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Syntactic markovian bisimulation for chemical reaction networks

Abstract:

In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially large state spaces. This makes the analysis very difficult in practice and represents the major bottleneck for the applicability of minimization techniques based, for instance, on lumpability. In this paper we present syntactic Markovian bisimulation (SMB), a notion of bisimulation developed in the Larsen-Skou style of ...

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

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Publisher copy:
10.1007/978-3-319-63121-9_23

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Oxford college:
St Annes College
ORCID:
0000-0002-8705-8488
Tribastone, M More by this author
Tschaikowski, M More by this author

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Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor
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Funding agency for:
Cardelli, L
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Grant:
QUANTICOL, 600708
Publisher:
Springer, Cham Publisher's website
Volume:
10460
Pages:
466-483
Series:
Lecture Notes in Computer Science
Host title:
Models, Algorithms, Logics and Tools
Publication date:
2017-07-25
DOI:
ISSN:
0302-9743
Pubs id:
pubs:724764
URN:
uri:6b46dbcb-a2f0-4bef-8b8f-f1d8ea278129
UUID:
uuid:6b46dbcb-a2f0-4bef-8b8f-f1d8ea278129
Local pid:
pubs:724764
ISBN:
978-3-319-63120-2

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