CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

Genome-scale modeling of human metabolism - a systems biology approach.

Adil Mardinoglu (Institutionen för kemi- och bioteknik, Systembiologi) ; Francesco Gatto (Institutionen för kemi- och bioteknik, Systembiologi) ; Jens B. Nielsen (Institutionen för kemi- och bioteknik, Systembiologi)
Biotechnology Journal (1860-6768). Vol. 8 (2013),
[Artikel, refereegranskad vetenskaplig]

Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models – one of the fundamental aspects of systems biology – have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

Nyckelord: Genome-scale metabolic models;Human Metabolic Reaction database;Personalized medicine;Systems biology;Whole-body modeling

Den här publikationen ingår i följande styrkeområden:

Läs mer om Chalmers styrkeområden  

Denna post skapades 2013-04-28. Senast ändrad 2017-09-14.
CPL Pubid: 176259


Institutioner (Chalmers)

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


Bioinformatik och systembiologi

Chalmers infrastruktur

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