{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Pdf":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.pdf"],"Owl":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095-biopax2.owl","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095-biopax3.owl"],"Svg":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.svg"],"Xml":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=manifest.xml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095_url.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.ode","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095-octave.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095-matlab.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.vcml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095.png","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=BIOMD0000000095_url.sedml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000095?filename=metadata.rdf"]},"type":"primary"},"statusCodeValue":200,"statusCode":"OK"}],"scores":null,"additional":{"submitter":["Molecular Systems Biology"],"curationStatus":["Manually curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["L2V1"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/BIOMD0000000095"],"publication_pubmed":["17102803"],"isPrivate":["false"],"repository":["BioModels"],"non_derived_xrefs":["BIOMD0000000055 biomodels.db"],"omics_type":["Models"],"modelFormat":["SBML"],"tokenised_name":["Zeilinger2006 PRR7 PRR9 Y"],"publication_year":["2006"],"submissionId":["MODEL4025663985"],"first_author":["Melanie N Zeilinger"],"publication_authors":["Melanie N Zeilinger, Eva M Farré, Stephanie R Taylor, Steve A Kay, Francis J Doyle"],"publication":["17102803,\n                            In plants, as in animals, the core mechanism to retain rhythmic gene expression relies on the interaction of multiple feedback loops. In recent years, molecular genetic techniques have revealed a complex network of clock components in Arabidopsis. To gain insight into the dynamics of these interactions, new components need to be integrated into the mathematical model of the plant clock. Our approach accelerates the iterative process of model identification, to incorporate new components, and to systematically test different proposed structural hypotheses. Recent studies indicate that the pseudo-response regulators PRR7 and PRR9 play a key role in the core clock of Arabidopsis. We incorporate PRR7 and PRR9 into an existing model involving the transcription factors TIMING OF CAB (TOC1), LATE ELONGATED HYPOCOTYL (LHY) and CIRCADIAN CLOCK ASSOCIATED (CCA1). We propose candidate models based on experimental hypotheses and identify the computational models with the application of an optimization routine. Validation is accomplished through systematic analysis of various mutant phenotypes. We introduce and apply sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures.. null, 2.\n                            Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, USA."],"submitter_mail":["msbforum@embo.org"],"submitter_affiliation":["Nature Publishing Group"],"publicationId":["BIOMD0000000095"],"pubmed_abstract":["In plants, as in animals, the core mechanism to retain rhythmic gene expression relies on the interaction of multiple feedback loops. In recent years, molecular genetic techniques have revealed a complex network of clock components in Arabidopsis. To gain insight into the dynamics of these interactions, new components need to be integrated into the mathematical model of the plant clock. Our approach accelerates the iterative process of model identification, to incorporate new components, and to systematically test different proposed structural hypotheses. Recent studies indicate that the pseudo-response regulators PRR7 and PRR9 play a key role in the core clock of Arabidopsis. We incorporate PRR7 and PRR9 into an existing model involving the transcription factors TIMING OF CAB (TOC1), LATE ELONGATED HYPOCOTYL (LHY) and CIRCADIAN CLOCK ASSOCIATED (CCA1). We propose candidate models based on experimental hypotheses and identify the computational models with the application of an optimization routine. Validation is accomplished through systematic analysis of various mutant phenotypes. We introduce and apply sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures."],"pubmed_title":["A novel computational model of the circadian clock in Arabidopsis that incorporates PRR7 and PRR9."],"pubmed_authors":["Zeilinger Melanie N MN, Farré Eva M EM, Taylor Stephanie R SR, Kay Steve A SA, Doyle Francis J FJ"],"additional_accession":[]},"is_claimable":false,"name":"Zeilinger2006_PRR7-PRR9-Y","description":"\n      \n        The model reproduces the circadian charecteristics as given in Table 1 for the PRR7-PRR9-Y model. The model makes use of the event section to introduce light at 30 hours. The Zeitgeber (ZT) times for species shown in Table 1 can be reproduced by looking at the time it takes for species to reach peak values after the introduction of light. The model was successfully tested on MathSBML.\n            \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      \n    ","dates":{"last_modification":"2024-08-21","publication":"2024-09-02","submission":"2007-03-13"},"accession":"BIOMD0000000095","cross_references":{"kegg__pathway":["ath04710"],"pubmed":["17102803"],"chebi":["CHEBI:33699"],"biomodels__db":["MODEL4025663985","BIOMD0000000095"],"go":["GO:0007623","GO:0005737","GO:0005634","GO:0005667","GO:0006351","GO:0009642","GO:0006402","GO:0006412","GO:0000060","GO:0065002","GO:0044257","GO:0045732"],"kegg__compound":["C00046"],"taxonomy":["3701"],"uniprot":["O81713","Q93WK5","Q8L500","Q9LKL2"],"interpro":["IPR010402"]}}