Global reconstruction of the human metabolic network based on genomic and bibliomic data.

@article{citeulike:1090233, abstract = {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.}, address = {Bioengineering Department, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412.}, author = {Duarte, Natalie C. C. and Becker, Scott A. A. and Jamshidi, Neema and Thiele, Ines and Mo, Monica L. L. and Vo, Thuy D. D. and Srivas, Rohith and Palsson, Bernhard O. O. }, citeulike-article-id = {1090233}, doi = {http://dx.doi.org/10.1073/pnas.0610772104}, issn = {0027-8424}, journal = {Proc Natl Acad Sci U S A}, keywords = {systems\_biology}, month = {January}, number = {6}, pages = {1777--1782}, posted-at = {2007-10-01 05:33:03}, priority = {2}, title = {Global reconstruction of the human metabolic network based on genomic and bibliomic data.}, url = {http://dx.doi.org/10.1073/pnas.0610772104}, volume = {104}, year = {2007} }

TY - JOUR ID - citeulike:1090233 L3 - citeulike-article-id:1090233 TI - Global reconstruction of the human metabolic network based on genomic and bibliomic data. JF - Proc Natl Acad Sci U S A VL - 104 IS - 6 SP - 1777 EP - 1782 AD - Bioengineering Department, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412. SN - 0027-8424 N2 - 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. KW - systems_biology AU - Duarte, Natalie AU - Becker, Scott AU - Jamshidi, Neema AU - Thiele, Ines AU - Mo, Monica AU - Vo, Thuy AU - Srivas, Rohith AU - Palsson, Bernhard PY - 2007/01/31/ UR - http://dx.doi.org/10.1073/pnas.0610772104 ER -