David C. Sterratt

The paper develops a unified deep non-linear mixed effects model for voltage-gated potassium channels, improving fit over existing models and enabling modeling of diverse channel types.

The paper fits and compares calcium-calmodulin kinetic models to a common dataset using non-linear mixed effects modelling, finding better fits and highlighting differences in activation patterns.

This paper identifies montelukast, an FDA-approved asthma drug, as a potential inhibitor of the Cav3.1 T-type calcium channel through computational simulations and suggests it may have therapeutic potential for neurological diseases.

The paper constructs a configurable synaptic proteome network model to analyze molecular mechanisms of disease co-morbidity by integrating proteomic and interaction data.

The paper quantifies developmental dynamics of retinocollicular projection ordering in mice and shows a combined activity-molecular model can capture segregation and convergence changes.

The paper maps proteins in biophysical models of synaptic plasticity, finding 4.2% of synaptic proteins are modelled and identifying gaps in disease-related proteins.