报告题目：Knowledge-based Interpretation of Genome Scale Data/基于知识的基因组数据分析
报告人： Larry Hunter 教授
报告时间：2016年10月17日（周一）16:00
报告地点：逸夫楼C座314会议室
摘要：
The interpretation of genomescale data sets, such as those from sequencing, proteomics, expressionprofiling, micro-RNA screens and other molecular assays, is a central challengefor contemporary biological research. How do the many significant genes, gene products or variants that areidentified by these assays relate to the phenotype under study? Answering this question requires extensiveknowledge, including knowledge about the structure, activity, localization,metabolism, regulation and biological processes of these molecules. Formalknowledge representation and reasoning has long been a topic of study inArtificial Intelligence, yet these results are not fully exploited bybioinformatics software. In this talk, Iwill review the computational techniques, standards and tools in formalknowledge representation and reasoning, how these can be used to interpretexperimental molecular findings in light of existing knowledge, and describerecent advances in these areas from my laboratory.
报告人简介：
Prof. Lawrence Hunter is theDirector of the University of Colorado's Computational Bioscience Program and aProfessor of Pharmacology (School of Medicine) and Computer Science(Boulder). He received a Ph.D. in computerscience from Yale University in 1989, and then joined the National Institutesof Health as a staff scientist, first at the National Library of Medicine andthen at the National Cancer Institute, before coming to Colorado in 2000. Dr. Hunter is widely recognized as one of thefounders of bioinformatics; he served as the first President of theInternational Society for Computational Biology (ISCB), and created several ofthe most important conferences in the field, including ISMB, PSB and VizBi .Dr. Hunter's research interests span a wide range of areas, from cognitivescience to rational drug design. He has published more than 100 scientificpapers, holds two patents and has been elected a fellow of both the ISCB andthe American College of Medical Informatics. His primary focus recently hasbeen the integration of natural language processing, knowledge representation,machine learning and advanced visualization techniques to address challenges ininterpreting data generated by high throughput molecular biology.