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

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. Comp...

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Detalles Bibliográficos
Autores principales: Češka, Milan, Chau, Calvin, Křetínský, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363201/
http://dx.doi.org/10.1007/978-3-030-53288-8_32
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author Češka, Milan
Chau, Calvin
Křetínský, Jan
author_facet Češka, Milan
Chau, Calvin
Křetínský, Jan
author_sort Češka, Milan
collection PubMed
description 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.
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spelling pubmed-73632012020-07-16 SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks Češka, Milan Chau, Calvin Křetínský, Jan Computer Aided Verification Article 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. 2020-06-13 /pmc/articles/PMC7363201/ http://dx.doi.org/10.1007/978-3-030-53288-8_32 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
Češka, Milan
Chau, Calvin
Křetínský, Jan
SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title_full SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title_fullStr SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title_full_unstemmed SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title_short SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks
title_sort sequaia: a scalable tool for semi-quantitative analysis of chemical reaction networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363201/
http://dx.doi.org/10.1007/978-3-030-53288-8_32
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