Stochastic cell migration modulates exposure to signals that regulate commitment in the nephron progenitor niche.

An analysis of influenza viruses from naturally infected people suggests a tight transmission bottleneck and little positive selection within hosts.

The complex process of protein translocation across membranes has been dissected into multiple key steps and the distributions of translocation rates indicate stochastic nature of the reaction.

A reanalysis of the stochastic model of organelle production (Mukherji and O'Shea, 2014) suggests that this model requires significant further discussion.

How gene expression noise is regulated is critical for cell fate and tissue patterning.

Fluctuations in the availability of particles for binding can completely jeopardize yield in heterogeneous self-assembly.

A combined experimental and modeling approach provides insight into potential biases when inferring transcription rates from static mRNA distributions, and shows that correcting for cell-cycle phase and post-transcriptional noise provides rates that agree with live-cell transcription measurements.

A systematic comparison of experimentally measured and theoretically predicted magnitudes of organelle abundance fluctuations suggests that budding yeast produces the maximum level of variability in organelle abundance that can be generated by organelle biogenesis pathways.

New modelling, statistics, and experiments show that cellular populations of mitochondrial DNA (mtDNA) evolve during development according to solvable stochastic dynamics involving binomial partitioning and random turnover, facilitating a predictive and quantitative theory of the mtDNA bottleneck.

An optimal wire and function trade-off emerges from noisy growth and stochastic retraction during Drosophila class I ventral posterior dendritic arborisation (c1vpda) dendrite development.