Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA.
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA; Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, 22908, USA.
Comput Biol Med. 2019 Feb;105:64-71. doi: 10.1016/j.compbiomed.2018.12.010. Epub 2018 Dec 17.
GEnome-scale Network REconstructions (GENREs) mathematically describe metabolic reactions of an organism or a specific cell type. GENREs can be used with a number of constraint-based reconstruction and analysis (COBRA) methods to make computational predictions on how a system changes in different environments. We created a simplified GENRE (referred to as iSIM) that captures central energy metabolism with nine metabolic reactions to illustrate the use of and promote the understanding of GENREs and constraint-based methods. We demonstrate the simulation of single and double gene deletions, flux variability analysis (FVA), and test a number of metabolic tasks with the GENRE. Code to perform these analyses is provided in Python, R, and MATLAB. Finally, with iSIM as a guide, we demonstrate how inaccuracies in GENREs can limit their use in the interrogation of energy metabolism.
基因组尺度网络重建（GENRE）从数学角度描述了生物体或特定细胞类型的代谢反应。GENRE 可以与许多基于约束的重建和分析（COBRA）方法一起使用，以便在不同环境下对系统的变化进行计算预测。我们创建了一个简化的 GENRE（简称 iSIM），它包含九个代谢反应，以捕捉中心能量代谢，以说明 GENRE 和基于约束的方法的使用和促进对它们的理解。我们演示了单基因和双基因缺失的模拟、通量变异性分析（FVA），并使用 GENRE 测试了许多代谢任务。执行这些分析的代码提供了 Python、R 和 MATLAB 版本。最后，以 iSIM 为指导，我们演示了 GENRE 的不准确性如何限制它们在能量代谢研究中的使用。
