Article

scHiCyclePred: a deep learning framework for predicting cell cycle phases from single-cell Hi-C data using multi-scale interaction information

2023-12-13

Abstract excerpt

While scRNA-seq offers gene expression snapshots, it misses the spatial context of chromatin organization crucial for cell cycle regulation. Single-cell Hi-C, capturing chromatin’s three-dimensional (3D) architecture, fills this void, revealing interactions between genomic regions that transcript-only data might overlook. We introduce scHiCyclePred, a model that utilizes single-cell Hi-C’s multi-scale interaction...

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Literature Corpus work: 530b6ad1-85ee-5765-95c2-d96fe478fdd2
DOI: 10.1101/2023.12.12.571388

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