Abstract: The task of molecular biology is to identify and define cellular states and functions in terms of chemical structures and reactions. Molecular genetics elucidates the structures and functions of DNA in terms of its sequence and gene expressions; biochemistry elucidates chemical reactions, macromolecular structural dynamics, and their functions, as well as protein reaction networks (i.e., pathways) that control transcription, signaling, and cell functions.  In recent years, the chemical master equation (CME) has become the model for biochemical reactions in living cells.  The theory supersedes the 

traditional deterministic models based on the law of mass action; it provides reaction kinetics and concentration (or copy number) fluctuations; and it allows a rigorous definition of "cellular state(s)" in terms of the concentrations and copy numbers of 

biomolecules in a cell.  We discuss the mathematical foundation of the CME and the computational approach to cellular biochemistry, its relation to open-system thermodynamics.  In particular we outline its similarities to and distinctions from computational macromolecular dynamics.

报告人简介：

Professor Qian received his B.A. in Astrophysics from Peking University in China in 1982, and his Ph.D. in Biochemistry and Biophysics from Washington University School of Medicine in St. Louis in 1989. 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. 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. His current research areas are computaional systems biology at the cellular level, molecular biophysics, and mathematical biology. These include large-scale metabolic networks, protein interaction networks and signal transduction modeling, protein thermodynamics and folding, and macromolecular mechanics of single molecules (FCS, SPT, AFM, SME) as well as mathematical modeling for motor protein, muscle contraction, cell motility, and cancer metastasis.