PSU Mark
Eberly College of Science Mathematics Department

Meeting Details

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Title:Numerical methods for stochastic bio-chemical reacting networks with multiple time and concentration scales
Seminar:CCMA PDEs and Numerical Methods Seminar Series
Speaker:Di Liu, MSU
Abstract:
Multiscale and stochastic approaches play a crucial role in faithfully capturing the dynamical features and making insightful predictions of cellular reacting systems involving gene expression. A Genetic Regulatory Networks (GRN), describing all the reacting channels and species involved in gene expression, consists of a set of genes, proteins, small molecules and their mutual regulatory interactions. From the point of view of modeling, Genetic Regulatory Networks, unlike metabolism networks, involve fewer species and lower concentrations of molecules in a small volume within a cell; therefore stochastic effects have a significant impact on the system. Despite their accuracy, the standard stochastic simulation algorithms are necessarily inefficient for most of the realistic problems with a multiscale nature characterized by 1.) Rare events arising from the metastability of the system, 2.) Multiple time scales induced by widely disparate reactions rates, and 3.) Multiple well separated concentration scales of the reacting species. In this talk, I will discuss some recent progress on using asymptotic techniques for probability theory, e.g. Random Homogenization and Large Deviation Theory, to simplify the complex networks and help to design efficient numerical schemes.

Room Reservation Information

Room Number:MB216
Date:12 / 03 / 2007
Time:03:35pm - 04:25pm