Approximations for Expected Generation Number

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 appro...

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Bibliographic Details
Published in:Biometrics 2007-12, Vol.63 (4), p.1023-1030
Main Authors: Cole, D.J, Ridout, M.S, Morgan, B.J.T, Byrne, L.J, Tuite, M.F
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Asymmetric cell division
Biometrics
Biometry - methods
Cell cycle
Cell Cycle - physiology
Cell division
Cell growth
Cell Proliferation
Cell reproduction
Cellular biology
Coefficients
Computer Simulation
Data Interpretation, Statistical
Daughter cells
Error rates
Exponential growth
Generation time
Mathematical expressions
Measurement techniques
Models, Biological
Models, Statistical
Mother cells
Renewal theory
Research methodology
Robust approximation
Saccharomyces cerevisiae
Saccharomyces cerevisiae - cytology
Saccharomyces cerevisiae - growth & development
Variation in generation time
Yeast cells
Yeasts
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Summary: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.
ISSN:0006-341X
1541-0420
DOI:10.1111/j.1541-0420.2007.00780.x