{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Pdf":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.pdf"],"Svg":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.svg"],"Owl":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120-biopax3.owl","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120-biopax2.owl"],"Xml":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120_url.xml","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120_urn.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.vcml","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.m","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.sci","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.png","https://www.ebi.ac.uk/biomodels/model/download/MODEL6399676120?filename=MODEL6399676120.xpp"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"submitter":["Monica Mo"],"curationStatus":["Non-curated"],"levelVersion":["L2V3"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/MODEL6399676120"],"publication_pubmed":["17267599"],"isPrivate":["false"],"repository":["BioModels"],"modelFormat":["SBML"],"omics_type":["Models"],"tokenised_name":["Duarte2007 Homo sapiens Metabol Recon 1"],"publication_year":["2007"],"submissionId":["MODEL6399676120"],"modelFlag":["Non Kinetic"],"publication_authors":["Natalie C Duarte, Scott A Becker, Neema Jamshidi, Ines Thiele, Monica L Mo, Thuy D Vo, Rohith Srivas, Bernhard Ø Palsson"],"first_author":["Natalie C Duarte"],"publication":["17267599,\n                            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.. 6, 104.\n                            Bioengineering Department, University of California at San Diego, La Jolla, CA 92093-0412, USA."],"submitter_mail":["mlmo@ucsd.edu"],"submitter_affiliation":["University of California, San Diego"],"pubmed_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."],"pubmed_title":["Global reconstruction of the human metabolic network based on genomic and bibliomic data."],"pubmed_authors":["Duarte Natalie C NC, Becker Scott A SA, Jamshidi Neema N, Thiele Ines I, Mo Monica L ML, Vo Thuy D TD, Srivas Rohith R, Palsson Bernhard Ø BØ"],"additional_accession":[]},"is_claimable":false,"name":"Duarte2007_Homo_sapiens_Metabol_Recon_1","description":"\n      \n        This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team.      \n          To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to      CC0 Public Domain Dedication\n          for more information.      \n      In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..      \n      \n          To cite BioModels Database, please use:      Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.\n  \n\n","dates":{"last_modification":"2009-10-08","publication":"2005-01-01","submission":"2008-12-03"},"accession":"MODEL6399676120","cross_references":{"pubmed":["17267599"],"biomodels__db":["MODEL6399676120"],"go":["GO:0040008"],"taxonomy":["9606"]}}