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Efficient computation of stochastic cell-size transient dynamics

Acceso Abierto
ID Minciencias: ART-0000001817-77
Ranking: ART-ART_A1

Abstract:

How small, fast-growing bacteria ensure tight cell-size distributions remains elusive. High-throughput measurement techniques have propelled efforts to build modeling tools that help to shed light on the relationships between cell size, growth and cycle progression. Most proposed models describe cell division as a discrete map between size at birth and size at division with stochastic fluctuations assumed. However, such models underestimate the role of cell size transient dynamics by excluding them.We propose an efficient approach for estimation of cell size transient dynamics. Our technique approximates the transient size distribution and statistical moment dynamics of exponential growing cells following an adder strategy with arbitrary precision.We approximate, up to arbitrary precision, the distribution of division times and size across time for the adder strategy in rod-shaped bacteria cells. Our approach is able to compute statistical moments like mean size and its variance from such distributions efficiently, showing close match with numerical simulations. Additionally, we observed that these distributions have periodic properties. Our approach further might shed light on the mechanisms behind gene product homeostasis.

Tópico:

Gene Regulatory Network Analysis

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Citations: 19
19

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Información de la Fuente:

SCImago Journal & Country Rank
FuenteBMC Bioinformatics
Cuartil año de publicaciónNo disponible
Volumen20
IssueS23
Páginas1 - 6
pISSNNo disponible
ISSNNo disponible

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