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Hepatology. 2017 Oct;66(4):1323-1334. doi: 10.1002/hep.29268. Epub 2017 Aug 30.

Large-scale computational models of liver metabolism: How far from the clinics?

Author information

1
Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
2
Department of Medicine II, Saarland University Medical Center, Saarland University, Homburg, Germany.
3
Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Abstract

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).

PMID:
28520105
DOI:
10.1002/hep.29268
[Indexed for MEDLINE]

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