Book section
Syntactic markovian bisimulation for chemical reaction networks
- Abstract:
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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
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- Files:
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(Accepted manuscript, pdf, 327.5KB)
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- Publisher copy:
- 10.1007/978-3-319-63121-9_23
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Authors
Contributors
+ Aceto, L
Role:
Editor
+ Bacci, G
Role:
Editor, Editor
+ Ingólfsdóttir, A
Role:
Editor
+ Legay, A
Role:
Editor
+ Mardare, R
Role:
Editor
Funding
Bibliographic Details
- 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
- Source identifiers:
-
724764
- ISBN:
- 9783319631202
Item Description
- Pubs id:
-
pubs:724764
- UUID:
-
uuid:6b46dbcb-a2f0-4bef-8b8f-f1d8ea278129
- Local pid:
- pubs:724764
- Deposit date:
- 2018-06-13
Terms of use
- Copyright holder:
- Springer International Publishing AG
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 Springer International Publishing AG. This is the accepted manuscript version of the chapter. The final version is available online from Springer at: https://doi.org/10.1007/978-3-319-63121-9_23
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