Automated Integration of Biomedical Knowledge

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Today, ontologies are critical instruments for biomedical investigators, especially in those areas, such as cancer research, that require the command of a vast amount of information and a systemic approach to the design and interpretation of experiments. In fact, ontologies are proliferating in all areas of biomedical research, offering both challenges and opportunities. One of the principal challenges of this field stems from the fact that ontologies are developed in isolation, rendering it impossible to move, for instance, from genes to organisms, to diseases, to drugs. The National Center for Biomedical Ontology (NCBO) represents a fundamental endeavor in the collection, coordination and distribution of biomedical ontologies and offers an unparalleled opportunity to combine these biomedical ontologies into a single search space where genetic, anatomic, molecular and pharmacological information can be seamlessly explored and exploited as a holistic representation of biomedical knowledge. Unfortunately, ontology integration using standard means of manual curation is a labor intensive task, unable to scale up and keep up with the current growth rate of biomedical ontologies. We have developed a systematic framework for automated ontology engineering based on information theory, and we have successfully applied it to the analysis and engineering of Gene Ontology (GO), the development gene and protein databases, and the identification of peripheral biomarkers of disease progression and drug response. This project brings together a unique group of competences, ranging from ontology engineering, statistical signal processing, bioinformatics, cancer research, and clinical pharmacogenomics, to develop a principled method, grounded on the mathematics of information theory, to automatically combine and integrate biomedical ontologies and implement it as part of the NCBO architecture