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A top-down model-guided framework unveils the role of regulatory logics underlying gene regulatory networks in cell fate decisions.

Unsupervised machine learning on the ultrastructure and shape of cells in volume electron microscopy yields a compact representation of cellular morphology that complements genetics-based cell type characterisation.

A simple efficient coding model predicts complex trade-offs in resource allocation for sensory inputs with heterogeneous receptor densities and activation levels.

Single-cell transcriptomic analysis of developing retinal ganglion cells in mice suggests that their diversification into 45 discrete types occurs via the gradual restriction of multipotential precursors.

Computational evolutionary model to predict the efficacy of broadly neutralizing antibodies (bNAbs) in suppressing HIV and to design optimal combination therapy with bNAbs.

Biperiden, but not amisulpride, delays auditory mismatch responses during environmental stability, suggesting a differential sensitivity of auditory statistical learning to muscarinic versus dopaminergic receptor status which could prove useful for developing tests that predict an individual's response to antipsychotic treatment.

A theoretical model that considers the diversity of collateral effects among drug resistance mutations provides insights into the development of robust sequential antibiotic treatments.

The subjective value of choice options changes during deliberation, and accounting for these changes improves predictions of choices, response times, and BOLD fMRI activity.