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.

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.

Long-lived tropical trees in Southeast Asia accumulate somatic mutations in a manner that is dependent on time, rather than growth rate.

A coarse-grained model of microbial growth coupling fluxes of carbon and energy shows that resource allocation is a major explanatory factor of the observed variability of growth rates and growth yields across different bacterial strains.

Time-lapse imaging and the modular recreation of host physiology reveal that alveolar epithelial cells, potential permissive infection sites for Mycobacterium tuberculosis, can restrict early bacterial growth via surfactant secretion.

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.

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.

Wings achieve plasticity in size while maintaining robust pattern via ecdysone, which elicits graded responses for growth rates and threshold responses for patterning rates, in the fruit fly Drosophila melanogaster.