A Semantic Web Approach to Integrate Phenotype Descriptions and Clinical Data

Integrating phenotype descriptions from text-rich research resources, such as OMIM, and data from experimental and clinical practice is one of the current challenges to promote translational research. Exploring new technologies to uniformly represent biomedical information is needed to support integration of information drawn from disparate sources. Positive progress to integrate data requires to propose solutions supporting fully semantic translations. The Semantic Web is a promising technology, so international efforts, such as the OBO Foundry, are developing ontologies to support annotation and integration of scientific data. In this paper, we show an approach to get concordances between phenotype descriptions and clinical data, supported by knowledge adapters based on description logic and semantic web rules. This integration provides a valuable resource for researchers in order to infer new data for statistical analysis.

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