Title: Systems Bioinformatics: Networks for Personalized Medicine

Speaker: Dr. Gil Alterovitz
         Assistant Professor ,Harvard Medical School, Harvard University

Time and Date: January 5, 2011,2:30pm

Avenue：Multifunctional Hall, Mingdao Building

Abstract:
Systems Bioinformatics is based on three principles: integration, abstraction, and prediction.  This talk will describe work that accomplishes this using a Bayesian, network, and information theoretic framework.  This work: integrates genetic and medical information to quantitative networks of dependencies, abstracts information via multi-scale Bayesian networks to establish relevant biomedical metrics (e.g. disease pathways), and predicts phenotypes of medical relevance such as complex behavioral traits (e.g. nicotine dependence).  This overall approach and/or subcomponents have also been used in other areas.  Linking knowledge networks under contexts with terabytes empirical information is one such area.   Finally, this talk will explore recent work on development of predictive networks for determining individual variability in drug response.