| Effective translational research requires automated analysis of large datasets collected by multiple researchers working at multiple locations. Reliable, machine interpretation of-—and reasoning with—-large datasets assembled at different times and places by different researchers requires standard representations of data. These representations are controlled, structured vocabularies also known as ontologies. By far, the most successful ontology is the Gene Ontology (GO), used by bioinformatics researchers to annotate genomics data. However, to address the phenotype side of translational research will require annotation of electronic medical record data and clinical research data with a clinical-phenotype ontology analogous to GO.... |
