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Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art

Abstract:

Stochasticity is a key characteristic of intracellular processes such as gene regulation and chemical signalling. Therefore, characterizing stochastic effects in biochemical systems is essential to understand the complex dynamics of living things. Mathematical idealizations of biochemically reacting systems must be able to capture stochastic phenomena. While robust theory exists to describe such stochastic models, the computational challenges in exploring these models can be a significant bur...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1098/rsif.2018.0943

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Mathematical Institute
Oxford college:
St Hughs College
Role:
Author
ORCID:
0000-0002-6304-9333
Publisher:
Royal Society Publisher's website
Journal:
Journal of the Royal Society Interface Journal website
Volume:
16
Issue:
151
Pages:
Article: 20180943
Publication date:
2019-02-27
Acceptance date:
2019-02-06
DOI:
EISSN:
1742-5662
ISSN:
1742-5689
Pubs id:
pubs:953243
URN:
uri:5c9d7c69-ddc5-43c9-b44a-f87f0018a2a8
UUID:
uuid:5c9d7c69-ddc5-43c9-b44a-f87f0018a2a8
Local pid:
pubs:953243

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