Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems

Zhouyi Xu; Xiaodong Cai

doi:10.1109/GENSIPS.2010.5719686

Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems

Zhouyi Xu, Xiaodong Cai

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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. However, both the wSSA and the refined wSSA do not provide a systematic method for selecting the values of importance sampling parameters but require some initial guessing for those values. In this paper, we develop a systematic method for selecting the values of importance sampling parameters for the wSSA. Numerical results demonstrate that our parameter selection method can substantially improve the performance of the wSSA in terms of simulation efficiency and accuracy.

Original language	English (US)
Title of host publication	2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
DOIs	https://doi.org/10.1109/GENSIPS.2010.5719686
State	Published - Dec 1 2010
Event	2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 - Cold Spring Harbor, NY, United States Duration: Nov 10 2010 → Nov 12 2010

Publication series

Name	2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010

Other

Other	2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
Country/Territory	United States
City	Cold Spring Harbor, NY
Period	11/10/10 → 11/12/10

Keywords

Biochemical reaction system
Rare event
Stochastic simulation

ASJC Scopus subject areas

Genetics
Signal Processing

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10.1109/GENSIPS.2010.5719686

Cite this

Xu, Z., & Cai, X. (2010). Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems. In 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 [5719686] (2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010). https://doi.org/10.1109/GENSIPS.2010.5719686

Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems. / Xu, Zhouyi; Cai, Xiaodong.

2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010. 2010. 5719686 (2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Xu, Z & Cai, X 2010, Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems. in 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010., 5719686, 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010, 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010, Cold Spring Harbor, NY, United States, 11/10/10. https://doi.org/10.1109/GENSIPS.2010.5719686

Xu Z, Cai X. Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems. In 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010. 2010. 5719686. (2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010). https://doi.org/10.1109/GENSIPS.2010.5719686

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abstract = "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. However, both the wSSA and the refined wSSA do not provide a systematic method for selecting the values of importance sampling parameters but require some initial guessing for those values. In this paper, we develop a systematic method for selecting the values of importance sampling parameters for the wSSA. Numerical results demonstrate that our parameter selection method can substantially improve the performance of the wSSA in terms of simulation efficiency and accuracy.",

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Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems

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Keywords

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