Formal knowledge representations have the potential to facilitate significant computational assistance to biomedical researchers hoping to understand genome-scale data sets. However, ontology annotation of gene products and related enrichment approaches have yet barely begun to realize this potential. Nevertheless, solid ontological foundations are likely to be critical for successful knowledge-based analysis of genome-scale data. In this talk, I will describe some desiderata for formal representations of biological knowledge relevant to more complex forms of automated reasoning, some of my laboratory's efforts to create and use such representations, and a vision for the productive development of our field.
Lawrence Hunter is the Director of the University of Colorado's Computational Bioscience Program and a Professor of Pharmacology (School of Medicine) and Computer Science (Boulder). He received a Ph.D. in computer science from Yale University in 1989, and then joined the National Institutes of Health as a staff scientist, first at the National Library of Medicine and then at the National Cancer Institute, before coming to Colorado in 2000. Dr. Hunter is widely recognized as one of the founders of bioinformatics; he served as the first President of the International Society for Computational Biology (ISCB), and created several of the most important conferences in the field, including ISMB, PSB and VizBi . Dr. Hunter's research interests span a wide range of areas, from cognitive science to rational drug design. He has published more than 100 scientific papers, holds two patents and has been elected a fellow of both the ISCB and the American College of Medical Informatics. His primary focus recently has been the integration of natural language processing, knowledge representation, machine learning and advanced visualization techniques to address challenges in interpreting data generated by high throughput molecular biology.