Systems biology in hepatology: Approaches and applications
Review article, 2018

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.


Adil Mardinoglu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Royal Institute of Technology (KTH)

Jan Borén

Sahlgrenska University Hospital

Ulf Smith

Sahlgrenska University Hospital

Mathias Uhlen

Royal Institute of Technology (KTH)

Jens B Nielsen

Royal Institute of Technology (KTH)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Nature Reviews Gastroenterology and Hepatology

1759-5045 (ISSN) 1759-5053 (eISSN)

Vol. 15 6 365-377

Subject Categories

Bioinformatics (Computational Biology)

Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)

Bioinformatics and Systems Biology



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