Gene regulatory networks driven by intrinsic noise with two-time scales： a stochastic averaging approach  

作　　者：Fuke WU George YIN Tianhai TIAN 

机构地区：[1]School of Mathematics and Statistics, Huazhong University of Science and Technology,Wuhan 430074, China [2]Department of Mathematics, Wayne State University, Detroit, MI 48202, USA [3]School of Mathematical Sciences, Monash University, Melbourne Vic 3800, Australia

出　　处：《Frontiers of Mathematics in China》2014年第4期947-963,共17页中国高等学校学术文摘·数学（英文）

摘　　要：This work focuses on gene regulatory networks driven by intrinsic noise with two-time scales. It uses a stochastic averaging approach for these systems to reduce complexity. Comparing with the traditional quasi-steady- state hypothesis （QSSH）, our approach uses stochastic averaging principle to treat the intrinsic noise coming from both the fast-changing variables and the slow-changing variables, which yields a more precise description of the underlying systems. To provide further insight, this paper also investigates a prototypical two-component activator-repressor genetic circuit model as an example. If all the protein productions were linear, these two methods would yield the same reduction result. However, if one of the protein productions is nonlinear, the stochastic averaging principle leads to a different reduction result from that of the traditional QSSH.This work focuses on gene regulatory networks driven by intrinsic noise with two-time scales. It uses a stochastic averaging approach for these systems to reduce complexity. Comparing with the traditional quasi-steady- state hypothesis （QSSH）, our approach uses stochastic averaging principle to treat the intrinsic noise coming from both the fast-changing variables and the slow-changing variables, which yields a more precise description of the underlying systems. To provide further insight, this paper also investigates a prototypical two-component activator-repressor genetic circuit model as an example. If all the protein productions were linear, these two methods would yield the same reduction result. However, if one of the protein productions is nonlinear, the stochastic averaging principle leads to a different reduction result from that of the traditional QSSH.

关 键 词：Two-time scales intrinsic noise intracellular reaction chemicalLangevin equation （CLE） stationary distribution 

分 类 号：O324[理学—一般力学与力学基础] Q253[理学—力学]