Standardization of data and models facilitates effective communication, especially in computational systems biology. However, both the development and consistent use of standards and resources remain challenging. As a result, the amount, quality, and format of the information contained within systems biology models are not consistent and therefore present challenges for widespread use and communication. Here, we focused on these standards, resources, and challenges in the field of constraint‐based metabolic modeling by conducting a community‐wide survey. We used this feedback to (i) outline the major challenges that our field faces and to propose solutions and (ii) identify a set of features that defines what a “gold standard” metabolic network reconstruction looks like concerning content, annotation, and simulation capabilities. We anticipate that this community‐driven outline will help the long‐term development of community‐inspired resources as well as produce high‐quality, accessible models within our field. More broadly, we hope that these efforts can serve as blueprints for other computational modeling communities to ensure the continued development of both practical, usable standards and reproducible, knowledge‐rich models.

中文翻译：

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促进开发和解决代谢建模挑战的社区标准。

数据和模型的标准化促进了有效的交流，尤其是在计算系统生物学中。然而，标准和资源的开发和一致使用仍然具有挑战性。因此，系统生物学模型中包含的信息的数量、质量和格式不一致，因此对广泛使用和交流提出了挑战。在这里，我们通过进行社区范围的调查来关注基于约束的代谢建模领域的这些标准、资源和挑战。我们使用此反馈来 (i) 概述我们的领域面临的主要挑战并提出解决方案，以及 (ii) 确定一组特征，这些特征定义了“黄金标准”代谢网络重建在内容、注释和模拟能力方面的样子. 我们预计这个社区驱动的大纲将有助于社区启发资源的长期发展，并在我们的领域内产生高质量、可访问的模型。更广泛地说，我们希望这些努力可以作为其他计算建模社区的蓝图，以确保实用、可用的标准和可重复的、知识丰富的模型的持续发展。