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 |
|---|---|
| Title of host publication | 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 |
| DOIs | |
| 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 |
Other
| Other | 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010 |
|---|---|
| Country | United States |
| City | Cold Spring Harbor, NY |
| Period | 11/10/10 → 11/12/10 |
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Keywords
- Biochemical reaction system
- Rare event
- Stochastic simulation
ASJC Scopus subject areas
- Genetics
- Signal Processing
Cite this
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.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Importance sampling method for efficient estimation of the probability of rare events in biochemical reaction systems
AU - Xu, Zhouyi
AU - Cai, Xiaodong
PY - 2010/12/1
Y1 - 2010/12/1
N2 - 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.
AB - 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.
KW - Biochemical reaction system
KW - Rare event
KW - Stochastic simulation
UR - http://www.scopus.com/inward/record.url?scp=79952800776&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952800776&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2010.5719686
DO - 10.1109/GENSIPS.2010.5719686
M3 - Conference contribution
SN - 9781612847924
BT - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
ER -