Three Ontologies to Define Phenotype Measurement Data - Shimoyama, Mary; Nigam, Rajni; McIntosh, Leslie S.; Nagarajan, Rakesh; Rice, Treva K.; Rao, D.C.; Dwinell, Melinda R. (Frontiers in Genetics, 2012)
There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol. To standardize the elements of phenotype measurement records, three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provide the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitate data integration from multiple human epidemiological studies into a centralized repository. An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.