Algorithms and Software for Stochastic Simulation of Biochemical Reacting Systems

by: H Li, Y Cao, LR Petzold, DT Gillespie

Biotechnol. Prog. (26 September 2007)

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DOI, American Chem. Soc. Publications

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Abstract

Abstract: Traditional deterministic approaches for simulation of chemically reacting systems fail to capture the randomness inherent in such systems at scales common in intracellular biochemical processes. In this manuscript, we briefly review the state of the art in discrete stochastic and multiscale algorithms for simulation of biochemical systems and we present the StochKit software toolkit.

@article{citeulike:1719326, abstract = {Abstract: Traditional deterministic approaches for simulation of chemically reacting systems fail to capture the randomness inherent in such systems at scales common in intracellular biochemical processes. In this manuscript, we briefly review the state of the art in discrete stochastic and multiscale algorithms for simulation of biochemical systems and we present the StochKit software toolkit.}, address = {Department of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, Department of Computer Science, Virginia Tech, Blacksburg, Virginia 24061, and Dan T. Gillespie Consulting, 30504 Cordoba Place, Castaic, California 91384}, author = {Li, H. and Cao, Y. and Petzold, L. R. and Gillespie, D. T. }, citeulike-article-id = {1719326}, doi = {http://dx.doi.org/10.1021/bp070255h}, journal = {Biotechnol. Prog.}, keywords = {simulation\_algorithms, stochastic}, month = {September}, posted-at = {2007-11-26 17:02:53}, priority = {2}, title = {Algorithms and Software for Stochastic Simulation of Biochemical Reacting Systems}, url = {http://dx.doi.org/10.1021/bp070255h}, year = {2007} }

RIS record

TY - JOUR ID - citeulike:1719326 L3 - citeulike-article-id:1719326 TI - Algorithms and Software for Stochastic Simulation of Biochemical Reacting Systems JF - Biotechnol. Prog. AD - Department of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, Department of Computer Science, Virginia Tech, Blacksburg, Virginia 24061, and Dan T. Gillespie Consulting, 30504 Cordoba Place, Castaic, California 91384 N2 - Abstract: Traditional deterministic approaches for simulation of chemically reacting systems fail to capture the randomness inherent in such systems at scales common in intracellular biochemical processes. In this manuscript, we briefly review the state of the art in discrete stochastic and multiscale algorithms for simulation of biochemical systems and we present the StochKit software toolkit. KW - simulation_algorithms KW - stochastic AU - Li, H AU - Cao, Y AU - Petzold, LR AU - Gillespie, DT PY - 2007/09/26/ UR - http://dx.doi.org/10.1021/bp070255h ER -

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