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Catalyst: Fast and flexible modeling of reaction networks
We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reacti...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584191/ https://www.ncbi.nlm.nih.gov/pubmed/37851697 http://dx.doi.org/10.1371/journal.pcbi.1011530 |
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author | Loman, Torkel E. Ma, Yingbo Ilin, Vasily Gowda, Shashi Korsbo, Niklas Yewale, Nikhil Rackauckas, Chris Isaacson, Samuel A. |
author_facet | Loman, Torkel E. Ma, Yingbo Ilin, Vasily Gowda, Shashi Korsbo, Niklas Yewale, Nikhil Rackauckas, Chris Isaacson, Samuel A. |
author_sort | Loman, Torkel E. |
collection | PubMed |
description | We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation. |
format | Online Article Text |
id | pubmed-10584191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-105841912023-10-19 Catalyst: Fast and flexible modeling of reaction networks Loman, Torkel E. Ma, Yingbo Ilin, Vasily Gowda, Shashi Korsbo, Niklas Yewale, Nikhil Rackauckas, Chris Isaacson, Samuel A. PLoS Comput Biol Research Article We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation. Public Library of Science 2023-10-18 /pmc/articles/PMC10584191/ /pubmed/37851697 http://dx.doi.org/10.1371/journal.pcbi.1011530 Text en © 2023 Loman et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Loman, Torkel E. Ma, Yingbo Ilin, Vasily Gowda, Shashi Korsbo, Niklas Yewale, Nikhil Rackauckas, Chris Isaacson, Samuel A. Catalyst: Fast and flexible modeling of reaction networks |
title | Catalyst: Fast and flexible modeling of reaction networks |
title_full | Catalyst: Fast and flexible modeling of reaction networks |
title_fullStr | Catalyst: Fast and flexible modeling of reaction networks |
title_full_unstemmed | Catalyst: Fast and flexible modeling of reaction networks |
title_short | Catalyst: Fast and flexible modeling of reaction networks |
title_sort | catalyst: fast and flexible modeling of reaction networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584191/ https://www.ncbi.nlm.nih.gov/pubmed/37851697 http://dx.doi.org/10.1371/journal.pcbi.1011530 |
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