Hao Chen

BRIDGE-GRN improves directed gene regulatory network inference from scRNA-seq data by using role-aware graph learning and cross-view contrastive regularization, achieving strong performance across multiple benchmarks.

SPSID denoises gene regulatory networks by distinguishing direct from indirect interactions, outperforming existing methods in simulations and benchmarks.

BiGAT-Fusion improves drug-disease association prediction by addressing class imbalance, directional asymmetry, and static feature fusion through a novel graph neural network model.