Effects of asymmetric division on a stochastic model of the cell division cycle
References (8)
- et al.
A stochastic model of cell division (with application to fission yeast)
Math. Biosci.
(1987) - et al.
Sloppy size control of the cell division cycle
J. Theoret. Biol.
(1986) A note on Koch and Schaechter's hypothesis about growth and fission of bacteria
J. Gen. Microbiol.
(1964)- et al.
Handbook of Mathematical Functions
(1965)
Cited by (16)
Theoretical study of mesoscopic stochastic mechanism and effects of finite size on cell cycle of fission yeast
2008, Physica A: Statistical Mechanics and its ApplicationsCitation Excerpt :In order to account for the experimental observations, many stochastic models have been proposed. The division asymmetry [8–10], the rate constant of the biochemical reaction [11], and the nuclear volume [12] are treated as stochastic variables and introduced into their mathematic models, respectively. For cellular or sub-cellular reaction systems, the internal noise must be considered due to the finite of system size.
Damage segregation at fissioning may increase growth rates: A superprocess model
2007, Theoretical Population BiologyCitation Excerpt :In contrast to the general selective advantage for reduced within-generation variability in the uncorrelated setting, the results of our analysis suggest that increased variability may be selectively favored when the phenotype is a shared resource. If the resource is simply size, then our model might be compared to the asymmetric-division cell cycle model developed by Tyson (1989). That work lacked an explicit stochastic population model, and did not address the question of overall population growth rate, but some of the observations from that paper may be relevant, most significantly the simple empirical fact of size asymmetry in yeast division.
A comprehensive continuous-time model for the appearance of CGH signal due to chromosomal missegregations during mitosis
2005, Mathematical BiosciencesCitation Excerpt :In contrast to the transition probability model, which expresses the probability of mitosis as a (fixed) function of time, the sloppy size model first proposed by Wheals [42] and then formalized by Tyson and Diekmann [43], expresses the probability of mitosis as a function of cell size (where ‘size’ can mean mass, volume, length, or some other measure of the cell). In later papers [47,58], which benefited from increased understanding of the molecular mechanisms of mitosis, size was modeled as the number of molecules of one or more proteins in the mitosis-associated CDC protein family. In sloppy size modeling, it is typical to scale cell sizes to lie in the interval (0, 1).
Effects of stochasticity in models of the cell cycle: From quantized cycle times to noise-induced oscillations
2004, Journal of Theoretical Biology