Lei Huang

scCAFE is a deep learning model that detects multi-scale chromatin architectural features in single-cell Hi-C data, outperforming existing methods and enabling cell-type annotation from 3D genome features.

This study compares proteomics and transcriptomics for drug response prediction in cancer cell lines, finding proteomics provides better performance.

This paper introduces PMDM, a dual diffusion model for generating 3D bioactive molecules and optimizing leads for specific protein targets.

DeepMotifSyn synthesizes heterodimeric DNA motifs from monomeric pairs using deep learning, outperforming existing methods on CAP-SELEX data.