Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2007-2-7
pubmed:abstractText
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.
pubmed:commentsCorrections
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pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0027-8424
pubmed:author
pubmed:issnType
Print
pubmed:day
6
pubmed:volume
104
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1777-82
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Global reconstruction of the human metabolic network based on genomic and bibliomic data.
pubmed:affiliation
Bioengineering Department, University of California at San Diego, La Jolla, CA 92093-0412, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural, Validation Studies