-Title: 『Ensemble Modeling in Systems Biology』

-Speaker: Dr. Sang Ok Song (Critical Care Medicine, University of Pittsburgh Medical School)

-Date: 5 January, 2012 (Thu) 4:30PM

-Place: #1101 @ W1-3 Bldg.

-Abstract:

Systems biology aims at system-level understanding of complex biological systems by focusing on dynamic interactions between components in the system. Predictive dynamic models can provide mechanistic insights of the behavior of biological systems and assist in the identification of therapeutic targets. Building dynamic models of biological systems requires quantitative information on model parameters which are not available or directly accessible in vivo.

The sparsity of good quality experimental data together with the uncertainty stemming from the fundamental ill-posedness of the inverse problem in biological complexity impose significant challenges to reliable model parameter estimation. The conventional approaches to find a unique "best" parameter set often give meaningless or misleading results. Given this reality in systems biology, ensemble modeling approaches to probabilistically infer a family of model parameter sets consistent with experimental data seems appropriate, offering a means to quantify parametric uncertainty.

A brief introduction of systems biology and its related issues are reviewed and mathematical modeling studies spanning from molecular and cellular levels to tissue and organ levels are presented. Modeling and analysis of ATP-induced P2 mediated calcium signaling in sensory neurons generate qualitative insight into the critical interactions controlling ATP induced calcium dynamics. The ensemble model of coarse- grained dynamics of the acute inflammatory response in sepsis serve as effective tool to gain insight into the pathophysiology of severe sepsis and generate testable hypotheses that guide future experiments.

※ For international students, attendance of this seminar will be considered as attendance of department seminar during regular semester.