Heterogeneous dual-channel and interpretable graph representation learning with global virtual nodes for microRNA-mediated drug sensitivity prediction.
Channel-gated global heterogeneous propagation is introduced, in which global virtual nodes first enable graph-level context exchange and a channel-wise propagation gate then recalibrates propagated embeddings to emphasize discriminative feature channels and suppress noisy or redundant ones.