Uncovering Cellular Dynamics and Metabolism with Geometric Deep Learning and Optimal Transport

Explore cutting-edge techniques in geometric deep learning and optimal transport for uncovering cellular dynamics and metabolism in this 27-minute conference talk from the Computational Genomics Summer Institute (CGSI) 2024. Delve into the latest research presented by Smita Krishnaswamy, focusing on innovative approaches to analyze and interpret complex biological data. Gain insights into the application of latent ordinary differential equations for irregularly sampled time series and other advanced computational methods in genomics. Examine the intersection of machine learning and computational biology through related papers, including work on geometric deep learning and optimal transport in cellular analysis. Enhance your understanding of how these sophisticated mathematical and computational tools are revolutionizing our ability to study and comprehend cellular processes and metabolic pathways.