Metabolic network analysis is an accessible and versatile modeling approach for biology that has taken much inspiration from electric circuit analysis. After introducing its main concepts, we focus on numerical tools, such as optimization and sampling, to predict cellular features and behaviors at a large scale. Optimization approaches exploit that metabolic networks are shaped by evolution and are, thus, assumed to embed a fitness condition reflecting the environment that they evolved in. In the past ten years, there is a trend to generalize metabolic network analysis to consortia of interacting species. This raises technical questions on, for example, optimality in consortia but also more general ones on metabolic coevolution, information exchange, and adaptation. This suggests and allows us to explore interesting analogies to technological systems, specifically to smart grids.

中文翻译：

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代谢网络、微生物联盟和智能电网的类比

代谢网络分析是一种可访问且通用的生物学建模方法，它从电路分析中获得了很多灵感。在介绍了它的主要概念之后，我们专注于数值工具，例如优化和采样，以大规模预测细胞特征和行为。优化方法利用了代谢网络是由进化形成的，因此假定嵌入了反映它们进化的环境的适应度条件。在过去十年中，有一种趋势是将代谢网络分析推广到相互作用物种的联合体。这引发了技术问题，例如，联合体的最优性，以及代谢协同进化、信息交换和适应等更普遍的问题。