BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=curation_notes.txthttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196.pdfhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=manifest.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196_url.sedmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196-matlab.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196.odehttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196-octave.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=curation_image.pnghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196.pnghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=BIOMD0000000196.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000196?filename=metadata.rdfprimaryOK200Harish DharuriManually curateddelayed differential equation modelL2V1https://www.ebi.ac.uk/biomodels/BIOMD000000019616473373falseBioModelsSBMLModelsSrividhya2006 CellCycle2006MODEL1502077979J Srividhya, M S GopinathanJ Srividhya16473373, We propose a seven variable model with time delay in one of the variables for the cell cycle in higher eukaryotes. The model consists of four important phosphorylation-dephosphorylation (P-D) cycles that govern the cell cycle, namely Pre-MPF-MPF, Cdc25P-Cdc25, Wee1P-Wee1 and APCP-APC. Other variables are cyclin, free cyclin dependent kinase (Cdk) and mass. The mass acts as a G2/M checkpoint and the checkpoint is represented by a saddle node loop bifurcation. The key feature of the model is that a time lag has been introduced in the activation of anaphase promoting complex (APC) by maturation promoting factor (MPF). This is effected by treating MPF as a time-delayed variable in the activation step of APC. The time lag acts as a spindle checkpoint. Absence of time delay induces a bistability in our model. Time delay also brings about variability in G1 phase timings. The model also reproduces the mutant phenotype experiments on wee1 cells. Stochasticity has been introduced in the model to simulate the dependence of the cycle time on cell birth length. Mutant phenotypes in the stochastic model reproduce the experimental observations better than the deterministic model.. 3, 241. Indiana University School of Informatics, Indiana University, Bloomington, IN 47406, USA. srividhya@iitm.ac.inhdharuri@cds.caltech.eduCalifornia Institute of TechnologyBIOMD0000000196We propose a seven variable model with time delay in one of the variables for the cell cycle in higher eukaryotes. The model consists of four important phosphorylation-dephosphorylation (P-D) cycles that govern the cell cycle, namely Pre-MPF-MPF, Cdc25P-Cdc25, Wee1P-Wee1 and APCP-APC. Other variables are cyclin, free cyclin dependent kinase (Cdk) and mass. The mass acts as a G2/M checkpoint and the checkpoint is represented by a saddle node loop bifurcation. The key feature of the model is that a time lag has been introduced in the activation of anaphase promoting complex (APC) by maturation promoting factor (MPF). This is effected by treating MPF as a time-delayed variable in the activation step of APC. The time lag acts as a spindle checkpoint. Absence of time delay induces a bistability in our model. Time delay also brings about variability in G1 phase timings. The model also reproduces the mutant phenotype experiments on wee1 cells. Stochasticity has been introduced in the model to simulate the dependence of the cycle time on cell birth length. Mutant phenotypes in the stochastic model reproduce the experimental observations better than the deterministic model.We consider a model for a network of phosphorylation-dephosphorylation cycles coupled through forward and backward regulatory interactions, such that a protein phosphorylated in a given cycle activates the phosphorylation of a protein by a kinase in the next cycle as well as the dephosphorylation of a protein by a phosphatase in a preceding cycle. The network is cyclically organized in such a way that the protein phosphorylated in the last cycle activates the kinase in the first cycle. We study the dynamics of the network in the presence of both forward and backward coupling, in conditions where a threshold exists in each cycle in the amount of protein phosphorylated as a function of the ratio of kinase to phosphatase maximum rates. We show that this system can display sustained (limit-cycle) oscillations in which each cycle in the pathway is successively turned on and off, in a sequence resembling the fall of a series of dominoes. The model thus provides an example of a biochemical system displaying the dynamics of dominoes and clocks (Murray & Kirschner, 1989). It also shows that a continuum of clock waveforms exists of which the fall of dominoes represents a limit. When the cycles in the network are linked through only forward (positive) coupling, bistability is observed, while in the presence of only backward (negative) coupling, the system can display multistability or oscillations, depending on the number of cycles in the network. Inhibition or activation of any kinase or phosphatase in the network immediately stops the oscillations by bringing the system into a stable steady state; oscillations resume when the initial value of the kinase or phosphatase rate is restored. The progression of the system on the limit cycle can thus be temporarily halted as long as an inhibitor is present, much as when a domino is held in place. These results suggest that the eukaryotic cell cycle, governed by a network of phosphorylation-dephosphorylation reactions in which the negative control of cyclin-dependent kinases plays a prominent role, behaves as a limit-cycle oscillator impeded in the presence of inhibitors. We contrast the case where the sequence of domino-like transitions constitutes the clock with the case where the sequence of transitions is passively coupled to a biochemical oscillator operating as an independent clock.A simple time delay model for eukaryotic cell cycle.A model for a network of phosphorylation-dephosphorylation cycles displaying the dynamics of dominoes and clocks.Srividhya J J, Gopinathan M S MSGonze D D, Goldbeter A AfalseSrividhya2006_CellCycle In this model the values of "free CDK" (Id: x2), "cdc25_P" (x4) "Wee1_P" (Id: y5) and "APC" (Id: y6) are assigned using the parameters describing the total concentrations totcdk (Id: c)), totcdc5, totwee1 and totAPC. So if you want to change the levels of these proteins, you need to change the values ofthese parameters. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team. For more information see the terms of use. To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691. 2024-08-212024-09-022008-10-21BIOMD0000000196REACT_152REACT_6216.2REACT_6914.2REACT_6255.1REACT_6178.2REACT_2119.3REACT_1944.21647337311371173MAMO:0000089MODEL1502077979BIOMD0000000196GO:0022402GO:0005623GO:0016538GO:0004672GO:0031387GO:0005680GO:0000307GO:0010467GO:0008054GO:0016310GO:0016311GO:0016049GO:0051301C005622759P14635P06493P04821P30304P30291IPR015454