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Jean-Benoît Lalanne is an Assistant Professor at the Université de Montréal, specializing in the quantitative study of gene regulation using various model systems. His research interests are broad, encompassing both prokaryotic and recently mammalian models. Despite his training in physics, he has extensive experience in genetics, molecular biology, and genomics. His lab focuses on developing high-throughput techniques to measure biological activities accurately, such as high-resolution RNA sequencing, ribosome profiling, and single-cell reporters. His primary goal is to develop genomic methods to generate large-scale datasets, particularly using multiplexed reporters, to train predictive sequence-function models for mammalian cis-regulatory elements, often referred to as enhancers. He is also interested in biophysically constrained and interpretable machine learning, as well as active learning for optimizing measurement designs. Lalanne's academic journey includes a postdoctoral fellowship in Genomics at the University of Washington and a PhD from MIT, along with master's and bachelor's degrees from McGill University. He has received several awards, including the Next-Generation Scientist Award from the Cancer Research Society.
Department of Pharmacology and Physiology - Research intensive with options in Neuropharmacology and Pharmacogenomics.