Lubbock Alexander L R, Lopez Carlos F
Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37212, United States of America.
Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville Tennessee 37212, United States of America.
Curr Opin Syst Biol. 2021 Sep;27. doi: 10.1016/j.coisb.2021.05.004. Epub 2021 May 24.
Computational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with community standards used for interchange. Models undergo steady state or dynamic analysis, which can include simulation and calibration within a single application, or transfer across various tools. Here, we describe a novel programmatic modeling paradigm, whereby modeling is augmented with software engineering best practices. We focus on Python - a popular programming language with a large scientific package ecosystem. Models can be encoded as programs, adding benefits such as modularity, testing, and automated documentation generators, while still being extensible and exportable to standardized formats for use with external tools if desired. Programmatic modeling is a key technology to enable collaborative model development and enhance dissemination, transparency, and reproducibility.
计算建模已成为一种既定技术，用于对细胞过程的数学表示进行编码，并获得能够驱动可测试预测的机制性见解。这些模型通常使用图形用户界面或特定领域语言构建，并采用社区标准进行交换。模型会进行稳态或动态分析，这可以包括在单个应用程序内进行模拟和校准，或者跨各种工具进行转移。在这里，我们描述了一种新颖的编程建模范式，通过软件工程最佳实践增强建模。我们专注于Python——一种拥有庞大科学软件包生态系统的流行编程语言。模型可以编码为程序，带来诸如模块化、测试和自动文档生成器等好处，同时如果需要，仍然可以扩展并导出为标准化格式以供外部工具使用。编程建模是实现协作式模型开发并提高传播、透明度和可重复性的关键技术。
