Neural Optimal Transport for Inferring Single-Cell Responses to Perturbations

Explore cutting-edge approaches to predicting single-cell responses to perturbations in this comprehensive lecture and primer from the Broad Institute. Delve into the world of neural optimal transport methods for modeling cellular changes, presented by Charlotte Bunne from ETH Zurich. Learn how these advanced deep learning techniques achieve state-of-the-art results in predicting treatment responses at the single-cell level, with applications in large-scale clinical studies. Discover the analytical challenges and opportunities in studying cell state transitions using single-cell genomics, presented by Oana Ursu from Genentech. Gain insights into key questions in the field, including quantifying perturbation effects, predicting combinatorial perturbations, and modeling cell population responses. Understand how computational advances synergize with experimental techniques to provide high-resolution insights into cell states across multiple modalities, time, and space.