Performing ontology-driven gene prediction queries in a multi-agent environment

Gene prediction is one of the most challenging problems in Computational Biology. Motivated by the strengths and limitations of the currently available Web-based gene predictors, a Knowledge Base was constructed that conceptualizes the functionalities and requirements of each tool, following an ontology-based approach. According to this classification, a Multi-Agent System was developed that exploits the potential of the underlying semantic representation, in order to provide transparent and efficient query services based on user-implied criteria. Given a query, a broker agent searches for matches in the Knowledge Base, and coordinates correspondingly the submission/retrieval tasks via a set of wrapper agents. This approach is intended to enable efficient query processing in a resource-sharing environment by embodying a metasearch mechanism that maps queries to the appropriate gene prediction tools and obtains the overall prediction outcome.