Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution
Yuan-Chen Sun, Wen-Jie Jiang, Kang-Wen Cai, Na-Na Wei, Fu-Ting Lai, Hao-Jie Wang, Rui-Xiang Gao, Ze-Yu Kuang, Jia-Lu Zhou, An Liu, Han-Wen Zhu, Yu-Juan Wang, Ming Xu, Hua-Jun Wu · 2026
Read Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution by Yuan-Chen Sun, Wen-Jie Jiang, Kang-Wen Cai, Na-Na Wei, Fu-Ting Lai, Hao-Jie Wang, Rui-Xiang Gao, Ze-Yu Kuang, Jia-Lu Zhou, An Liu, Han-Wen Zhu, Yu-Juan Wang, Ming Xu, Hua-Jun Wu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13250166.txt.
Description
Three-dimensional genome organization controls cell-type-specific gene expression through chromatin interactions, yet systematic analysis across diverse cellular contexts remains limited by experimental constraints. Here we present Hi-Compass, a depth-aware deep learning framework that predicts cell-type-specific chromatin organization using only chromatin accessibility data as cell-type-specific input.
Catalog record
| CREATOR | Yuan-Chen Sun, Wen-Jie Jiang, Kang-Wen Cai, Na-Na Wei, Fu-Ting Lai, Hao-Jie Wang, Rui-Xiang Gao, Ze-Yu Kuang, Jia-Lu Zhou, An Liu, Han-Wen Zhu, Yu-Juan Wang, Ming Xu, Hua-Jun Wu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 86 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |