Cargando…

libRoadRunner 2.0: a high performance SBML simulation and analysis library

MOTIVATION: This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML). RESULTS: libRoadRunner is a self-contained library, able to run eit...

Descripción completa

Detalles Bibliográficos
Autores principales: Welsh, Ciaran, Xu, Jin, Smith, Lucian, König, Matthias, Choi, Kiri, Sauro, Herbert M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825722/
https://www.ncbi.nlm.nih.gov/pubmed/36478036
http://dx.doi.org/10.1093/bioinformatics/btac770
_version_ 1784866683884666880
author Welsh, Ciaran
Xu, Jin
Smith, Lucian
König, Matthias
Choi, Kiri
Sauro, Herbert M
author_facet Welsh, Ciaran
Xu, Jin
Smith, Lucian
König, Matthias
Choi, Kiri
Sauro, Herbert M
author_sort Welsh, Ciaran
collection PubMed
description MOTIVATION: This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML). RESULTS: libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom just-in-time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a large variety of processors, making it fast enough to simulate extremely large models or repeated runs in reasonable timeframes. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) as well as several SBML extensions such as hierarchical composition and probability distributions. It offers multiple deterministic and stochastic integrators, as well as tools for steady-state, sensitivity, stability and structural analyses. AVAILABILITY AND IMPLEMENTATION: libRoadRunner binary distributions for Windows, Mac OS and Linux, Julia and Python bindings, source code and documentation are all available at https://github.com/sys-bio/roadrunner, and Python bindings are also available via pip. The source code can be compiled for the supported systems as well as in principle any system supported by LLVM-13, such as ARM-based computers like the Raspberry Pi. The library is licensed under the Apache License Version 2.0.
format Online
Article
Text
id pubmed-9825722
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-98257222023-01-10 libRoadRunner 2.0: a high performance SBML simulation and analysis library Welsh, Ciaran Xu, Jin Smith, Lucian König, Matthias Choi, Kiri Sauro, Herbert M Bioinformatics Original Paper MOTIVATION: This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML). RESULTS: libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom just-in-time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a large variety of processors, making it fast enough to simulate extremely large models or repeated runs in reasonable timeframes. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) as well as several SBML extensions such as hierarchical composition and probability distributions. It offers multiple deterministic and stochastic integrators, as well as tools for steady-state, sensitivity, stability and structural analyses. AVAILABILITY AND IMPLEMENTATION: libRoadRunner binary distributions for Windows, Mac OS and Linux, Julia and Python bindings, source code and documentation are all available at https://github.com/sys-bio/roadrunner, and Python bindings are also available via pip. The source code can be compiled for the supported systems as well as in principle any system supported by LLVM-13, such as ARM-based computers like the Raspberry Pi. The library is licensed under the Apache License Version 2.0. Oxford University Press 2022-12-08 /pmc/articles/PMC9825722/ /pubmed/36478036 http://dx.doi.org/10.1093/bioinformatics/btac770 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Welsh, Ciaran
Xu, Jin
Smith, Lucian
König, Matthias
Choi, Kiri
Sauro, Herbert M
libRoadRunner 2.0: a high performance SBML simulation and analysis library
title libRoadRunner 2.0: a high performance SBML simulation and analysis library
title_full libRoadRunner 2.0: a high performance SBML simulation and analysis library
title_fullStr libRoadRunner 2.0: a high performance SBML simulation and analysis library
title_full_unstemmed libRoadRunner 2.0: a high performance SBML simulation and analysis library
title_short libRoadRunner 2.0: a high performance SBML simulation and analysis library
title_sort libroadrunner 2.0: a high performance sbml simulation and analysis library
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825722/
https://www.ncbi.nlm.nih.gov/pubmed/36478036
http://dx.doi.org/10.1093/bioinformatics/btac770
work_keys_str_mv AT welshciaran libroadrunner20ahighperformancesbmlsimulationandanalysislibrary
AT xujin libroadrunner20ahighperformancesbmlsimulationandanalysislibrary
AT smithlucian libroadrunner20ahighperformancesbmlsimulationandanalysislibrary
AT konigmatthias libroadrunner20ahighperformancesbmlsimulationandanalysislibrary
AT choikiri libroadrunner20ahighperformancesbmlsimulationandanalysislibrary
AT sauroherbertm libroadrunner20ahighperformancesbmlsimulationandanalysislibrary