Srividya Iyer-Biswas

TL;DR: The experimental and theoretical analysis reveals a simple physical principle governing these complex biological processes: a single temperature-dependent scale of cellular time governs the stochastic dynamics of growth and division in balanced growth conditions.

TL;DR: This work derives the exact time-dependent solution of the master equation for a transcriptional pulsing model of mRNA distributions and shows that, among others, bimodal and long-tailed (power-law) distributions occur in the steady state as the rate constants are varied over biologically significant time scales.

TL;DR: This model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next, and it is described how more complex reaction networks can reduce to such a cycle.

TL;DR: The Poisson representation is exploited to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise.

TL;DR: In this article, the authors derived exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division.