Genome-scale models (GEMs) are predictive tools to study genotype-phenotype relationships in biological systems. Initially, genome-scale models were used for predicting the metabolic state of the organism given the nutrient condition and genetic perturbation (if any). Such metabolic (M-) models have been successfully developed for diverse organisms in both prokaryotes and eukaryotes. In this review, we focus our attention to genome-scale models of metabolism and macromolecular expression or ME-models. ME-models expand the scope of M-models by incorporating macromolecular biosynthesis pathways of transcription and translation. ME-models can predict the proteome investment in metabolism under any given condition. Therefore, ME-models significantly improve the quantitative prediction of gene expression. Unlike M-models that can predict biological properties in only nutrient-limited condition, ME-models can do so in both nutrient- and proteome-limited conditions. There are a few limitations of ME-models, many of which have now been largely overcome, making them more attractive to the broader research community. We finally discuss the applications of GEMs in general, and how they have been applied for biomedical, bioengineering and bioremediation purposes.

基因组规模模型（GEM）是研究生物系统中基因型与表型关系的预测工具。最初，在给定营养条件和遗传扰动（如果有）的情况下，使用基因组规模模型来预测生物的代谢状态。已经针对原核生物和真核生物中的多种生物成功开发了这种代谢（M-）模型。在这篇综述中，我们将注意力集中在代谢和大分子表达的基因组规模模型或ME模型上。通过整合转录和翻译的大分子生物合成途径，ME模型扩大了M模型的范围。ME模型可以预测任何给定条件下蛋白质组在新陈代谢上的投资。因此，ME模型显着改善了基因表达的定量预测。与仅在营养限制条件下可以预测生物学特性的M模型不同，ME模型可以在营养限制和蛋白质组限制条件下进行预测。ME模型存在一些局限性，其中许多现已被克服，这使其对更广泛的研究界更具吸引力。最后，我们将讨论GEM的一般应用，以及它们如何用于生物医学，生物工程和生物修复目的。