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Efficient Formulations for Exact Stochastic Simulation of Chemical Systems

Mauch, Sean and Stalzer, Mark (2011) Efficient Formulations for Exact Stochastic Simulation of Chemical Systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8 (1). pp. 27-35. ISSN 1545-5963.

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One can generate trajectories to simulate a system of chemical reactions using either Gillespie's direct method or Gibson and Bruck's next reaction method. Because one usually needs many trajectories to understand the dynamics of a system, performance is important. In this paper, we present new formulations of these methods that improve the computational complexity of the algorithms. We present optimized implementations, available from>, that offer better performance than previous work. There is no single method that is best for all problems. Simple formulations often work best for systems with a small number of reactions, while some sophisticated methods offer the best performance for large problems and scale well asymptotically. We investigate the performance of each formulation on simple biological systems using a wide range of problem sizes. We also consider the numerical accuracy of the direct and the next reaction method. We have found that special precautions must be taken in order to ensure that randomness is not discarded during the course of a simulation.

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Additional Information:© 2011 IEEE. Manuscript received 23 Jan. 2009; revised 9 Apr. 2009; accepted 11 Apr. 2009; published online 30 Apr. 2009. This project was supported by Grant Number R01EB007511 from the National Institute of Biomedical Imaging and Bioengineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Biomedical Imaging and Bioengineering or the National Institutes of Health. The authors gratefully acknowledge Dan Gillespie, Linda Petzold and her research group at UCSB, and Michael Hucka for many useful conversations and comments.
Funding AgencyGrant Number
National Institute of Biomedical Imaging and BioengineeringR01EB007511
Subject Keywords:Biology and genetics; stochastic processes; algorithm design and analysis
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INSPEC Accession Number11640159
PubMed ID21071794
Issue or Number:1
Record Number:CaltechAUTHORS:20120524-142544167
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Official Citation:Mauch, S.; Stalzer, M.; , "Efficient Formulations for Exact Stochastic Simulation of Chemical Systems," Computational Biology and Bioinformatics, IEEE/ACM Transactions on , vol.8, no.1, pp.27-35, Jan.-Feb. 2011 doi: 10.1109/TCBB.2009.47
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:31639
Deposited By: Jason Perez
Deposited On:24 May 2012 22:44
Last Modified:03 Oct 2019 03:53

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