Shreejoy Tripathy

Dr. Tripathy is an Independent Scientist at the Centre for Addiction and Mental Health and an Assistant Professor in the Department of Psychiatry at the University of Toronto. He did his Post-Doc at the University of British Columbia with Paul Pavlidis, where he worked on integrating neuron electrophysiology with cell type-specific gene expression. He received his PhD in Neural Computation from Carnegie Mellon University with Nathan Urban in 2013, on computational and neuroinformatics methods for studying the electrophysiological diversity of neurons throughout the brain. He received is BSc in Biomedical Engineering from Johns Hopkins University in 2008.

Research Synopsis

The goal of the Tripathy Lab (https://triplab.org) is to develop a multi-scale understanding of brain cell type diversity, bridging genetics and gene expression with cell and circuit physiology. The lab develops machine learning and statistical methods to help neuroscientists translate information at different levels of organization, like gene expression to neuron electrophysiology. The long-term goal of this work is to better understand the cellular changes that underlie psychiatric and neurological disorders and to ultimately develop approaches that can help guide tailored treatments for mental health patients. 
The lab is part of the new Krembil Centre for Neuroinformatics and contributes to the building of large-scale computational simulations of the nervous system. The lab is a computational “dry-lab”, but collaborates extensively with experimental groups in Toronto and beyond.

Recent Publications

Toker L, Mancarci BO, Tripathy SJ, Pavlidis P.  Transcriptomic evidence for alterations in astrocytes and parvalbumin interneurons in five cohorts of schizophrenia and bipolar subjects. Biological Psychiatry, December 2018.

Tripathy SJ, Toker L, Bomkamp C, Mancarci O, Belmadani M, Pavlidis P. Assessing transcriptome quality in patch-seq datasets. Frontiers in Cellular Neuroscience, October 2018.

Mancarci BO, Toker L, Tripathy SJ, Li B, Rocco B, Sibille E, Pavlidis P. Cross-laboratory analysis of brain cell type specific transcriptomes with applications to bulk tissue data. eNeuro, November 2017.

Tripathy SJ, Toker L, Li B, Crichlow CL, Tebaykin D, Mancarci O, Pavlidis P. Transcriptomic correlates of neuron electrophysiological diversity. PLoS Computational Biology, 13 (10), e1005814. October 2017.