Contribution to OBO ontologies and application of structured vocabularies for data integration and biological reasoning

As the amount of accessible biological data is growing exponentially, it is becoming harder and harder to extract the biological knowledge contained in thousands of databases. Biomedical scientists collect facts, often recording them in natural language, and then use their knowledge to make inferences about as yet uncharacterised observations. Therefore, to make the best use of biological databases and the knowledge they contain, different kinds of information from different sources must be integrated in ways that make sense to the scientific community. The Gene Ontology (GO) and other biomedical ontologies (OBO) are fundamental components in data integration and annotation. This PhD project focuses on the improvement of some already existing resources, and the development of new methods that facilitate data integration and extraction, for genes, drugs and diseases, and their inter-relationships. The work consists of contributions to biological ontologies and definitions of cross-links between different semantic fields represented in several distinct databases. Significant changes in GO content and structure have been provided, resulting in the addition of hundreds of terms useful in the representation of muscle and nervous system biology. In addition, a resource has been developed to find preliminary correlations between genes, drugs and diseases. This resource integrates information from several very up-to-date sources, most of which are manually curated; and from a human disease ontology, the "Disease Ontology". The revised ontologies will facilitate the interpretation of high-throughout experiments in the area of muscle biology and neurobiology, and more importantly, in the fields of neuromuscular and nervous system diseases. Furthermore, the developed ontology-based system will provide interoperability support for physicians and medical researchers in the interpretation of data from studies on human diseases.