Open access
Aug 2026
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.
Yue Wang, Si-Cheng Tian, Dan Li
· International Journal of Mol... · 0 citations