Project 1 illustration

Linking gene expression to neuron function

We are developing machine learning methods to map the relationship between cell type-specific gene expression and phenotypic features of neuron function, including neuron electrophysiology and morphology.
Relevant publications: here and here
Project 2 illustration

Studying the diversity and function of human cortical neurons

Working with experimental colleagues in the Valiante Lab at the Krembil Research Institute, we are investigating the electrophysiological function of human cortical neurons from tissue resected during routine neurosurgery. One goal of this work is to correlate variability in neuron function to an individual’s genetics and demographic features.
Relevant publications: here
Project 3 illustration

Using single-cell transcriptomics to understand brain disorders

Single-cell RNA-sequencing is revolutionizing our understanding of the cell types of the nervous system. In collaboration with a number of experimental colleagues, we are developing computational methods to use these technologies to understand how brain cells change in their proportion, gene expression, and electrophysiology due to neuropsychiatric and neurological conditions, including depression, aging, and Alzheimer's disease.
Relevant publications: here and here;
Project 4 illustration

Neuroinformatics for brain cell types

We build and contribute to online public databases on brain cell type diversity, including, and (in collaboration with the Pavlidis Lab at UBC).
Relevant publications: here and here; YouTube video for NeuroElectro: here
Project 5 illustration

Understanding how experimental methods impact neuron characterization

Because we analyze datasets collected by many different labs, we develop computational methods to help assess a dataset’s overall quality. This work includes understanding what factors contribute to high quality patch-seq data and how differences in ACSF and pipette solutions contribute to variable patch clamp data.
Relevant publications: here and here
Project 6 illustration

Using large-scale population cohorts to understand the interplay between genetics, the brain, and psychiatric illnesses

We have begun using datasets like the UK Biobank to better understand the multi-modal and multi-faceted aspects of psychiatric illness. We are using these datasets to pursue questions like: "How is depression defined into subtypes?" and "How do genetics and environmental influences, like poor sleep quality or cannabis use, interact to increase the risk of psychiatric disorders?".