LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo from wikipedia

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… Click to show full abstract

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.

Keywords: weighted stochastic; comparison; simulation methods; simulation; stochastic simulation; biology

Journal Title: ACS synthetic biology
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.