Bioinformatics Advance Access published online on September 5, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl465
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1 Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, 1308 W. Main St., Urbana, IL 61801, USA
* To whom correspondence should be addressed.
Motivation: The stochastic kinetics of a well-mixed chemical system, governed by the chemical Master equation, can be simulated using the exact methods of Gillespie. However, these methods do not scale well as systems become more complex and larger models are built to include reactions with widely varying rates, since the computational burden of simulation increases with the number of reaction events. Continuous models may provide an approximate solution and are computationally less costly, but they fail to capture the stochastic behavior of small populations of macromolecules. Results: In this paper we present a hybrid simulation algorithm that dynamically partitions the system into subsets of continuous and discrete reactions, approximates the continuous reactions deterministically as a system of ordinary differential equations (ODE), and uses a Monte Carlo method for generating discrete reaction events according to a time-dependent propensity. Our approach to partitioning is improved in that we dynamically partition the system of reactions, based on a threshold relative to the distribution of propensities in the discrete subset. We have implemented the hybrid algorithm in an extensible framework, utilizing two rigorous ODE solvers to approximate the continuous reactions, and use an example model to illustrate the accuracy and potential speedup of the algorithm when compared to exact stochastic simulation. Availability: Software and benchmark models used for this publication can be made available upon request from the authors. Supplementary information: Complete lists of reactions and parameters of the HIV-1 Tat transactivation model, as well as additional results for other benchmark models, are available at http://www.mobius.uiuc.edu/bioinfo06/.
Received March 9, 2006
Revised August 4, 2006
Accepted August 26, 2006
Article
Dynamic partitioning for hybrid simulation of the bistable HIV-1 transactivation network
Mark Griffith 1, Tod Courtney 1 *, Jean Peccoud 2, and William H. Sanders 1
2 Virginia Bioinformatics Institute, Washington Street, MC 0477, Virginia Tech, Blacksburg, VA 24061, USA
Tod Courtney, E-mail: tod{at}crhc.uiuc.edu
Abstract
Associate Editor: Thomas Lengauer
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