{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Pdf":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.pdf"],"Svg":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.svg"],"Owl":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832-biopax2.owl","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832-biopax3.owl"],"Xml":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832_url.xml","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832_urn.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.xpp","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.sci","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.png","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.vcml","https://www.ebi.ac.uk/biomodels/model/download/MODEL6185746832?filename=MODEL6185746832.m"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"submitter":["Herbert Sauro"],"curationStatus":["Non-curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["L2V3"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/MODEL6185746832"],"publication_pubmed":["17907797"],"isPrivate":["false"],"repository":["BioModels"],"modelFormat":["SBML"],"omics_type":["Models"],"tokenised_name":["Qiao2007 MAPK Signaling Oscillatory"],"publication_year":["2007"],"submissionId":["MODEL6185746832"],"publication_authors":["Liang Qiao, Robert B Nachbar, Ioannis G Kevrekidis, Stanislav Y Shvartsman"],"first_author":["Liang Qiao"],"publication":["17907797,\n                            Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures. We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics.. 9, 3.\n                            Department of Chemical Engineering, Princeton University, Princeton, New Jersey, USA."],"submitter_mail":["hsauro@u.washington.edu"],"submitter_affiliation":["University of Washington"],"pubmed_abstract":["Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures. We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics."],"pubmed_title":["Bistability and oscillations in the Huang-Ferrell model of MAPK signaling."],"pubmed_authors":["Qiao Liang L, Nachbar Robert B RB, Kevrekidis Ioannis G IG, Shvartsman Stanislav Y SY"],"additional_accession":[]},"is_claimable":false,"name":"Qiao2007_MAPK_Signaling_Oscillatory","description":"\n      \n        This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). 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":"2011-07-04","publication":"2005-01-01","submission":"2009-03-25"},"accession":"MODEL6185746832","cross_references":{"pubmed":["17907797"],"biomodels__db":["MODEL6185746832"],"go":["GO:0000165"],"taxonomy":["2759"]}}