Publication Details

SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks

ČEŠKA Milan, CHAU Calvin and KŘETÍNSKÝ Jan. SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks. In: International Conference on Computer Aided Verification. Lecture Notes in Computer Science, vol. 12224. Cham: Springer Verlag, 2020, pp. 653-666. ISBN 978-3-030-53287-1. Available from: https://link.springer.com/chapter/10.1007/978-3-030-53288-8_32
Czech title
SeQuaiA: Nástroj pro semikvantitativní analýzu chemických reakčních sítí
Type
conference paper
Language
english
Authors
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT)
Chau Calvin (TUM)
Křetínský Jan (TUM)
URL
Keywords

probabilistic verification,
population Markov chains,
abstraction

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.

Published
2020
Pages
653-666
Proceedings
International Conference on Computer Aided Verification
Series
Lecture Notes in Computer Science
Volume
12224
Conference
32th International Conference on Computer Aided Verification, Online, US
ISBN
978-3-030-53287-1
Publisher
Springer Verlag
Place
Cham, DE
DOI
10.1007/978-3-030-53288-8_32
UT WoS
000695276000032
EID Scopus
2-s2.0-85089219258
BibTeX 
@INPROCEEDINGS{FITPUB12353,
   author = "Milan \v{C}e\v{s}ka and Calvin Chau and Jan K\v{r}et\'{i}nsk\'{y}",
   title = "SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks",
   pages = "653--666",
   booktitle = "International Conference on Computer Aided Verification",
   series = "Lecture Notes in Computer Science",
   volume = 12224,
   year = 2020,
   location = "Cham, DE",
   publisher = "Springer Verlag",
   ISBN = "978-3-030-53287-1",
   doi = "10.1007/978-3-030-53288-8\_32",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12353"
}
Back to top