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Analysis of a stochastic model for bacterial growth and the lognormality of the cell-size distribution

Published 11 May 2016 in physics.bio-ph, cond-mat.stat-mech, and physics.data-an | (1605.03901v2)

Abstract: This paper theoretically analyzes a phenomenological stochastic model for bacterial growth. This model comprises cell division and the linear growth of cells, where growth rates and cell cycles are drawn from lognormal distributions. We find that the cell size is expressed as a sum of independent lognormal variables. We show numerically that the quality of the lognormal approximation greatly depends on the distributions of the growth rate and cell cycle. Furthermore, we show that actual parameters of the growth rate and cell cycle take values that give a good lognormal approximation; thus, the experimental cell-size distribution is in good agreement with a lognormal distribution.

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