Best Practices for Making Reproducible Biochemical Models
Best Practices for Making Reproducible Biochemical Models
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DOI：
10.1016/j.cels.2020.06.012
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发表时间：
2020-08-26
期刊：
影响因子：
9.3
通讯作者：
Sauro, Herbert M.
中科院分区：
文献类型：
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作者：
Porubsky, Veronica L.;Goldberg, Arthur P.;Sauro, Herbert M.
像许多科学学科一样，动态生化建模受到不可复制结果的阻碍。这限制了生化模型的实用性，因为它们很难理解、信任或重复使用。我们全面列出了生化建模师在构建可重复使用的生化模型人工制品时应遵循的最佳实践-模型使用的所有数据、模型描述和定制软件-可以理解和重复使用。最佳实践为非典型生化建模工作流的所有步骤提供建议，在这些步骤中，建模师收集数据；构造、训练、模拟和验证模型；使用模型的预测来推进知识；以及公开共享模型构件。最佳实践强调通过使用标准工具和格式获得的好处，并为在建模工作流程的某些阶段不使用或不能使用标准的建模者提供指导。采用这些最佳实践将提高研究人员复制、理解和重复使用生化模型的能力。
Like many scientific disciplines, dynamical biochemical modeling is hindered by irreproducible results. This limits the utility of biochemical models by making them difficult to understand, trust, or reuse. We comprehensively list the best practices that biochemical modelers should follow to build reproducible biochemical model artifacts-all data, model descriptions, and custom software used by the model-that can be understood and reused. The best practices provide advice for all steps of atypical biochemical modeling workflow in which a modeler collects data; constructs, trains, simulates, and validates the model; uses the predictions of a model to advance knowledge; and publicly shares the model artifacts. The best practices emphasize the benefits obtained by using standard tools and formats and provides guidance to modelers who do not or cannot use standards in some stages of their modeling workflow. Adoption of these best practices will enhance the ability of researchers to reproduce, understand, and reuse biochemical models.