Neutral tagging and detailed analysis of bacterial growth kinetics can quantify the mechanisms of colonization resistance in differently colonized animals.

Interactions in protein complexes can be predicted from evolutionary information from genomic sequences.

Marcks and Marcks-like 1 proteins are required for normal neurite formation and proliferation of neuro-glial progenitors during development and regeneration of the Xenopus spinal cord implicating these proteins as critical new factors for spinal cord development and regeneration.

Multiple independent directional selection events on a neural substrate that underpins domain-general associative abilities partly explains independent occurrences of complex behavior in different lineages of mammals.

A new machine learning method makes it possible to efficiently identify the parameters of cognitive models using Bayesian inference, even when only model simulations are available.

β-adrenergic receptors at the Golgi apparatus activate a local signaling pathway, not accessed by cell surface receptors, to drive cardiac hypertrophy and could represent a target for heart failure therapy.

Deep neural networks can be trained to automatically find mechanistic models which quantitatively agree with experimental data, providing new opportunities for building and visualizing interpretable models of neural dynamics.

Following exposure of Leishmania culture promastigotes to DNA stress, single-cell RNA sequencing reveals discrete clusters of cells associated with efficient generation of hybrids between different species and strains in vitro marked by expression of the ancestral gamete fusogen HAP2.

Circulating myeloid cells invade the brain during pancreatic cancer, where they accumulate at a unique central nervous system interface and drive anorexia and muscle catabolism.

During Kupffer's vesicle morphogenesis, cell volume anisotropy impacts cell shape changes.