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Hybrid framework for the simulation of stochastic chemical kinetics

Abstract:

Stochasticity plays a fundamental role in various biochemical processes, such as cell regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be modelled as Markov processes, typically simulated using the Gillespie Stochastic Simulation Algorithm (SSA) [26]. While easy to implement and exact, the computational cost of using the Gillespie SSA to simulate such systems can become prohibitive as the frequency of reaction events increases. This has motivated numerous coarse-gra...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jcp.2016.08.034

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
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Funding agency for:
Erban, R
Grant:
Philip Leverhulme Prize
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Funding agency for:
Erban, R
Grant:
Philip Leverhulme Prize
Isaac Newton Institute for Mathematical Sciences More from this funder
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Publisher:
Elsevier Publisher's website
Journal:
Journal of Computational Physics Journal website
Volume:
326
Pages:
398–419
Publication date:
2016-08-01
Acceptance date:
2016-08-24
DOI:
Source identifiers:
580171
Keywords:
Pubs id:
pubs:580171
UUID:
uuid:12b95716-683b-4feb-ae86-4393804ace7e
Local pid:
pubs:580171
Deposit date:
2016-08-29

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