Enriching and Answering Proteomic Queries Using Semantic Knowledges

Querying and sharing Web proteomics is a challenging topic in Pharmaceutical Drug Discovery and Computational Biology. Given that, several data sources can be used to answer the same sub-goals in the Global query, it is obvious that we can have many different candidates rewritings. The user-query is formulated using Concepts and Properties related to Proteomics research (Domain Ontology). Semantic mappings describe the contents of underlying sources in order to reflect their query capabilities. In this work, we propose to enrich the user query using WordNet and we give a. characterization of query rewriting problem using semantic mappings as an associated hypergraph. Hence, the generation of candidates rewrititngs can be formulated as the discovery of minimals Transversals associated with this hypergraph. We exploit and adapt algorithms available in Hypergraph Theory to find all candidates rewritings from a query answering problem. In this context, some relevant criteria could help to determine optimal and qualitative rewritings, according to user preferences, and sources technical performances.