Dr. Takis Benos, Department of Computational and Systems Biology, University of Pittsburgh
Multi-modal Data Integration and Causal Inference in Systems Medicine
Abstract: The advancement of technologies for high-throughput collection of personal data, including lifestyle, clinical and biomedical data, has inadvertently transformed biology and medicine. Integrating and co-analyzing these different data streams has become the research bottleneck and, in all likelihood, will be a central research topic for the next decade. My group has historically worked on the development of statistical and computational methods to identify key molecules (genes, microRNAs, etc) that affect disease onset and progression. More recently, we became interested in how we can combine the power of genomics with the rich medical data that are available. In this talk, I will present some of our recent efforts on causal modeling over mixed data types (continuous and discrete variables) and how to apply them to address important biomedical and clinical questions in chronic diseases and cancer diagnosis and therapy.
Hosting Faculty: Dr. George Bebis
Saturday, March 9 at 12:00pm to 1:00pm