title: Approximations for expected generation number.
abstract: A deterministic formula is commonly used to approximate the expected generation number of a population of growing cells. However, this can give misleading results because it does not allow for natural variation in the times that individual cells take to reproduce. Here we present more accurate approximations for both symmetric and asymmetric cell division. Based on the first two moments of the generation time distribution, these approximations are also robust. We illustrate the improved approximations using data that arise from monitoring individual yeast cells under a microscope and also demonstrate how the approximations can be used when such detailed data are not available.
authors.affiliation: Institute of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, Kent CT2 7NF, UK. D.J.Cole@kent.ac.uk
authors.forename: D J
authors.initials: DJ
authors.lastname: Cole
authors.forename: M S
authors.initials: MS
authors.lastname: Ridout
authors.forename: B J T
authors.initials: BJ
authors.lastname: Morgan
authors.forename: L J
authors.initials: LJ
authors.lastname: Byrne
authors.forename: M F
authors.initials: MF
authors.lastname: Tuite
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D002453:Cell Cycle / Q000502:physiology*; D049109:Cell Proliferation; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D008954:Models, Biological; D015233:Models, Statistical; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000254:growth & development*