Preprint Open Access

A finite state projection method for steady-state sensitivity analysis of stochastic reaction networks

Dürrenberger, Patrik; Gupta, Ankit; Khammash, Mustafa


Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Dürrenberger, Patrik</dc:creator>
  <dc:creator>Gupta, Ankit</dc:creator>
  <dc:creator>Khammash, Mustafa</dc:creator>
  <dc:date>2021-03-01</dc:date>
  <dc:description>Abstract

Consider the standard stochastic reaction network model where the dynamics is given by a continuous-time Markov chain over a discrete lattice. For such models, estimation of parameter sensitivities is an important problem, but the existing computational approaches to solve this problem usually require time-consuming Monte Carlo simulations of the reaction dynamics. Therefore, these simulation-based approaches can only be expected to work over finite time-intervals, while it is often of interest in applications to examine the sensitivity values at the steady-state after the Markov chain has relaxed to its stationary distribution. The aim of this paper is to present a computational method for the estimation of steady-state parameter sensitivities, which instead of using simulations relies on the recently developed stationary finite state projectionalgorithm [Gupta et al., J. Chem. Phys. 147, 154101 (2017)] that provides an accurate estimate of the stationary distribution at a fixed set of parameters. We show that sensitivity values at these parameters can be estimated from the solution of a Poisson equation associated with the infinitesimal generator of the Markov chain. We develop an approach to numerically solve the Poisson equation, and this yields an efficient estimator for steady-state parameter sensitivities. We illustrate this method using several examples.</dc:description>
  <dc:identifier>https://zenodo.org/record/4839189</dc:identifier>
  <dc:identifier>10.1063/1.5085271</dc:identifier>
  <dc:identifier>oai:zenodo.org:4839189</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/743269/</dc:relation>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/766840/</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/cosy-bio</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:source>The Journal of Chemical Physics 150(13)</dc:source>
  <dc:title>A finite state projection method for steady-state sensitivity analysis of stochastic reaction networks</dc:title>
  <dc:type>info:eu-repo/semantics/preprint</dc:type>
  <dc:type>publication-preprint</dc:type>
</oai_dc:dc>
3
4
views
downloads
Views 3
Downloads 4
Data volume 3.8 MB
Unique views 3
Unique downloads 4

Share

Cite as