Abstract
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 meta-search mechanism that maps queries to the appropriate gene prediction tools and obtains the overall prediction outcome.
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Koutkias, V., Malousi, A., Maglaveras, N. (2004). Performing Ontology-Driven Gene Prediction Queries in a Multi-agent Environment. In: Barreiro, J.M., Martín-Sánchez, F., Maojo, V., Sanz, F. (eds) Biological and Medical Data Analysis. ISBMDA 2004. Lecture Notes in Computer Science, vol 3337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30547-7_38
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DOI: https://doi.org/10.1007/978-3-540-30547-7_38
Publisher Name: Springer, Berlin, Heidelberg
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