Seminar by Dr. Sudin Bhattacharya titled Deep Generative Learning of Single Cell Gene Expression to predict Dose-Dependent Chemical Perturbations

The Centre for BioSystems Science and Engineering (BSSE) cordially invites you to attend a departmental seminar.

Speaker: Dr. Sudin Bhattacharya

Department of Biomedical Engineering, Department of Pharmacology and Toxicology

Institute for Quantitative Health Science & Engineering

Michigan State University

Abstract: 

Single cell RNA-sequencing allows us to study cell-type specificity and heterogeneity of biological responses to chemical perturbations. However, experimentally testing all relevant combinations of cell types, chemicals, and doses is a near-impossible task. A deep learning formalism called variational autoencoders (VAEs) has been shown to be effective in computationally predicting single-cell gene expression perturbations. We have developed single cell Variational Inference of Dose-Response (scVIDR), a VAE-based tool to predict the trajectory of cellular dose-response, which achieves better dose-response predictions than existing models. We show that scVIDR can predict dose-dependent gene expression changes across cell types and interpret the latent space of the autoencoder model in terms of biological pathways.