Unraveling the three-dimensional genome structure using machine learning.

The study of chromatin interactions has advanced considerably with technologies such as high-throughput chromosome conformation capture (Hi-C) sequencing, providing a genome-wide view of physical interactions within the nucleus. These techniques have revealed the existence of hierarchical chromatin structures such as compartments, topologically associating domains (TADs), and chromatin loops, which are crucial in genome organization and regulation. However, identifying and analyzing these structural features require advanced computational methods.