PDF(Pubmed)
Abstract：
BACKGROUND: 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/C++ 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 Poincaré and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincaré serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincaré 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-in-time 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 Poincaré and SimBio as valuable tools for the modeling community.
METHODS: Poincaré and SimBio are released under the MIT license. Their source code is available on GitHub (https://github.com/maurosilber/poincare and https://github.com/hgrecco/simbio) and can be installed from PyPI or conda-forge.
RESULTS: In response, we developed Poincaré and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincaré serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincaré 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-in-time 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 Poincaré and SimBio as valuable tools for the modeling community.
METHODS: Poincaré and SimBio are released under the MIT license. Their source code is available on GitHub (https://github.com/maurosilber/poincare and https://github.com/hgrecco/simbio) and can be installed from PyPI or conda-forge.
摘要：
背景：化学反应网络（CRN）在系统生物学等不同领域发挥着关键作用，生物化学,化学工程,和流行病学。CRN的高级定义可以使用各种模拟方法，包括确定性和随机性方法，从相同的模型。然而,用于模拟CRN的现有Python工具通常包装外部C/C++库以进行模型定义，转换成方程和/或数值求解它们，限制了它们的可扩展性和与更广泛的Python生态系统的集成。
结果：作为回应，我们开发了庞加莱和SimBio,两个新颖的Python包，用于模拟动态系统和CRN。庞加莱是动力系统建模的基础，虽然SimBio将此功能扩展到CRN，包括对系统生物学标记语言（SBML）的支持。Poincaré和SimBio是作为纯Python软件包开发的，使用户能够通过编写新的或利用其他Python软件包来轻松扩展其模拟功能。此外，这不会影响性能，因为代码可以用Numba及时(JIT)编译。我们使用BioModels存储库中的精选模型进行的基准测试表明，与其他现有工具相比，这些工具可能提供潜在的卓越性能优势。此外,为了确保用户友好的体验，我们的软件包使用标准类型的现代Python语法，提供与集成开发环境（IDE）的无缝集成。我们以Python为中心的方法显着增强了代码分析，错误检测，和重构能力，将Poincaré和SimBio定位为建模社区的有价值的工具。
背景：Poincaré和SimBio是在MIT许可下发布的。它们的源代码可在GitHub上找到（https://github.com/maurosilber/pointcare和https://github.com/hgrecco/simbio）。并且可以从PyPI或conda-forge安装。
结果：作为回应，我们开发了庞加莱和SimBio,两个新颖的Python包，用于模拟动态系统和CRN。庞加莱是动力系统建模的基础，虽然SimBio将此功能扩展到CRN，包括对系统生物学标记语言（SBML）的支持。Poincaré和SimBio是作为纯Python软件包开发的，使用户能够通过编写新的或利用其他Python软件包来轻松扩展其模拟功能。此外，这不会影响性能，因为代码可以用Numba及时(JIT)编译。我们使用BioModels存储库中的精选模型进行的基准测试表明，与其他现有工具相比，这些工具可能提供潜在的卓越性能优势。此外,为了确保用户友好的体验，我们的软件包使用标准类型的现代Python语法，提供与集成开发环境（IDE）的无缝集成。我们以Python为中心的方法显着增强了代码分析，错误检测，和重构能力，将Poincaré和SimBio定位为建模社区的有价值的工具。
背景：Poincaré和SimBio是在MIT许可下发布的。它们的源代码可在GitHub上找到（https://github.com/maurosilber/pointcare和https://github.com/hgrecco/simbio）。并且可以从PyPI或conda-forge安装。
