Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems
- Autores
- Silberberg, Mauro; Hermjakob, Henning; Malik Sheriff, Rahuman S.; Grecco, Hernan Edgardo
- Año de publicación
- 2024
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Motivation: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/Cþþ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. Results: In response, we developed Poincare and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincare serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincare and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-intime compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. In addition, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments. Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincare and SimBio as valuable tools for the modeling community.
Fil: Silberberg, Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Hermjakob, Henning. European Molecular Biology Laboratory; Alemania
Fil: Malik Sheriff, Rahuman S.. European Molecular Biology Laboratory; Alemania
Fil: Grecco, Hernan Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina - Materia
-
modelling
simulation
python
ODE - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/264098
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Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systemsSilberberg, MauroHermjakob, HenningMalik Sheriff, Rahuman S.Grecco, Hernan EdgardomodellingsimulationpythonODEhttps://purl.org/becyt/ford/1.7https://purl.org/becyt/ford/1Motivation: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/Cþþ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. Results: In response, we developed Poincare and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincare serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincare and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-intime compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. In addition, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments. Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincare and SimBio as valuable tools for the modeling community.Fil: Silberberg, Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Hermjakob, Henning. European Molecular Biology Laboratory; AlemaniaFil: Malik Sheriff, Rahuman S.. European Molecular Biology Laboratory; AlemaniaFil: Grecco, Hernan Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaOxford University Press2024-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/264098Silberberg, Mauro; Hermjakob, Henning; Malik Sheriff, Rahuman S.; Grecco, Hernan Edgardo; Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems; Oxford University Press; Bioinformatics; 40; 8; 8-2024; 1-61367-4811CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btae465/7723995info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btae465info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:54:07Zoai:ri.conicet.gov.ar:11336/264098instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:54:08.15CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
title |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
spellingShingle |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems Silberberg, Mauro modelling simulation python ODE |
title_short |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
title_full |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
title_fullStr |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
title_full_unstemmed |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
title_sort |
Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems |
dc.creator.none.fl_str_mv |
Silberberg, Mauro Hermjakob, Henning Malik Sheriff, Rahuman S. Grecco, Hernan Edgardo |
author |
Silberberg, Mauro |
author_facet |
Silberberg, Mauro Hermjakob, Henning Malik Sheriff, Rahuman S. Grecco, Hernan Edgardo |
author_role |
author |
author2 |
Hermjakob, Henning Malik Sheriff, Rahuman S. Grecco, Hernan Edgardo |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
modelling simulation python ODE |
topic |
modelling simulation python ODE |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.7 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Motivation: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/Cþþ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. Results: In response, we developed Poincare and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincare serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincare and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-intime compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. In addition, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments. Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincare and SimBio as valuable tools for the modeling community. Fil: Silberberg, Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: Hermjakob, Henning. European Molecular Biology Laboratory; Alemania Fil: Malik Sheriff, Rahuman S.. European Molecular Biology Laboratory; Alemania Fil: Grecco, Hernan Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina |
description |
Motivation: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/Cþþ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. Results: In response, we developed Poincare and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincare serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincare and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-intime compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. In addition, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments. Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincare and SimBio as valuable tools for the modeling community. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-08 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/264098 Silberberg, Mauro; Hermjakob, Henning; Malik Sheriff, Rahuman S.; Grecco, Hernan Edgardo; Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems; Oxford University Press; Bioinformatics; 40; 8; 8-2024; 1-6 1367-4811 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/264098 |
identifier_str_mv |
Silberberg, Mauro; Hermjakob, Henning; Malik Sheriff, Rahuman S.; Grecco, Hernan Edgardo; Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems; Oxford University Press; Bioinformatics; 40; 8; 8-2024; 1-6 1367-4811 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
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application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Oxford University Press |
publisher.none.fl_str_mv |
Oxford University Press |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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