Header

UZH-Logo

Maintenance Infos

A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays


Ramaswamy, Rajesh; Sbalzarini, Ivo F (2011). A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays. Journal of Chemical Physics, 134(1):014106.

Abstract

Several real-world systems, such as gene expression networks in biological cells, contain cou- pled chemical reactions with a time delay between reaction initiation and completion. The non- Markovian kinetics of such reaction networks can be exactly simulated using the delay stochastic simulation algorithm (dSSA). The computational cost of dSSA scales with the total number of reactions in the network. We reduce this cost to scale at most with the smaller number of species by using the concept of partial reaction propensities. The resulting delay partial-propensity direct method (dPDM) is an exact dSSA formulation for well-stirred systems of coupled chemical reac- tions with delays. We detail dPDM and present a theoretical analysis of its computational cost. Furthermore, we demonstrate the implications of the theoretical cost analysis in two prototypical benchmark applications. The dPDM formulation is shown to be particularly efficient for strongly coupled reaction networks, where the number of reactions is much larger than the number of species.

Abstract

Several real-world systems, such as gene expression networks in biological cells, contain cou- pled chemical reactions with a time delay between reaction initiation and completion. The non- Markovian kinetics of such reaction networks can be exactly simulated using the delay stochastic simulation algorithm (dSSA). The computational cost of dSSA scales with the total number of reactions in the network. We reduce this cost to scale at most with the smaller number of species by using the concept of partial reaction propensities. The resulting delay partial-propensity direct method (dPDM) is an exact dSSA formulation for well-stirred systems of coupled chemical reac- tions with delays. We detail dPDM and present a theoretical analysis of its computational cost. Furthermore, we demonstrate the implications of the theoretical cost analysis in two prototypical benchmark applications. The dPDM formulation is shown to be particularly efficient for strongly coupled reaction networks, where the number of reactions is much larger than the number of species.

Statistics

Citations

8 citations in Web of Science®
8 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

44 downloads since deposited on 05 Jul 2013
10 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > LipidX
Special Collections > SystemsX.ch > Research, Technology and Development Projects > WingX
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2011
Deposited On:05 Jul 2013 11:03
Last Modified:07 Dec 2017 21:38
Publisher:American Institute of Physics
ISSN:0021-9606
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1063/1.3521496

Download

Download PDF  'A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays'.
Preview
Content: Accepted Version
Filetype: PDF
Size: 2MB
View at publisher
Download PDF  'A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays'.
Preview
Content: Published Version
Filetype: PDF
Size: 609kB