Genome scale metabolic models (GEMs) offer a powerful means of integrating genome and biochemical information on an organism to make testable predictions of metabolic functions at different conditions and to systematically predict essential genes that may be targeted by drugs. This review describes how Plasmodium GEMs have become increasingly more accurate through the integration of omics and experimental genetic data. We also discuss how GEMs contribute to our increasing understanding of how Plasmodium metabolism is reprogrammed between life cycle stages.

中文翻译：

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疟原虫红细胞代谢和肝脏阶段的基因组重建

基因组规模代谢模型 (GEM) 提供了一种强大的方法，可以整合生物体的基因组和生化信息，以对不同条件下的代谢功能进行可测试的预测，并系统地预测可能被药物靶向的必需基因。这篇综述描述了疟原虫GEM如何通过组学和实验遗传数据的整合变得越来越准确。我们还讨论了 GEM 如何帮助我们加深对疟原虫代谢如何在生命周期阶段之间重新编程的理解。