Hybrid numerical solution of the chemical master equation Conference Paper


Author(s): Henzinger, Thomas A; Mateescu, Maria; Mikeev, Linar; Wolf, Verena
Title: Hybrid numerical solution of the chemical master equation
Affiliation IST Austria
Abstract: We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe net- works of biochemical reactions and play an important role in the stochastic modeling of biological systems. Our approach is based on the construction of a stochastic hybrid model in which certain discrete random variables of the original Markov chain are approximated by continuous deterministic variables. We compute the solution of the stochastic hybrid model using a numerical algorithm that discretizes time and in each step performs a mutual update of the transient prob- ability distribution of the discrete stochastic variables and the values of the continuous deterministic variables. We im- plemented the algorithm and we demonstrate its usefulness and efficiency on several case studies from systems biology.
Keywords: Markov process; biochemical reaction network; chemical master equation; stochastic hybrid model
Conference Title: CMSB: Computational Methods in Systems Biology
Conference Dates: September 29 - October 1, 2010
Conference Location: Trento, Italy
ISBN: 978-331923400-7
Publisher: Springer  
Date Published: 2010-09-01
Start Page: 55
End Page: 65
URL:
DOI: 10.1145/1839764.1839772
Notes: This research has been partially funded by the Swiss Na- tional Science Foundation under grant 205321-111840 and by the German Research Council (DFG) as part of the Clus- ter of Excellence on Multimodal Computing and Interaction at Saarland University and the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS).
Open access: yes (repository)
IST Austria Authors
  1. Thomas A. Henzinger
    415 Henzinger
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