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GeNESiS: gene network evolution simulation software

BACKGROUND: There has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze t...

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Detalles Bibliográficos
Autores principales: Kratz, Anton, Tomita, Masaru, Krishnan, Arun
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2640387/
https://www.ncbi.nlm.nih.gov/pubmed/19087333
http://dx.doi.org/10.1186/1471-2105-9-541
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author Kratz, Anton
Tomita, Masaru
Krishnan, Arun
author_facet Kratz, Anton
Tomita, Masaru
Krishnan, Arun
author_sort Kratz, Anton
collection PubMed
description BACKGROUND: There has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs. RESULTS: In this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs. CONCLUSION: We believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs.
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spelling pubmed-26403872009-02-12 GeNESiS: gene network evolution simulation software Kratz, Anton Tomita, Masaru Krishnan, Arun BMC Bioinformatics Software BACKGROUND: There has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs. RESULTS: In this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs. CONCLUSION: We believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs. BioMed Central 2008-12-16 /pmc/articles/PMC2640387/ /pubmed/19087333 http://dx.doi.org/10.1186/1471-2105-9-541 Text en Copyright © 2008 Kratz et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Kratz, Anton
Tomita, Masaru
Krishnan, Arun
GeNESiS: gene network evolution simulation software
title GeNESiS: gene network evolution simulation software
title_full GeNESiS: gene network evolution simulation software
title_fullStr GeNESiS: gene network evolution simulation software
title_full_unstemmed GeNESiS: gene network evolution simulation software
title_short GeNESiS: gene network evolution simulation software
title_sort genesis: gene network evolution simulation software
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2640387/
https://www.ncbi.nlm.nih.gov/pubmed/19087333
http://dx.doi.org/10.1186/1471-2105-9-541
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