Stochastic neural network models for gene regulatory networks

Tianhai Tian, Kevin Burrage

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

36 Citations (Scopus)

Abstract

Recent advances in gene-expression profiling technologies provide large amounts of gene expression data. This raises the possibility for a functional understanding of genome dynamics by means of mathematical modelling. As gene expression involves intrinsic noise, stochastic models are essential for better descriptions of gene regulatory networks. However, stochastic modelling for large scale gene expression data sets is still in the very early developmental stage. In this paper we present some stochastic models by introducing stochastic processes into neural network models that can describe intermediate regulation for large scale gene networks. Poisson random variables are used to represent chance events in the processes of synthesis and degradation. For expression data with normalized concentrations, exponential or normal random variables are used to realize fluctuations. Using a network with three genes, we show how to use stochastic simulations for studying robustness and stability properties of gene expression patterns under the influence of noise, and how to use stochastic models to predict statistical distributions of expression levels in population of cells. The discussion suggest that stochastic neural network models can give better description of gene regulatory networks and provide criteria for measuring the reasonableness o mathematical models.

Original languageEnglish
Title of host publication2003 Congress on Evolutionary Computation, CEC 2003 - Proceedings
Subtitle of host publication2003 Congress on Evolutionary Computation, CEC 2003; Canberra, ACT; Australia; 8 December 2003 through 12 December 2003
Pages162-169
Number of pages8
DOIs
Publication statusPublished - 1 Jan 2003
EventIEEE Congress on Evolutionary Computation 2003 - Canberra, Australia
Duration: 8 Dec 200312 Dec 2003
https://ieeexplore.ieee.org/xpl/conhome/9096/proceeding (Proceedings)

Conference

ConferenceIEEE Congress on Evolutionary Computation 2003
Abbreviated titleIEEE CEC 2003
CountryAustralia
CityCanberra
Period8/12/0312/12/03
Internet address

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