Reference : Global reconstruction of the human metabolic network based on genomic and bibliomic data.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/13043
Global reconstruction of the human metabolic network based on genomic and bibliomic data.
English
Duarte, Natalie C. [> >]
Becker, Scott A. [> >]
Jamshidi, Neema [> >]
Thiele, Ines mailto []
Mo, Monica L. [> >]
Vo, Thuy D. [> >]
Srivas, Rohith [> >]
Palsson, Bernhard O. [> >]
2007
Proceedings of the National Academy of Sciences of the United States of America
104
6
1777-82
Yes (verified by ORBilu)
0027-8424
1091-6490
United States
[en] Computational Biology ; Computer Simulation ; Gastric Bypass ; Gene Expression Profiling ; Genome, Human/physiology ; Humans/metabolism ; Metabolism/genetics/physiology ; Muscle, Skeletal/metabolism/surgery ; Systems Biology
[en] Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology.
http://hdl.handle.net/10993/13043

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