T2N, a novel interface between Matlab, TREES toolbox and NEURON, was used to generate compartmental models that reproduce the electrophysiology of dentate granule cells over a multitude of species, experimental conditions and developmental stages.

A stochastic model of locomotory control in C. elegans based on an extensive new set of tracking data can explain and predict effects of ablations and mutations on behavior.

Whole-brain computational modelling, incorporating novel ML-based parameter estimation techniques, reveals how transcranial magnetic stimulation-evoked brain responses are driven at earlier timepoints by local echoes of the external stimulus, and at later timepoints by large-scale network reverberation across the connectome.

Mean kurtosis brain maps, derived from a sub-diffusion model with a novel clinically feasible two-diffusion-time acquisition, exhibit superior tissue contrast compared to the traditional diffusional kurtosis imaging (DKI).

Transcriptional activation domains achieve rapid, dynamic, specific interaction with Mediator through binding of an unstructured peptide to multiple hydrophobic surfaces without particular amino acid side chain interactions.

Integrated experimental-computational approaches were implemented to reveal the dynamic conformational landscape of a biologically relevant protein methyltransferase SETD8 for functional annotation.

Hierarchical modeling of internalizing symptoms and task performance reveals that difficulty adapting probabilistic learning to second-order uncertainty is common to anxiety and depression and holds across rewarding and punishing outcomes.

A mathematical model describes the function of dopaminergic neurons in both learning and action planning.