{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Txt":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=curation_notes.txt"],"Pdf":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497.pdf"],"Owl":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497-biopax2.owl","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497-biopax3.owl"],"Xml":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=manifest.xml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497_url.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=metadata.rdf","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497-matlab.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497_url.sedml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497.ode","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=BIOMD0000000497.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000497?filename=curation_image.png"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"submitter":["Vijayalakshmi Chelliah"],"curationStatus":["Manually curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["L2V4"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/BIOMD0000000497"],"publication_pubmed":["24324546"],"isPrivate":["false"],"repository":["BioModels"],"modelFormat":["SBML"],"omics_type":["Models"],"tokenised_name":["Stanford2013   Kinetic model of yeast metabolic network (regulation)"],"publication_year":["2013"],"submissionId":["MODEL1307040000"],"publication_authors":["Natalie J Stanford, Timo Lubitz, Kieran Smallbone, Edda Klipp, Pedro Mendes, Wolfram Liebermeister"],"first_author":["Natalie J Stanford"],"publication":["24324546,\n                            The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.. 11, 8.\n                            School of Computer Science, Manchester Centre for Integrative Systems Biology, University of Manchester, Manchester, United Kingdom."],"submitter_mail":["viji@ebi.ac.uk"],"submitter_affiliation":["EMBL-EBI"],"publicationId":["BIOMD0000000497"],"pubmed_abstract":["The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments."],"pubmed_title":["Systematic construction of kinetic models from genome-scale metabolic networks."],"pubmed_authors":["Stanford Natalie J NJ, Lubitz Timo T, Smallbone Kieran K, Klipp Edda E, Mendes Pedro P, Liebermeister Wolfram W"],"additional_accession":[]},"is_claimable":false,"name":"Stanford2013 - Kinetic model of yeast metabolic network (regulation)","description":"\n      \n        Stanford2013 - Kinetic model of yeast metabolic network (standard)\n                  Large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. This model is built with regulatory information.\n                \n                  This model is described in the article:\n                        Systematic construction of kinetic models from genome-scale metabolic networks.\n                    \n                Stanford NJ, Lubitz T, Smallbone K, Klipp E, Mendes P, Liebermeister W.\n                PLoS ONE 2013; 8(11): e79195\n                Abstract:\n                        The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.\n                    \n                \n                  This model is hosted on        BioModels Database\n            and identified\nby:        BIOMD0000000497\n            .        \n                To cite BioModels Database, please use:        BioModels Database: An enhanced, curated and annotated resource\nfor published quantitative kinetic models\n            .        \n                \n                  To the extent possible under law, all copyright and related or\nneighbouring rights to this encoded model have been dedicated to the public\ndomain worldwide. Please refer to        CC0 Public Domain\nDedication\n            for more information.        \n                \n            \n      \n    ","dates":{"last_modification":"2024-08-21","publication":"2024-09-02","submission":"2013-07-04"},"accession":"BIOMD0000000497","cross_references":{"eco":["ECO:0000033","ECO:0000034","ECO:0000035"],"pubmed":["24324546"],"chebi":["CHEBI:17588","CHEBI:16189","CHEBI:16551","CHEBI:15699","CHEBI:17191","CHEBI:18283","CHEBI:15603","CHEBI:18189","CHEBI:18019","CHEBI:28938","CHEBI:16027","CHEBI:16643","CHEBI:28102","CHEBI:17295","CHEBI:16567","CHEBI:17203","CHEBI:37671","CHEBI:30616","CHEBI:49258","CHEBI:16927","CHEBI:17719","CHEBI:17115","CHEBI:35121","CHEBI:17544","CHEBI:16857","CHEBI:18319","CHEBI:16828","CHEBI:17214","CHEBI:17516","CHEBI:17895","CHEBI:15638","CHEBI:16414","CHEBI:17672","CHEBI:16521","CHEBI:16526","CHEBI:15682","CHEBI:17239","CHEBI:18262","CHEBI:49072","CHEBI:15899","CHEBI:17962","CHEBI:15521","CHEBI:29748","CHEBI:17436","CHEBI:31014","CHEBI:16383","CHEBI:18059","CHEBI:36464","CHEBI:15441","CHEBI:16947","CHEBI:15531","CHEBI:28808","CHEBI:17361","CHEBI:49256","CHEBI:15346","CHEBI:52976","CHEBI:25168","CHEBI:37563","CHEBI:27402","CHEBI:17268","CHEBI:16292","CHEBI:27466","CHEBI:30807","CHEBI:35146","CHEBI:17108","CHEBI:15532","CHEBI:17805","CHEBI:18349","CHEBI:30864","CHEBI:16897","CHEBI:16543","CHEBI:15589","CHEBI:18272","CHEBI:16905","CHEBI:29112","CHEBI:15946","CHEBI:15919","CHEBI:18302","CHEBI:37522","CHEBI:52371","CHEBI:17634","CHEBI:16975","CHEBI:18277","CHEBI:16077","CHEBI:18299","CHEBI:35374","CHEBI:16878","CHEBI:16749","CHEBI:44337","CHEBI:17369","CHEBI:27391","CHEBI:32814","CHEBI:17363","CHEBI:15893","CHEBI:52961","CHEBI:16332","CHEBI:16174","CHEBI:15846","CHEBI:15637","CHEBI:16908","CHEBI:17713","CHEBI:18364","CHEBI:16284","CHEBI:18009","CHEBI:18297","CHEBI:15918","CHEBI:29114","CHEBI:16474","CHEBI:27689","CHEBI:52957","CHEBI:16288","CHEBI:28493","CHEBI:29123","CHEBI:15961","CHEBI:16444","CHEBI:28862","CHEBI:25646","CHEBI:16192","CHEBI:18413","CHEBI:15533","CHEBI:18035","CHEBI:50606","CHEBI:18257","CHEBI:35129","CHEBI:15633","CHEBI:30839","CHEBI:17275","CHEBI:18361","CHEBI:15842","CHEBI:7814","CHEBI:15809","CHEBI:16452","CHEBI:15753","CHEBI:16214","CHEBI:15379","CHEBI:16763","CHEBI:17013","CHEBI:29889","CHEBI:16810","CHEBI:28850","CHEBI:15525","CHEBI:17835","CHEBI:17622","CHEBI:43474","CHEBI:17407","CHEBI:16337","CHEBI:23929","CHEBI:17980","CHEBI:18303","CHEBI:18249","CHEBI:52332","CHEBI:36242","CHEBI:16933","CHEBI:15958","CHEBI:16426","CHEBI:52320","CHEBI:49183","CHEBI:50593","CHEBI:16236","CHEBI:16238","CHEBI:32364","CHEBI:16038","CHEBI:16630","CHEBI:17877","CHEBI:18021","CHEBI:17862","CHEBI:16057","CHEBI:35366","CHEBI:17038","CHEBI:29934","CHEBI:11814","CHEBI:50583","CHEBI:15361","CHEBI:15740","CHEBI:11851","CHEBI:29806","CHEBI:17015","CHEBI:52977","CHEBI:16680","CHEBI:17552","CHEBI:50571","CHEBI:15820","CHEBI:15414","CHEBI:15721","CHEBI:15491","CHEBI:17211","CHEBI:36208","CHEBI:28726","CHEBI:17138","CHEBI:17754","CHEBI:17794","CHEBI:15978","CHEBI:16566","CHEBI:16016","CHEBI:16001","CHEBI:15440","CHEBI:16108","CHEBI:17052","CHEBI:25629","CHEBI:15428","CHEBI:17813","CHEBI:15541","CHEBI:28087","CHEBI:17865","CHEBI:30031","CHEBI:36655","CHEBI:30407","CHEBI:15380","CHEBI:1949","CHEBI:17345","CHEBI:37565","CHEBI:50591","CHEBI:36457","CHEBI:17359","CHEBI:17709","CHEBI:15652","CHEBI:30904","CHEBI:52974","CHEBI:12071","CHEBI:18095","CHEBI:16240","CHEBI:20506","CHEBI:17855","CHEBI:16136","CHEBI:17659","CHEBI:17202","CHEBI:27735","CHEBI:28843","CHEBI:18066","CHEBI:53005","CHEBI:18406","CHEBI:16695","CHEBI:53004","CHEBI:28413","CHEBI:46398","CHEBI:16087","CHEBI:18247","CHEBI:18252","CHEBI:16584","CHEBI:18005","CHEBI:52388","CHEBI:15934","CHEBI:52615","CHEBI:18381","CHEBI:17082","CHEBI:52389","CHEBI:16977","CHEBI:18608","CHEBI:17917","CHEBI:52386","CHEBI:16257","CHEBI:16467","CHEBI:18191","CHEBI:17111","CHEBI:37737","CHEBI:15967","CHEBI:17196","CHEBI:20629","CHEBI:24636","CHEBI:29991","CHEBI:17601","CHEBI:13086","CHEBI:15377","CHEBI:18150","CHEBI:16349","CHEBI:17482","CHEBI:15343","CHEBI:17561","CHEBI:30089","CHEBI:17798","CHEBI:15345","CHEBI:29985","CHEBI:15351","CHEBI:17232","CHEBI:17984","CHEBI:18050","CHEBI:16335","CHEBI:15971","CHEBI:17985","CHEBI:16255","CHEBI:16761","CHEBI:16996","CHEBI:15954"],"biomodels__db":["MODEL1307040000","BIOMD0000000497"],"go":["GO:0008152","GO:1901576","GO:0005622","GO:0005576"],"taxonomy":["4932"]}}