A Comparison of Weighted Stochastic Simulation Methods for the Analysis of Genetic Circuits
A Comparison of Weighted Stochastic Simulation Methods for the Analysis of Genetic Circuits
复制标题
遗传电路分析的加权随机模拟方法比较
DOI：
10.1021/acssynbio.2c00553
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发表时间：
2023
影响因子：
4.7
通讯作者：
Zheng, Hao
中科院分区：
文献类型：
--
作者：
Ahmadi, Mohammad;Thomas, Payton J.;Buecherl, Lukas;Winstead, Chris;Myers, Chris J.;Zheng, Hao
罕见事件在合成生物学中特别令人感兴趣，因为罕见生物化学事件可能对生物系统是灾难性的，例如，通过触发不可逆事件，如脱靶药物递送。为了有效地估计罕见事件的概率，已经发展了几种加权随机模拟方法。在优化参数和模型条件下，这些方法可以大大提高模拟效率相比，传统的随机模拟。不幸的是，最佳的参数和条件不能推导出先验。本文对加权随机模拟方法进行了评述。它表明，这里考虑的方法不能一致，有效，准确地完成任务的稀有事件模拟，而不诉诸于计算昂贵的校准程序，这会破坏他们的整体效率。结果表明，在这些方法可以部署用于生物模拟的一般用途之前，需要进一步的发展。
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 deduceda 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.