Journal article
Hybrid framework for the simulation of stochastic chemical kinetics
- Abstract:
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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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(Version of record, pdf, 3.5MB)
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- Publisher copy:
- 10.1016/j.jcp.2016.08.034
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Authors
Funding
+ Leverhulme Trust
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Funding agency for:
Erban, R
Grant:
Philip Leverhulme Prize
Isaac Newton Institute for Mathematical Sciences
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Bibliographic Details
- 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:
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580171
Item Description
- Keywords:
- Pubs id:
-
pubs:580171
- UUID:
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uuid:12b95716-683b-4feb-ae86-4393804ace7e
- Local pid:
- pubs:580171
- Deposit date:
- 2016-08-29
Terms of use
- Copyright holder:
- Duncan et al
- Copyright date:
- 2016
- Notes:
- © 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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