Modelling Genetic Regulatory Networks

摘要：

A genetic regulatory network (GRN) is a dynamic system to describe interactions among a large number of different substances in a living biological cell.There have been numerous attempts to model the dynamical behaviour of genetic regulatory networks.Boolean models are a class of discrete models for modelling genetic regulatory networks,which are conditioned on the premise that genes interact with each other through Boolean logic.As mentioned previously,Boolean models include Boolean Networks,Instantaneously Random Probabilistic Boolean Networks and Context-Sensitive Boolean Networks.There are a large number of issues surrounding Boolean models,including Boolean Networks and Probabilistic Boolean Networks.The model inference is the procedure of determining whether the modelled networks are consistent with the given data sample,and choosing one model,from among many,that makes more sense for the data.This paper has reviewed the research into modelling gene regulatory networks,especially upon Boolean models.

作者: Le Yu Zhong Su

会议类型: 国际会议

会议名称: Asia Simulation Conference 2008/the 7th International Conference on System Simulation and Scientific Computing(2008亚洲仿真会议/第七届系统仿真和科学计算国际会议)(ICSC2008)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-10（万方平台首次上网日期，不代表论文的发表时间）