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A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models

Driven by the desire to understand genomic functions through the interactions among genes and gene products, the research in gene regulatory networks has become a heated area in genomic signal processing. Among the most studied mathematical models are Boolean networks and probabilistic Boolean netwo...

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Detalles Bibliográficos
Autor principal: Xiao, Yufei
Formato: Texto
Lenguaje:English
Publicado: Bentham Science Publishers Ltd. 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808677/
https://www.ncbi.nlm.nih.gov/pubmed/20436877
http://dx.doi.org/10.2174/138920209789208237
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author Xiao, Yufei
author_facet Xiao, Yufei
author_sort Xiao, Yufei
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description Driven by the desire to understand genomic functions through the interactions among genes and gene products, the research in gene regulatory networks has become a heated area in genomic signal processing. Among the most studied mathematical models are Boolean networks and probabilistic Boolean networks, which are rule-based dynamic systems. This tutorial provides an introduction to the essential concepts of these two Boolean models, and presents the up-to-date analysis and simulation methods developed for them. In the Analysis section, we will show that Boolean models are Markov chains, based on which we present a Markovian steady-state analysis on attractors, and also reveal the relationship between probabilistic Boolean networks and dynamic Bayesian networks (another popular genetic network model), again via Markov analysis; we dedicate the last subsection to structural analysis, which opens a door to other topics such as network control. The Simulation section will start from the basic tasks of creating state transition diagrams and finding attractors, proceed to the simulation of network dynamics and obtaining the steady-state distributions, and finally come to an algorithm of generating artificial Boolean networks with prescribed attractors. The contents are arranged in a roughly logical order, such that the Markov chain analysis lays the basis for the most part of Analysis section, and also prepares the readers to the topics in Simulation section.
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spelling pubmed-28086772010-05-01 A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models Xiao, Yufei Curr Genomics Article Driven by the desire to understand genomic functions through the interactions among genes and gene products, the research in gene regulatory networks has become a heated area in genomic signal processing. Among the most studied mathematical models are Boolean networks and probabilistic Boolean networks, which are rule-based dynamic systems. This tutorial provides an introduction to the essential concepts of these two Boolean models, and presents the up-to-date analysis and simulation methods developed for them. In the Analysis section, we will show that Boolean models are Markov chains, based on which we present a Markovian steady-state analysis on attractors, and also reveal the relationship between probabilistic Boolean networks and dynamic Bayesian networks (another popular genetic network model), again via Markov analysis; we dedicate the last subsection to structural analysis, which opens a door to other topics such as network control. The Simulation section will start from the basic tasks of creating state transition diagrams and finding attractors, proceed to the simulation of network dynamics and obtaining the steady-state distributions, and finally come to an algorithm of generating artificial Boolean networks with prescribed attractors. The contents are arranged in a roughly logical order, such that the Markov chain analysis lays the basis for the most part of Analysis section, and also prepares the readers to the topics in Simulation section. Bentham Science Publishers Ltd. 2009-11 /pmc/articles/PMC2808677/ /pubmed/20436877 http://dx.doi.org/10.2174/138920209789208237 Text en ©2009 Bentham Science Publishers Ltd. http://creativecommons.org/licenses/by/2.5/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Xiao, Yufei
A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title_full A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title_fullStr A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title_full_unstemmed A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title_short A Tutorial on Analysis and Simulation of Boolean Gene Regulatory Network Models
title_sort tutorial on analysis and simulation of boolean gene regulatory network models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808677/
https://www.ncbi.nlm.nih.gov/pubmed/20436877
http://dx.doi.org/10.2174/138920209789208237
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