In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models
Review article, 2017

The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising framework for uncovering the mechanistic relationship between genotype and phenotype. GEMs hereby enable uncovering associations between cellular physiology and pathology in a systematic manner. Here we review the current progress on reconstruction of human GEMs and how they have been employed as scaffold for interpreting multi-omics high-throughput data with the objective to identify disease-specific metabolic features. We further discuss recent achievements on how to apply these findings for potential target identification and therapeutic drug development. There are, however, challenges in developing models that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions.

Drug development

Human metabolism

Constraint-based analysis

Genome-scale metabolic model

Topological analysis

Author

Jun Geng

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Jens B Nielsen

Technical University of Denmark (DTU)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Royal Institute of Technology (KTH)

Current Opinion in Systems Biology

2452-3100 (ISSN) 2452-3100 (eISSN)

Vol. 2 29-38

Subject Categories

Pharmaceutical Sciences

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

DOI

10.1016/j.coisb.2017.01.001

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Latest update

5/2/2018 1