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A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances

Massimo Pisu, Alessandro Concas, Giacomo Cao
Computation biology and chemistry, Volume 55, page 1--13 - 2015
Cell cycle regulates proliferative cell capacity under normal or pathologic conditions, and in general it governs all in vivo/in vitro cell growth and proliferation processes. Mathematical simulation by means of reliable and predictive models represents an important tool to interpret experiment results, to facilitate the definition of the optimal operating conditions for in vitro cultivation, or to predict the effect of a specific drug in normal/pathologic mammalian cells. Along these lines, a novel model of cell cycle progression is proposed in this work. Specifically, it is based on a population balance (PB) approach that allows one to quantitatively describe cell cycle progression through the different phases experienced by each cell of the entire population during its own life. The transition between two consecutive cell cycle phases is simulated by taking advantage of the biochemical kinetic model developed by GĂ©rard and Goldbeter (2009) which involves cyclin-dependent kinases (CDKs) whose regulation is achieved through a variety of mechanisms that include association with cyclins and protein inhibitors, phosphorylation-dephosphorylation, and cyclin synthesis or degradation. This biochemical model properly describes the entire cell cycle of mammalian cells by maintaining a sufficient level of detail useful to identify check point for transition and to estimate phase duration required by PB. Specific examples are discussed to illustrate the ability of the proposed model to simulate the effect of drugs for in vitro trials of interest in oncology, regenerative medicine and tissue engineering.

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Références BibTex

@Article{PCC15,
  author       = {Pisu, M. and Concas, A. and Cao, G.},
  title        = {A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances},
  journal      = {Computation biology and chemistry},
  volume       = {55},
  pages        = {1--13},
  year         = {2015},
  keywords     = {cell cycle, computer simulation},
  doi          = {10.1016/j.compbiolchem.2015.01.002},
  url          = {http://publications.crs4.it/pubdocs/2015/PCC15},
}

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» Massimo Pisu
» Alessandro Concas
» Giacomo Cao