ArticlePLoS computational biology2023
Catalyst: Fast and flexible modeling of reaction networks.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed.
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- Mixed positive and negative feedback loops drive diverse single-cell gene expression dynamics.Nature communications · 2026Article
- Fundamental limits on symmetry breaking by Turing-like activator-inhibitor mechanisms.Development (Cambridge, England) · 2026Article
- Systems-level consequences of low RAF abundance for EGFR-ERK signaling.Biophysical journal · 2026Article
- Article
- PEtab.jl: advancing the efficiency and utility of dynamic modelling.Bioinformatics (Oxford, England) · 2025Article
- A BRC1-modulated switch in auxin efflux accounts for the competition between Arabidopsis axillary buds.PLoS biology · 2025Article
- Translating microbial kinetics into quantitative responses and testable hypotheses using Kinbiont.Nature communications · 2025Article
- Correction: Catalyst: Fast and flexible modeling of reaction networks.PLoS computational biology · 2025Article
- Environmental and molecular noise buffering by the cyanobacterial clock in individual cells.Nature communications · 2025Article
- A Nudge to the Truth: Atom Conservation as a Hard Constraint in Models of Atmospheric Composition Using a Species-Weighted Correction.ACS ES&T air · 2025Article
- MxlPy-Python package for mechanistic learning and hybrid modelling in life science.Bioinformatics advances · 2025Article
- Kinetic Modeling Enables Understanding of Off-Cycle Processes in Pd-Catalyzed Amination of Five-Membered Heteroaryl Halides.Journal of the American Chemical Society · 2024Article
- Advancing Mathematical Epidemiology and Chemical Reaction Network Theory via Synergies Between Them.Entropy (Basel, Switzerland) · 2024Article
- Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Predicting Long-Time-Scale Kinetics under Variable Experimental Conditions with Kinetica.jl.Journal of chemical theory and computation · 2024Article
- Feedback between stochastic gene networks and population dynamics enables cellular decision-making.Science advances · 2024Article
- SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem.Journal of integrative bioinformatics · 2024Article
- A stochastic model of hippocampal synaptic plasticity with geometrical readout of enzyme dynamics.eLife · 2023Article
- How proton transfer impacts hachimoji DNA.RSC advances · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.