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Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems

The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined wSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient estimation of the probability of rare events in biochemical reaction systems. In this p...

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Detalles Bibliográficos
Autores principales: Xu, Zhouyi, Cai, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171305/
https://www.ncbi.nlm.nih.gov/pubmed/21910924
http://dx.doi.org/10.1186/1687-4153-2011-797251
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author Xu, Zhouyi
Cai, Xiaodong
author_facet Xu, Zhouyi
Cai, Xiaodong
author_sort Xu, Zhouyi
collection PubMed
description The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined wSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient estimation of the probability of rare events in biochemical reaction systems. In this paper, we first apply the importance sampling technique to the next reaction method (NRM) of the stochastic simulation algorithm and develop a weighted NRM (wNRM). We then develop a systematic method for selecting the values of importance sampling parameters, which can be applied to both the wSSA and the wNRM. Numerical results demonstrate that our parameter selection method can substantially improve the performance of the wSSA and the wNRM in terms of simulation efficiency and accuracy.
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spelling pubmed-31713052011-09-13 Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems Xu, Zhouyi Cai, Xiaodong EURASIP J Bioinform Syst Biol Research The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined wSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient estimation of the probability of rare events in biochemical reaction systems. In this paper, we first apply the importance sampling technique to the next reaction method (NRM) of the stochastic simulation algorithm and develop a weighted NRM (wNRM). We then develop a systematic method for selecting the values of importance sampling parameters, which can be applied to both the wSSA and the wNRM. Numerical results demonstrate that our parameter selection method can substantially improve the performance of the wSSA and the wNRM in terms of simulation efficiency and accuracy. Springer 2011-07-25 /pmc/articles/PMC3171305/ /pubmed/21910924 http://dx.doi.org/10.1186/1687-4153-2011-797251 Text en Copyright © 2011 Xu and Cai; licensee Springer. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Xu, Zhouyi
Cai, Xiaodong
Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title_full Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title_fullStr Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title_full_unstemmed Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title_short Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
title_sort weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171305/
https://www.ncbi.nlm.nih.gov/pubmed/21910924
http://dx.doi.org/10.1186/1687-4153-2011-797251
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