Machine Learning for Single-Cell 3D Epigenomics

Explore cutting-edge machine learning techniques for single-cell 3D epigenomics in this comprehensive lecture from the Computational Genomics Summer Institute. Delve into the latest research on 3D genome structure analysis at the single-cell level, presented by Jian Ma from Carnegie Mellon University. Examine key papers discussing annual reviews of 3D genome structure in single cells, multiscale and integrative single-cell Hi-C analysis using Higashi, and the development of Fast-Higashi for ultrafast and interpretable single-cell 3D genome analysis. Gain insights into advanced computational methods and their applications in understanding the complex three-dimensional organization of the genome within individual cells.