Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Department of Medicine II, Saarland University Medical Center, Saarland University, Homburg, Germany.
Hepatology. 2017 Oct;66(4):1323-1334. doi: 10.1002/hep.29268. Epub 2017 Aug 30.
Understanding the dynamics of human liver metabolism is fundamental for effective diagnosis and treatment of liver diseases. This knowledge can be obtained with systems biology/medicine approaches that account for the complexity of hepatic responses and their systemic consequences in other organs. Computational modeling can reveal hidden principles of the system by classification of individual components, analyzing their interactions and simulating the effects that are difficult to investigate experimentally. Herein, we review the state-of-the-art computational models that describe liver dynamics from metabolic, gene regulatory, and signal transduction perspectives. We focus especially on large-scale liver models described either by genome scale metabolic networks or an object-oriented approach. We also discuss the benefits and limitations of each modeling approach and their value for clinical applications in diagnosis, therapy, and prevention of liver diseases as well as precision medicine in hepatology. (Hepatology 2017;66:1323-1334).
了解人类肝脏代谢的动态变化对于有效诊断和治疗肝脏疾病至关重要。系统生物学/医学方法可以帮助我们了解肝脏的复杂性以及肝脏对其他器官的系统性影响。通过对单个组件进行分类、分析它们的相互作用以及模拟难以通过实验研究来探讨的影响，计算模型可以揭示系统的隐藏原理。本文综述了从代谢、基因调控和信号转导角度描述肝脏动态变化的最新计算模型。我们特别关注通过基因组规模代谢网络或面向对象方法描述的大规模肝脏模型。我们还讨论了每种建模方法的优缺点及其在肝脏疾病的诊断、治疗和预防以及肝脏病学中的精准医学等临床应用中的价值。（《肝脏病学》2017；66：1323-1334）
