Title:	Charting Chemical Space with Computers: Challenges and Opportunities for AI and Machine Learning
Date:	October 10, 2005 (Monday)
Time:	2:30 p.m. - 3:30 p.m.
Venue:	ICS L1, Institute of Chinese Studies, The Chinese University of Hong Kong, Shatin, N.T.
Speaker:	Professor Pierre Baldi School of Information and Computer Sciences Department of Biological Chemistry Director Institute for Genomics and Bioinformatics University of California, Irvine USA

ABSTRACT:

Small molecules with at most a few dozen atoms play a fundamental role in organic chemistry and biology. They can be used as combinatorial building blocks for chemical synthesis, as molecular probes for perturbing and analyzing biological systems, and for the screening/design/discovery of new drugs. As datasets of small molecules become increasingly available, it becomes important to develop computational methods to store, search, classify, and analyze small molecules and in particular for the prediction of their physical, chemical, and biological properties.

We will describe databases and machine learning methods, in particular kernel methods, for chemical molecules represented by 1D strings, 2D graphs of bonds, and 3D structures. We will demonstrate state-of-the-art results for the prediction of physical, chemical, and biological properties of small molecules and the discovery of new reactions and compounds. More broadly, we will discuss some of the challenges and opportunities for computer science, AI, and machine learning in chemistry.

BIOGRAPHY:

Pierre Baldi is a Professor in the School of Information and Computer Sciences and the Department of Biological Chemistry at the University of California, Irvine and the Director of the Institute for Genomics and Bioinformatics. Born and raised in Europe, he received his PhD from the California Institute of Technology in 1986. He has held postdoctoral, faculty, and member of the technical staff positions at UCSD and Caltech, in the Division of Biology and the Jet Propulsion Laboratory. He was CEO of a startup company for a few years and joined UCI in 1999. He is the recipient of a 1993 Lew Allen Award at JPL and a Laurel Wilkening Faculty Innovation Award at UCI. Dr. Baldi's has published four books: Modeling the Internet and the We--Probabilistic Methods and Algorithms, Wiley, (2003); DNA Microarrays and Gene Regulation--From Experiments to Data Analysis and Modeling, Cambridge University Press, (2002); The Shattered Self--The End of Evolution, MIT Press, (2001); Bioinformatics: the Machine Learning Approach, MIT Press, Second Edition (2001); and over 150 scientific articles. His research focuses in various areas at the intersection of computational and life sciences, in particular the application of AI/statistical/machine learning methods to problems in bio and chemical informatics. The work of his group has resulted in several databases, software, and web servers that are widely used (www.igb.uci.edu/servers/servers.html). His main contributions include the development of Hidden Markov Models (HMMPro) for sequence analysis, recursive neural networks for de novo protein structure prediction (SCRATCH), Bayesian statistical methods for DNA microarray analysis (Cyber-T), informatics infrastructure for systems biology (SIGMOID) and, more recently, databases and tools in chemical informatics (ChemDB) for the prediction of molecular properties and applications in chemical synthesis, discovery, and drug design.

Enquiries: Miss Temmy So at tel 2609 8444

For more information, please refer to http://www.cse.cuhk.edu.hk/seminar