Abstract
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.
| Original language | English |
|---|---|
| Article number | 541 |
| Journal | BMC Bioinformatics |
| Volume | 9 |
| DOIs | |
| Publication status | Published - 2008 Dec 16 |
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ASJC Scopus subject areas
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Structural Biology
- Applied Mathematics
Cite this
GeNESiS : Gene network evolution simulation software. / Kratz, Anton; Tomita, Masaru; Krishnan, Arun.
In: BMC Bioinformatics, Vol. 9, 541, 16.12.2008.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - GeNESiS
T2 - Gene network evolution simulation software
AU - Kratz, Anton
AU - Tomita, Masaru
AU - Krishnan, Arun
PY - 2008/12/16
Y1 - 2008/12/16
N2 - 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.
AB - 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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U2 - 10.1186/1471-2105-9-541
DO - 10.1186/1471-2105-9-541
M3 - Article
C2 - 19087333
AN - SCOPUS:60749084381
VL - 9
JO - BMC Bioinformatics
JF - BMC Bioinformatics
SN - 1471-2105
M1 - 541
ER -