The BABY algorithm by estimating growth rates of individual cells from time-lapse microscopy images will help characterise the diversity in populations of budding cells, particularly differences in fitness.

Cells employ two strategies, adjusting both their cell cycle lengths and their growth rates in a size-dependent manner, to correct aberrations in cell size.

The growth environment driven ratio of ATP to growth rate, called absolute growth, determines the final population composition of Staphylococcus aureus and Pseudomonas aeruginosa when in co-culture.

Growth-delayed offspring generated from eggs that lacked normal epigenetic programming exhibited a remarkable capacity to undergo late gestational fetal growth recovery, despite inefficient placental function.

A unified framework for cell lineage statistics enables quantification of fitness landscapes and selection strength for any cellular lineage traits in a model-independent manner, and reveals the contributions of growth heterogeneity to population growth in diverse experimental model systems.

The fish gill, an ever-growing organ with fast turnover rate, displays dedicated stem-cell populations for growth and homeostasis that are interchangeable upon external challenges.

A mechanistic basis is provided for the regulative ability of the mammalian embryo offering a long-sought explanation for coordinating cell behaviors at the population level ensuring robustness in developmental outcome.

Global gene expression control mechanisms are modeled using a large dataset consisting of absolute-quantitative proteomics, transcriptomics, and partial metabolomics of Saccharomyces cerevisiae at a wide range of growth conditions.

Protein nutritional requirements decrease predictively with mass throughout ontogeny across the animal kingdom.

Single-cell data analysis must be guided by an underlying model.