Browse by author
Lookup NU author(s): Dr Colin GillespieORCiD,
Dr Andrew Golightly
This is the authors' accepted manuscript of an article that has been published in its final definitive form by American Institute of Physics Inc., 2019.
For re-use rights please refer to the publisher's terms and conditions.
© 2019 Author(s). Rare event probabilities play an important role in the understanding of the behavior of biochemical systems. Due to the intractability of the most natural Markov jump process representation of a system of interest, rare event probabilities are typically estimated using importance sampling. While the resulting algorithm is reasonably well developed, the problem of choosing a suitable importance density is far from straightforward. We therefore leverage recent developments on simulation of conditioned jump processes to propose an importance density that is simple to implement and requires no tuning. Our results demonstrate superior performance over some existing approaches.
Author(s): Gillespie CS, Golightly A
Publication type: Article
Publication status: Published
Journal: Journal of Chemical Physics
Online publication date: 12/06/2019
Acceptance date: 31/05/2019
Date deposited: 29/07/2019
ISSN (print): 0021-9606
ISSN (electronic): 1089-7690
Publisher: American Institute of Physics Inc.
Altmetrics provided by Altmetric