Efficient Formulations for Exact Stochastic Simulation of Chemical Systems Export

@article{citeulike:4451224, abstract = {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 http://cain.sourceforge.net, 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.}, address = {Los Alamitos, CA, USA}, author = {Mauch, Sean and Stalzer, Mark}, citeulike-article-id = {4451224}, citeulike-linkout-0 = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.47}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/TCBB.2009.47}, doi = {10.1109/TCBB.2009.47}, issn = {1545-5963}, journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics}, number = {1}, posted-at = {2009-05-02 14:57:21}, priority = {2}, publisher = {IEEE Computer Society}, title = {Efficient Formulations for Exact Stochastic Simulation of Chemical Systems}, url = {http://dx.doi.org/10.1109/TCBB.2009.47}, volume = {99}, year = {5555} }

TY - JOUR ID - citeulike:4451224 L3 - citeulike-article-id:4451224 N2 - 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 http://cain.sourceforge.net, 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. IS - 1 JF - IEEE/ACM Transactions on Computational Biology and Bioinformatics SN - 1545-5963 AD - Los Alamitos, CA, USA TI - Efficient Formulations for Exact Stochastic Simulation of Chemical Systems PB - IEEE Computer Society VL - 99 AU - Mauch, Sean AU - Stalzer, Mark PY - 5555/// UR - http://dx.doi.org/10.1109/TCBB.2009.47 ER -