Yue Wang

IAGRN: An Interleaved-Attention Graph Neural Network for Gene Regulatory Network Inference

A structure-aware interleaved-attention graph learning framework, termed IAGRN, is proposed for GRN inference from scRNA-seq data that interleaves topology-constrained local attention with distance-aware global attention, enabling effective integration of structural priors and long-range regulatory signals.