Machine and deep learning methods for predicting 3D genome organization

arXiv:2403.03231v1 Announce Type: cross
Abstract: Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged …

abstract arxiv cellular cs.lg deep learning development domains gene genome interactions machine organization processes profiling q-bio.gn roles technologies three-dimensional type