Gilberto J Soler-Llavina

DRUG-seq provides high-throughput, unbiased transcriptomic data for drug discovery, demonstrating reproducibility and mechanism-of-action resolution for diverse compounds.

The paper describes an optimized Patch-seq technique for high-quality electrophysiological, morphological, and transcriptomic characterization of neurons, along with software tools for data acquisition and analysis.

The paper classifies neurons in mouse visual cortex into 17 electrophysiological and 35 morphological types using unsupervised methods and links them to transcriptomic types.

The paper develops a biophysically detailed in silico model of layer 4 of the mouse primary visual cortex, showing how functional synaptic connectivity reproduces experimental observations of neuronal responses to visual stimuli.