eScreen: a deep learning framework for functionally decoding the regulatory genome at single-nucleotide resolution
Shijie Luo, Liquan Lin, Han Zhang, Yiding Yang, Yunxiang Liu, Yingli Han, Fei Chen, Ruipu Liang, Ximing Niang, Jinxian Dai, Run Chen, Hongli Lin, Zhijie Li, Yongying Peng, Fei Teng, Jialiang Huang
The paper introduces eScreen, a deep learning model that decodes regulatory genome function at single-nucleotide resolution using CRISPR screen data, achieving high accuracy and mechanistic interpretation.
bioRxiv · Feb 5, 2026 · PreprintGenomics