Csikasz-Nagy, Battogtokh, Chen, Novak, Tyson, 2006
This CellML model represents the budding yeast model taken from the original model code. This CellML model represents the budding yeast model taken from the original published paper. The model runs in both PCEnv and COR but does not replicate the published results. This may be because of the cell division event which we are currently unable to express in CellML. The units have been checked and they are consistent.
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.
The original paper reference is cited below:
Analysis of a Generic Model of Eukaryotic Cell-Cycle Regulation, Attila Csikasz-Nagy, Dorjsuren Battogtokh, Katherine C. Chen, Bela Novak, and John J. Tyson, 2006, Biophysical Journal, 90, 4361-4379. PubMed ID: 16581849