Dataset Information

Chen2004 - Cell Cycle Regulation

ABSTRACT: Chen2004 - Cell Cycle Regulation This is a hypothetical model of cell cycle that describes the molecular mechanism for regulating DNA synthesis, bud emergence, mitosis, and cell division in budding yeast. This model is described in the article: Integrative analysis of cell cycle control in budding yeast. Chen KC, Calzone L, Csikasz-Nagy A, Cross FR, Novak B, Tyson JJ Mol. Biol. Cell. [2004 Aug; Volume: 15 (Issue: 8 )] Page info: 3841-62 Abstract: The adaptive responses of a living cell to internal and external signals are controlled by networks of proteins whose interactions are so complex that the functional integration of the network cannot be comprehended by intuitive reasoning alone. Mathematical modeling, based on biochemical rate equations, provides a rigorous and reliable tool for unraveling the complexities of molecular regulatory networks. The budding yeast cell cycle is a challenging test case for this approach, because the control system is known in exquisite detail and its function is constrained by the phenotypic properties of >100 genetically engineered strains. We show that a mathematical model built on a consensus picture of this control system is largely successful in explaining the phenotypes of mutants described so far. A few inconsistencies between the model and experiments indicate aspects of the mechanism that require revision. In addition, the model allows one to frame and critique hypotheses about how the division cycle is regulated in wild-type and mutant cells, to predict the phenotypes of new mutant combinations, and to estimate the effective values of biochemical rate constants that are difficult to measure directly in vivo. The model reproduces the time profiles of the different species in Figure 2 of the paper. The figure depicts the cycle of a daughter cell. Since the Mass Doubling Time (MDT) is 90 minutes, time t=90 from the model simulation will correspond to time t=0 in the paper. The model was successfully tested using MathSBML and SBML odeSolver. To create a valid SBML file, a local parameter k=1 was added in the reaction 'Inactivation_274_CDC20'. Also, in order to annotate the protein and to have the interaction in the reaction graph to match figure 1 of the article, the reaction rate constants k_{mad2}, k_{bub2} and k_{lte1} are considered as species and renamed as MAD2, BUB2 and LTE1 in the model. This model is hosted on BioModels Database and identified by: BIOMD0000000056 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . 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 for more information.

SUBMITTER: Nicolas Le Novère

PROVIDER: BIOMD0000000056 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000056?filename=BIOMD0000000056-biopax2.owl	Owl
	BIOMD0000000056?filename=BIOMD0000000056-biopax3.owl	Owl
	BIOMD0000000056?filename=BIOMD0000000056-matlab.m	Other
	BIOMD0000000056?filename=BIOMD0000000056.m	Other
	BIOMD0000000056?filename=BIOMD0000000056.ode	Other

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Publications

Integrative analysis of cell cycle control in budding yeast.

Chen Katherine C KC Calzone Laurence L Csikasz-Nagy Attila A Cross Frederick R FR Novak Bela B Tyson John J JJ

Molecular biology of the cell 20040528 8

The adaptive responses of a living cell to internal and external signals are controlled by networks of proteins whose interactions are so complex that the functional integration of the network cannot be comprehended by intuitive reasoning alone. Mathematical modeling, based on biochemical rate equations, provides a rigorous and reliable tool for unraveling the complexities of molecular regulatory networks. The budding yeast cell cycle is a challenging test case for this approach, because the con ...[more]

PMID: 15169868

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Project description:This model originates from the Cell Cycle Database . It is described in: Analysis of a generic model of eukaryotic cell-cycle regulation. Csikász-Nagy A , Battogtokh D , Chen KC , Novák B , Tyson JJ Biophys. J. [2006 Jun],90(12 ):4361-79 PMID: 16581849 Abstract: We propose a protein interaction network for the regulation of DNA synthesis and mitosis that emphasizes the universality of the regulatory system among eukaryotic cells. The idiosyncrasies of cell cycle regulation in particular organisms can be attributed, we claim, to specific settings of rate constants in the dynamic network of chemical reactions. The values of these rate constants are determined ultimately by the genetic makeup of an organism. To support these claims, we convert the reaction mechanism into a set of governing kinetic equations and provide parameter values (specific to budding yeast, fission yeast, frog eggs, and mammalian cells) that account for many curious features of cell cycle regulation in these organisms. Using one-parameter bifurcation diagrams, we show how overall cell growth drives progression through the cell cycle, how cell-size homeostasis can be achieved by two different strategies, and how mutations remodel bifurcation diagrams and create unusual cell-division phenotypes. The relation between gene dosage and phenotype can be summarized compactly in two-parameter bifurcation diagrams. Our approach provides a theoretical framework in which to understand both the universality and particularity of cell cycle regulation, and to construct, in modular fashion, increasingly complex models of the networks controlling cell growth and division. 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 for more information. 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. 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.