学术报告
题目：Big Data Analytics in Computational Chemical Biology
报告人：Jun (Luke) Huan, Ph.D.
Associate Professor
Department of Electrical Engineering & Computer Science
Director, the Bioinformatics and Computational Life Sciences Laboratory

University of Kansas
时间：2013年6月13日（周四）下午14:00-15:30 PM
地点：生命学院610室
报告摘要：
The NIH Molecular Libraries Probe Production Centers Network (MLPCN) aims to remediate key deficiencies in drug discovery and chemical biology, through the pursuit of therapeutically feasible but unprofitable drug targets, undruggable genes of biochemical interest, and the development of chemically diverse, biologically relevant screening sets. In this talk we will present a few informatics approaches to integrate and model big data in chemical biology research, based on graphs. We will evaluate the novelty of MLPCN targets, their propensity for undergoing modulations of biochemical or therapeutic relevance, the degree of chemical diversity inherent in the MLPCN screening set, and biogenic bias of the set. Several advanced machine learning techniques, including ensemble learning and multi-task learning, for large-scale protein-ligand interaction prediction will be presented.
报告人简介：
Dr. Jun (Luke) Huan is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. He directs the Bioinformatics and Computational Life Sciences Laboratory at KU Information and Telecommunication Technology Center (ITTC) and the Cheminformatics core at KU Specialized Chemistry Center. Dr. Huan holds courtesy appointments at the KU Bioinformatics Center, the KU Bioengineering Program, and a visiting professorship from GlaxoSmithKline plc.. Dr. Huan received his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill. Before joining KU in 2006, he worked at Argonne National Laboratory and GlaxoSmithKline plc.. Dr. Huan was a recipient of the National Science Foundation Faculty Early Career Development Award in 2009. He has published more than 80 peer-reviewed papers in leading conferences and journals, including Nature Biotechnology and ACS Journal of Chemical Information and Modeling. His group also won the Best Student Paper Award at IEEE International Conference on Data Mining in 2011 and the Best Paper Award (runner-up) at ACM International Conference on Information and Knowledge Management in 2009. Dr. Huan served on the program committees of prestigious international conferences including ACM SIGKDD, ICML, ACM CIKM, IEEE ICDM, and IEEE BigData.
欢迎各位老师和同学积极参加！