EN 生科百年 内網 新内網

檢測到您當前使用浏覽器版本過于老舊,會導緻無法正常浏覽網站;請您使用電腦裡的其他浏覽器如:360、QQ、搜狗浏覽器的極速模式浏覽,或者使用谷歌、火狐等浏覽器。

下載Firefox

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

日期: 2021-11-08

北京大學定量生物學中心

學術報告

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

報告人:  Professor Hong Qian

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

: 1122日(周一)13:00-14:00

: ZOOM線上報告

Meeting ID: 963 4868 5218

Passwordcqbcqb

主持人: 鄧明華 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.
報告人簡介:
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.