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.; Ouzounis, ed., Christos A.

doi:10.1371/journal.pcbi.1011530

Title: Catalyst: Fast and flexible modeling of reaction networks

Journal Article · 17 October 2023 · PLoS Computational Biology (Online)

DOI: https://doi.org/10.1371/journal.pcbi.1011530 · OSTI ID:2202906

; Ma, Yingbo; Ilin, Vasily; Gowda, Shashi; Korsbo, Niklas; Yewale, Nikhil; Rackauckas, Chris;

; Ouzounis, ed., Christos A.

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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Sponsoring Organization:: USDOE

Grant/Contract Number:: AR0001222; AR0001211

OSTI ID:: 2202906

Alternate ID(s):: OSTI ID: 2471835

Journal Information:: PLoS Computational Biology (Online), Journal Name: PLoS Computational Biology (Online) Journal Issue: 10 Vol. 19; ISSN 1553-7358

Publisher:: Public Library of Science (PLoS)Copyright Statement

Country of Publication:: United States

Language:: English

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