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Bioinformatics Advance Access originally published online on January 31, 2007
Bioinformatics 2007 23(6):777-779; doi:10.1093/bioinformatics/btm004
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

SGN Sim, a Stochastic Genetic Networks Simulator

Andre S. Ribeiro 1,2,* and Jason Lloyd-Price 1

1Institute for Biocomplexity and Informatics, University of Calgary, Canada and 2Centre for Computational Physics, University of Coimbra, P-3004-516 Coimbra, Portugal

*To whom correspondence should be addressed.


  Abstract

Summary: We present SGNSim, ‘Stochastic Gene Networks Simulator’, a tool to model gene regulatory networks (GRN) where transcription and translation are modeled as multiple time delayed events and its dynamics is driven by a stochastic simulation algorithm (SSA) able to deal with multiple time delayed events. The delays can be drawn from several distributions and the reaction rates from complex functions or from physical parameters. SGNSim can generate ensembles of GRNs, within a set of user-defined parameters, such as topology. It can also be used to model specific GRNs and systems of chemical reactions. Perturbations, e.g. gene deletion, over-expression, copy and mutation, can be modeled as well. As examples, we present a model of a toggle switch without cooperative binding subject to perturbations, a system of reactions within a compartmentalized environment where membrane crossing is controlled by a negative feedback mechanism and a simulation based on the yeast transcriptional network.

Availability: SGNSim program, instructions and examples available at http://www.cs.tut.fi/~sanchesr/SGN/SGNSim.html.

Contact: andre.sanchesribeiro{at}tut.fi

Associate Editor: Chris Stoeckert

Received on November 5, 2006; revised on January 4, 2007; accepted on January 10, 2007

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[Abstract] [Full Text] [PDF]


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