A Comparison of Weighted Stochastic Simulation Methods for the Analysis of Genetic Circuits

被引:2
|
作者
Ahmadi, Mohammad [1 ]
Thomas, Payton J. [2 ]
Buecherl, Lukas [3 ]
Winstead, Chris [4 ]
Myers, Chris J. [3 ]
Zheng, Hao [1 ]
机构
[1] Univ S Florida, Dept Comp Sci & Engn, Tampa, FL 33620 USA
[2] Univ Utah, Dept Biomed Engn, Salt Lake City, UT 84112 USA
[3] Univ Colorado Boulder, Dept Elect Comp & Energy Engn, Boulder, CO 80309 USA
[4] Utah State Univ, Dept Elect & Comp Engn, Logan, UT 84322 USA
来源
ACS SYNTHETIC BIOLOGY | 2023年 / 12卷 / 01期
基金
美国国家科学基金会;
关键词
stochastic simulation; rare event simulation; importance sampling; weighted ensemble; genetic circuits; stochastic chemical kinetics;
D O I
10.1021/acssynbio.2c00553
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Rare events are of particular interest in synthetic biology because rare biochemical events may be catastrophic to a biological system by, for example, triggering irreversible events such as off-target drug delivery. To estimate the probability of rare events efficiently, several weighted stochastic simulation methods have been developed. Under optimal parameters and model conditions, these methods can greatly improve simulation efficiency in comparison to traditional stochastic simulation. Unfortunately, the optimal parameters and conditions cannot be deduced a priori. This paper presents a critical survey of weighted stochastic simulation methods. It shows that the methods considered here cannot consistently, efficiently, and exactly accomplish the task of rare event simulation without resorting to a computationally expensive calibration procedure, which undermines their overall efficiency. The results suggest that further development is needed before these methods can be deployed for general use in biological simulations.
引用
收藏
页码:287 / 304
页数:18
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