High-Throughput In Silico Genetic Screen for 3D Genome Organization - Models, Inference and Algorithms

Explore cutting-edge research in genome organization through two insightful talks. Discover the power of in silico genetic screening for uncovering 3D genome organization regulators as Bo Xia presents the C.Origami deep neural network, enabling high-throughput computational modeling of chromatin organization in leukemia and T cells. Then, delve into the world of graph representation learning with Ruochi Zhang, who introduces innovative algorithms like Hyper-SAGNN and Higashi for analyzing multiscale 3D genome organization and single-cell Hi-C data. Learn how these advanced methods reveal cell-to-cell variability in chromatin structure and its connection to gene regulation in complex brain tissues, paving the way for next-generation single-cell 3D epigenome studies.

Meeting : High-throughput in silico genetic screen for discovering novel 3D genome organization regulation
Primer : Charting the Landscape of 3D Genome Organization with Graph Representation Learning