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ČEŠKA, M. CHAU, C. KŘETÍNSKÝ, J.
Original Title
SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
Type
conference paper
Language
English
Original Abstract
Chemical reaction networks (CRNs) play a fundamental role in analysis and design of biochemical systems. They induce continuous-time stochastic systems, whose analysis is a computationally intensive task. We present a tool that implements the recently proposed semi-quantitative analysis of CRN. Compared to the proposed theory, the tool implements the analysis so that it is more flexible and more precise. Further, its GUI offers a wide range of visualization procedures that facilitate the interpretation of the analysis results as well as guidance to refine the analysis. Finally, we define and implement a new notion of "mean" simulations, summarizing the typical behaviours of the system in a way directly comparable to standard simulations produced by other tools.
Keywords
probabilistic verification, population Markov chains, abstraction
Authors
ČEŠKA, M.; CHAU, C.; KŘETÍNSKÝ, J.
Released
14. 7. 2020
Publisher
Springer Verlag
Location
Cham
ISBN
978-3-030-53287-1
Book
International Conference on Computer Aided Verification
Edition
Lecture Notes in Computer Science
Pages from
653
Pages to
666
Pages count
14
URL
https://link.springer.com/chapter/10.1007/978-3-030-53288-8_32
BibTex
@inproceedings{BUT168142, author="ČEŠKA, M. and CHAU, C. and KŘETÍNSKÝ, J.", title="SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks", booktitle="International Conference on Computer Aided Verification", year="2020", series="Lecture Notes in Computer Science", volume="12224", pages="653--666", publisher="Springer Verlag", address="Cham", doi="10.1007/978-3-030-53288-8\{_}32", isbn="978-3-030-53287-1", url="https://link.springer.com/chapter/10.1007/978-3-030-53288-8_32" }