Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
J Intern Med. 2012 Feb;271(2):131-41. doi: 10.1111/j.1365-2796.2011.02494.x.
Metabolism plays a key role in many major human diseases. Generation of high-throughput omics data has ushered in a new era of systems biology. Genome-scale metabolic network reconstructions provide a platform to interpret omics data in a biochemically meaningful manner. The release of the global human metabolic network, Recon 1, in 2007 has enabled new systems biology approaches to study human physiology, pathology and pharmacology. There are currently more than 20 publications that utilize Recon 1, including studies of cancer, diabetes, host-pathogen interactions, heritable metabolic disorders and off-target drug binding effects. In this mini-review, we focus on the reconstruction of the global human metabolic network and four classes of its application. We show that computational simulations for numerous pathologies have yielded clinically relevant results, many corroborated by existing or newly generated experimental data.
新陈代谢在许多重大人类疾病中起着关键作用。高通量组学数据的产生开创了系统生物学的新纪元。基因组规模的代谢网络重建为以生化方式解释组学数据提供了一个平台。2007 年全球人类代谢网络 Recon 1 的发布,使研究人类生理学、病理学和药理学的新系统生物学方法成为可能。目前,有 20 多篇出版物利用 Recon 1,包括癌症、糖尿病、宿主-病原体相互作用、遗传性代谢紊乱和非靶标药物结合效应的研究。在这篇迷你综述中,我们重点介绍了全球人类代谢网络的重建及其四类应用。我们表明,对许多病理的计算模拟已经产生了具有临床意义的结果,其中许多结果得到了现有或新生成的实验数据的证实。