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cff-version: 1.2.0
title: SBMLToolkit.jl
message: >-
  If you use this software, please cite the preferred-citation in this file.
preferred-citation:
  type: article
  authors:
  - given-names: Paul
    name-particle: F
    family-names: Lang
    email: plang@deeporigin.com
    affiliation: Deep Origin
    orcid: 'https://orcid.org/0000-0002-6388-2405'
  - given-names: Anand
    family-names: Jain
  - given-names: Christopher
    family-names: Rackauckas
    orcid: 'https://orcid.org/0000-0001-5850-0663'
    affiliation: JuliaHub
  doi: "10.1515/jib-2024-0003"
  journal: "Journal of Integrative Bioinformatics"
  month: 5
  title: "SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem"
  year: 2024
  keywords:
    - systems biology markup language
    - SBML
    - Julia
    - scientific machine learning
  license: CC-BY-4.0
  repository-code: >-
    https://github.com/JuliaSmoothOptimizers/CaNNOLeS.jl
  abstract: >-
    Julia is a general purpose programming language that was
    designed for simplifying and accelerating numerical
    analysis and computational science. In particular the
    Scientific Machine Learning (SciML) ecosystem of Julia
    packages includes frameworks for high-performance
    symbolic-numeric computations. It allows users to
    automatically enhance high-level descriptions of their
    models with symbolic preprocessing and automatic
    sparsification and parallelization of computations. This
    enables performant solution of differential equations,
    efficient parameter estimation and methodologies for
    automated model discovery with neural differential
    equations and sparse identification of nonlinear dynamics.
    To give the systems biology community easy access to
    SciML, we developed SBMLToolkit.jl. SBMLToolkit.jl imports
    dynamic SBML models into the SciML ecosystem to accelerate
    model simulation and fitting of kinetic parameters. By
    providing computational systems biologists with easy
    access to the open-source Julia ecosystevnm, we hope to
    catalyze the development of further Julia tools in this
    domain and the growth of the Julia bioscience community.
    SBMLToolkit.jl is freely available under the MIT license.
    The source code is available at
    https://github.com/SciML/SBMLToolkit.jl.
type: software
authors:
  - given-names: Paul
    name-particle: F
    family-names: Lang
    affiliation: Deep Origin
    orcid: 'https://orcid.org/0000-0002-6388-2405'
  - given-names: Anand
    family-names: Jain
  - given-names: Christopher
    family-names: Rackauckas
    orcid: 'https://orcid.org/0000-0001-5850-0663'
    affiliation: JuliaHub
  - given-names: contributors
repository-code: 'https://github.com/SciML/SBMLToolkit.jl'
license: MIT