A Preliminary Report on Answering Complex Queries
     related to Drug Discovery using Answer Set Programming

                     Olivier Bodenreider
                 National Library of Medicine
              National Institutes of Health, USA

                       Zeynep H. Coban 
                 Department of Biostatistics
             Harvard School of Public Health, USA

                       Mahir C. Doganay
          Department of Mathematics and Computing Science
             University of Groningen, The Netherlands

                          Esra Erdem 
          Faculty of Engineering and Natural Sciences
                   Sabanci University, Turkey

                         Hilal Kosucu
                Department of Computer Science
                 University of Toronto, Canada


We introduce a new method for integrating relevant parts of knowledge
extracted from biomedical ontologies and answering complex queries 
related to drug safety and discovery, using Semantic Web technologies 
and answer set programming. The applicability of this method is illustrated 
in detail on some parts of existing biomedical ontologies. Its effectiveness 
is demonstrated by computing an answer to a real-world biomedical query that 
requires the integration of NCBI Entrez Gene and the Gene Ontology.