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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Main Authors: Torkel E Loman, Yingbo Ma, Vasily Ilin, Shashi Gowda, Niklas Korsbo, Nikhil Yewale, Chris Rackauckas, Samuel A Isaacson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-10-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011530&type=printable
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author Torkel E Loman
Yingbo Ma
Vasily Ilin
Shashi Gowda
Niklas Korsbo
Nikhil Yewale
Chris Rackauckas
Samuel A Isaacson
author_facet Torkel E Loman
Yingbo Ma
Vasily Ilin
Shashi Gowda
Niklas Korsbo
Nikhil Yewale
Chris Rackauckas
Samuel A Isaacson
author_sort Torkel E Loman
collection DOAJ
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 Article
id doaj-art-60f207c7222a40df9cf4031b8bb09100
institution Kabale University
issn 1553-734X
1553-7358
language English
publishDate 2023-10-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS Computational Biology
spelling doaj-art-60f207c7222a40df9cf4031b8bb091002025-08-20T03:46:15ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582023-10-011910e101153010.1371/journal.pcbi.1011530Catalyst: Fast and flexible modeling of reaction networks.Torkel E LomanYingbo MaVasily IlinShashi GowdaNiklas KorsboNikhil YewaleChris RackauckasSamuel A IsaacsonWe 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.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011530&type=printable
spellingShingle Torkel E Loman
Yingbo Ma
Vasily Ilin
Shashi Gowda
Niklas Korsbo
Nikhil Yewale
Chris Rackauckas
Samuel A Isaacson
Catalyst: Fast and flexible modeling of reaction networks.
PLoS Computational Biology
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
url https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011530&type=printable
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AT shashigowda catalystfastandflexiblemodelingofreactionnetworks
AT niklaskorsbo catalystfastandflexiblemodelingofreactionnetworks
AT nikhilyewale catalystfastandflexiblemodelingofreactionnetworks
AT chrisrackauckas catalystfastandflexiblemodelingofreactionnetworks
AT samuelaisaacson catalystfastandflexiblemodelingofreactionnetworks