北京大学定量生物学中心

学术报告 

题    目: Gibbs' Theory and Statistical Physics: A third approach to understanding the biological world probabilistically?

报告人:  Professor Hong Qian

Olga Jung Wan Professor of Applied Mathematics, Department of Applied Mathematics, University of Washington, Seattle

时    间: 11月22日（周一）13:00-14:00

地    点: ZOOM线上报告

Meeting ID: 963 4868 5218

Password：cqbcqb

主持人: 邓明华 教授

摘 要:

How to apply the mathematical theory of probability to real world problems?  Interpretations of "what is probability" have led to the Bayesian and frequentist schools, and current biophysics mainly is based on stochastic modeling.  I try to show how Gibbs' theory stitches together both thoughts, as well as the large deviations theory, an asymptotic analysis of the law of large numbers.  This yields the statistical ensemble as a parametric family of probabilistic models that are specifically informed by the nature of "observables".  Two well-known entropy functions, Gibbs' and Shannon's, as well as the Pitman-Koopman-Darmois theorem, figure prominently in our theory.   

报告人简介：

Professor Qian (Q=Ch) received his B.A. in Astrophysics from Peking University in China, and his Ph.D. in Biochemistry and Biophysics from Washington University School of Medicine in St. Louis. Subsequently, he worked as postdoctoral researcher at University of Oregon and Caltech on biophysical chemistry and mathematical biology. Before joining the University of Washington, he was an assistant professor of Biomathematics at UCLA School of Medicine. From 1992-1994, he was a fellow with the Program in Mathematics and Molecular Biology (PMMB), a NSF-funded multi-university consortium.  He was elected a fellow of the American Physical Society in 2010.

Professor Qian's main research interest is the mathematical approach to and physical understanding of biological systems, especially in terms of stochastic mathematics and nonequilibrium statistical physics. In recent years, he has been particularly interested in a nonlinear, stochastic, open system approach to cellular dynamics. Similar population dynamic approach can be applied to other complex systems and processes, such as those in ecology, infection epidemics, and economics. He believes his recent work on the statistical thermodynamic laws of general Markov processes can have applications in ecomomic dynamics and theory of values. In his research on cellular biology, his recent interest is in isogenetic variations and possible pre-genetic biochemical origins of oncogenesis.