Breast luminal epithelial cells are the hotspots of aging-associated changes, which prime aged epithelia for oncogenic gene activation and may explain individual differences in breast cancer susceptibility due to the aging-associated increase in gene expression variances in luminal epithelia.

The effective higher-order binding cooperativities arising from an ensemble of dynamically interchanging conformations are identified and shown to fully describe integration of binding information at thermodynamic equilibrium.

Network symmetry represents a new vantage point for dissecting complex information processing characteristics in multisite modification, and the breaking of symmetry can confer ordering of modification and absolute concentration robustness.

Mutations that affect a metabolic network generically exhibit epistasis, which propagates to higher level phenotypes, such as fitness, carrying some information about the network’s topology.

With mathematical modeling being an important source of insight for microbial communities, we may need to move beyond commonly-used pairwise models that do not capture microbial interactions.

A multi-compartment spiking neural network model demonstrates that biologically feasible deep learning can be achieved if sensory inputs and higher-order feedback are received by different dendritic compartments.

A chemical probe was characterized for potency, selectivity, and ability to alter CARM1-dependent epigenetic plasticity against cancer cell invasion.