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Catalyst: Fast and flexible modeling of reaction networks

Abstract:
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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1011530

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-4453-0682
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Role:
Author
ORCID:
0009-0001-5271-7025
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Role:
Author
ORCID:
0000-0001-8046-6043
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Role:
Author
ORCID:
0000-0001-9811-3190


Publisher:
Public Library of Science
Journal:
PLoS Computational Biology More from this journal
Volume:
19
Issue:
10
Pages:
e1011530-e1011530
Publication date:
2023-10-18
DOI:
EISSN:
1553-7358
ISSN:
1553-734X


Language:
English
Keywords:
Pubs id:
2361684
Local pid:
pubs:2361684
Source identifiers:
W4387736994
Deposit date:
2026-01-19
ARK identifier:
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