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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...

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Autores principales: Loman, Torkel E., Ma, Yingbo, Ilin, Vasily, Gowda, Shashi, Korsbo, Niklas, Yewale, Nikhil, Rackauckas, Chris, Isaacson, Samuel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
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.
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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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