<HashMap><database>BioModels</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Txt>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=curation_notes.txt</Txt><Pdf>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.pdf</Pdf><Svg>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.svg</Svg><Owl>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100-biopax3.owl</Owl><Owl>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100-biopax2.owl</Owl><Xml>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=manifest.xml</Xml><Xml>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100_url.xml</Xml><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100-octave.m</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100-matlab.m</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=metadata.rdf</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.png</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.ode</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.vcml</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100_url.sedml</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=curation_image.jpeg</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000100?filename=BIOMD0000000100.m</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><submitter>Harish Dharuri</submitter><curationStatus>Manually curated</curationStatus><modellingApproach>ordinary differential equation model</modellingApproach><levelVersion>L2V1</levelVersion><full_dataset_link>https://www.ebi.ac.uk/biomodels/BIOMD0000000100</full_dataset_link><publication_pubmed>14556891</publication_pubmed><isPrivate>false</isPrivate><repository>BioModels</repository><modelFormat>SBML</modelFormat><omics_type>Models</omics_type><tokenised_name>Rozi2003 GlycogenPhosphorylase Activation</tokenised_name><publication_year>2003</publication_year><submissionId>MODEL4589754842</submissionId><publication_authors>Anvar Rozi, Ya Jia</publication_authors><first_author>Anvar Rozi</first_author><publication>14556891,
                            Taking into account the Ca(2+)-stimulated degradation of inositol 1,4,5-trisphosphate (IP(3)) by a 3-kinase, we have theoretically explored the effects of both simple and complex Ca(2+) oscillations on the regulation of a phosphorylation-dephosphorylation cycle process involved in glycogen degradation by glycogen phosphorylase a-form, respectively. For the case of simple Ca(2+) oscillations, the roles of cytosolic Ca(2+) oscillations in the regulation of active phosphorylase depend upon the maximum rate of IP(3) degradation by the 3-kinase, V(M5). In particular, the smaller the values of V(M5) are, the lower the effective Ca(2+) threshold for the activation of glycogen phosphorylase will be. For the case of complex Ca(2+) oscillations, the average level of fraction of active phosphorylase is nearly independent from the level of stimulation increasing in the bursting oscillatory domain. Both simple and complex Ca(2+) oscillations can contribute to increase the efficiency and specificity of cellular signalling, and some theoretical results of activation of glycogen phosphorylase regulated by Ca(2+) oscillations are close to the experimental results for gene expression in lymphocytes.. 3, 106.
                            Department of Physics, Central China Normal University, Wuhan 430079, Hubei, PR China.</publication><submitter_mail>hdharuri@cds.caltech.edu</submitter_mail><submitter_affiliation>California Institute of Technology</submitter_affiliation><publicationId>BIOMD0000000100</publicationId><pubmed_abstract>We investigate the various types of complex Ca2+ oscillations which can arise in a model based on the mechanism of Ca2+-induced Ca2+ release (CICR), that takes into account the Ca2+-stimulated degradation of inositol 1,4,5-trisphosphate (InsP3) by a 3-kinase. This model was previously proposed in the course of an investigation of plausible mechanisms capable of generating complex Ca2+ oscillations. Besides simple periodic behavior, this model for cytosolic Ca2+ oscillations in nonexcitable cells shows complex oscillatory phenomena like bursting or chaos. We show that the model also admits a coexistence between two stable regimes of sustained oscillations (birhythmicity). The occurrence of these various modes of oscillatory behavior is analysed by means of bifurcation diagrams. Complex oscillations are characterized by means of Poincaré sections, power spectra and Lyapounov exponents. The results point to the role of self-modulation of the InsP3 signal by 3-kinase as a possible source for complex temporal patterns in Ca2+ signaling.</pubmed_abstract><pubmed_abstract>Cytosolic calcium plays a crucial role as a second messenger in cellular signalling. Various cell types, including hepatocytes, display Ca(2+)oscillations when stimulated by an extracellular signal. However, the biological relevance of this temporal organization remains unclear. In this paper, we investigate theoretically the effect of Ca(2+)oscillations on a particular example of cell regulation: the phosphorylation-dephosphorylation cycle controlling the activation of glycogen phosphorylase in hepatocytes. By modelling periodic sinusoidal variations in the intracellular Ca(2+)concentration, we show that Ca(2+)oscillations reduce the threshold for the activation of the enzyme. Furthermore, as the activation of a given enzyme depends on the kinetics of its phosphorylation-dephosphorylation cycle, specificity can be encoded by the oscillation frequency. Finally, using a model for signal-induced Ca(2+)oscillations based on Ca(2+)-induced Ca(2+)release, we show that realistic Ca(2+)oscillations can potentiate the response to a hormonal stimulation. These results indicate that Ca(2+)oscillations in hepatocytes could contribute to increase the efficiency and specificity of cellular signalling, as shown experimentally for gene expression in lymphocytes (Dolmetsch et al., 1998).</pubmed_abstract><pubmed_abstract>Taking into account the Ca(2+)-stimulated degradation of inositol 1,4,5-trisphosphate (IP(3)) by a 3-kinase, we have theoretically explored the effects of both simple and complex Ca(2+) oscillations on the regulation of a phosphorylation-dephosphorylation cycle process involved in glycogen degradation by glycogen phosphorylase a-form, respectively. For the case of simple Ca(2+) oscillations, the roles of cytosolic Ca(2+) oscillations in the regulation of active phosphorylase depend upon the maximum rate of IP(3) degradation by the 3-kinase, V(M5). In particular, the smaller the values of V(M5) are, the lower the effective Ca(2+) threshold for the activation of glycogen phosphorylase will be. For the case of complex Ca(2+) oscillations, the average level of fraction of active phosphorylase is nearly independent from the level of stimulation increasing in the bursting oscillatory domain. Both simple and complex Ca(2+) oscillations can contribute to increase the efficiency and specificity of cellular signalling, and some theoretical results of activation of glycogen phosphorylase regulated by Ca(2+) oscillations are close to the experimental results for gene expression in lymphocytes.</pubmed_abstract><pubmed_title>A theoretical study of effects of cytosolic Ca2+ oscillations on activation of glycogen phosphorylase.</pubmed_title><pubmed_title>Bursting, chaos and birhythmicity originating from self-modulation of the inositol 1,4,5-trisphosphate signal in a model for intracellular Ca2+ oscillations.</pubmed_title><pubmed_title>Activation of the liver glycogen phosphorylase by Ca(2+)oscillations: a theoretical study.</pubmed_title><pubmed_authors>Gall D D, Baus E E, Dupont G G</pubmed_authors><pubmed_authors>Rozi Anvar A, Jia Ya Y</pubmed_authors><pubmed_authors>Houart G G, Dupont G G, Goldbeter A A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Rozi2003_GlycogenPhosphorylase_Activation</name><description>
      
        The model reproduces the temporal evolution of Glycogen phosphorylase for a vale of Vm5=30 as depicted in Fig 1a of the paper. The model makes use of calcium oscillations from the Borghans model to stimulate the activation of glycogen phosphorylase. Hence, this is a simple extension of the Borghans model. The model was succesfully tested on MathSBML and Jarnac.
            
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            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.
                
            
      
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