The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to-date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C-metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands-on computer laboratory component of a four-day metabolic modeling workshop and participant survey results showed improvements in learners' self-assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

中文翻译：

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通过交互式 Python 模块进行代谢建模和通量分析的综合教学


代谢网络中生化反应速率（通量）的建模广泛用于基础生物学研究和生物技术应用。已经开发了许多不同的建模方法来估计和预测通量，包括动力学和基于约束的（代谢通量分析和通量平衡分析）方法。尽管存在不同的资源来单独教授这些方法，但迄今为止，还没有开发出任何资源来以综合的方式教授这些方法，使学习者能够理解每种建模范式、它们之间的相互关系以及可以使用的信息。从每个人那里收集到的。我们用 Python 开发了一系列建模模拟来教授动力学建模、代谢控制分析、13C 代谢通量分析和通量平衡分析。这些模拟以一系列交互式笔记本的形式呈现，其中包含指导性课程计划和相关的讲义。学习者通过运行模拟、生成和使用数据以及对修改模型参数的影响进行预测并验证，使用简单代谢网络模型来吸收关键原理。我们使用这些模拟作为为期四天的代谢建模研讨会的计算机实验室实践部分，参与者调查结果显示，参加研讨会后，学习者的自我评估能力和理解和应用代谢建模技术的信心都有所提高。所提供的资源可以全部或单独纳入本科生、研究生或研究生级别的生物工程和代谢建模课程和研讨会。