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Novel insights into obesity and diabetes through genome-scale metabolic modeling

Leif Väremo (Institutionen för kemi- och bioteknik, Systembiologi) ; Intawat Nookaew (Institutionen för kemi- och bioteknik, Systembiologi) ; Jens B. Nielsen (Institutionen för kemi- och bioteknik, Systembiologi)
Frontiers in Physiology (1664-042X). Vol. 4 (2013), 92,
[Artikel, refereegranskad vetenskaplig]

The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes (T2D) and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs) are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers, and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

Nyckelord: systems biology, metabolism, obesity, diabetes, genome-scale metabolic models, metabolic networks, topology, constraint-based modeling

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Denna post skapades 2013-04-26. Senast ändrad 2015-11-26.
CPL Pubid: 176218


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Institutioner (Chalmers)

Institutionen för kemi- och bioteknik, Systembiologi (2008-2014)


Bioinformatik och systembiologi

Chalmers infrastruktur

C3SE/SNIC (Chalmers Centre for Computational Science and Engineering)

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