César Nieto

The paper infers cell division parameters in E. coli under nonsteady growth conditions using single-cell size trajectories and time-resolved models.

This study examines how C. glutamicum cells respond to pH stress by tracking cell size and survival, revealing stochastic and heritable differences in acid and alkaline stress survival.

This study shows insulators dynamically enhance enhancer-promoter coordination in Drosophila embryos through looping and coordination of transcriptional bursts.

The paper shows that Cdc13 accumulation is independent of cell growth rate but can be altered by nutrient-specific mechanisms in fission yeast.

This study shows that enhancer-promoter configurations in Drosophila embryos affect transcriptional dynamics, with downstream enhancer positioning reducing mRNA output by 70%.

The paper examines how bacterial cell volume changes over the growth curve in response to nutrient conditions using microscopy and mathematical modeling, finding non-monotonic dynamics in biomass-to-cell-number ratios.

The paper shows that noise in gene expression can differ between single-cell and population perspectives, with population-level noise being higher in some cases due to cell cycle dynamics and feedback loops.

This study identifies distinct growth and chaining properties in Clade 5 Clostridioides difficile strains using time-lapse microscopy, linked to the cmr switch sequence orientation.

The paper analyzes transcriptional bursting in Drosophila embryos to understand how spatial gene expression patterns are established despite variability in transcriptional activity.

The paper introduces a generalized adder mechanism for cell size homeostasis and shows how it affects clonal proliferation dynamics across different growth laws.

The paper combines mathematical modeling and experimental analysis to show that bacterial cell division is based on surface area, not size, leading to stable colony growth.

The paper investigates size regulation mechanisms in slow-growing E. coli cells, finding that different models explain size control under varying media conditions.

The paper analyzes optimal feedback strategies for reducing timing noise in biochemical events using stochastic models and shows that mixed feedback minimizes noise when degradation is present.

This study compares noise-attenuation mechanisms in gene expression through regulated synthesis and degradation, showing their distinct advantages in different noise regimes and population dynamics.

The paper analyzes how protein expression-growth coupling amplifies stochasticity in gene expression and quantifies the resulting noise and skewness in protein concentration.

This study investigates how stochasticity in bacterial division affects homeostasis, finding that noise in septum position and growth rate dampens oscillations in cell size dynamics.

The paper develops a framework to model cell size regulation and proliferation dynamics in single-cell-derived colonies, showing that fluctuations in cell number decrease over time in size-dependent models compared to size-independent models.

The paper develops a model to determine optimal regulatory strategies for achieving precise and minimal variability in protein threshold crossing times by analyzing feedback mechanisms and dilution effects.

PyEcoLib simulates E. coli stochastic size dynamics by modeling division as a jump process linked to cell size and continuous growth.

The paper analyzes bacterial cell size data to show that a commitment size model better explains both mean and fluctuation profiles than degradation-based models.

The paper analyzes how growth regimes and division strategies affect cell-size statistics in bacterial populations using deterministic and stochastic models.

This study shows division stochasticity can transmit to protein expression through chromosome replication, but only when replication is occurring.

The paper models bacterial cell size dynamics and protein production strategies to predict correlations between protein concentration and cell size.