological and clinical data. We developed methods to map these annotations to the NCI thesaurus and the SNOMED-CT ontologies. Using these two ontologies we can effectively represent about 80% of the annotations in a structured manner. This mapping offers the ability to perform ontology driven querying of the TMAD data. We also found that 40% of annotations can be mapped to terms from both ontologies, providing the potential to align the two ontologies based on experimental data. Our approach provides the basis for a data-driven ontology alignment by mapping annotations of experimental data.
authors.affiliation: Stanford Medical Informatics, Stanford University School of Medicine and the National Center for Biomedical Ontology, Stanford University, Stanford, CA 94305, USA. nigam@stanford.edu
authors.forename: Nigam H
authors.initials: NH
authors.lastname: Shah
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Rubin
authors.forename: Kaustubh S
authors.initials: KS
authors.lastname: Supekar
authors.forename: Mark A
authors.initials: MA
authors.lastname: Musen
mesh_terms: D006801:Humans; D007150:Immunohistochemistry; D046228:Microarray Analysis; D009316:National Institutes of Health (U.S.); D009369:Neoplasms / Q000145:classification* / Q000175:diagnosis; D039061:Systematized Nomenclature of Medicine; D014481:United States; D018875:Vocabulary, Controlled