ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction
Fig 9
Schematic diagram of the ASGCL model.
Module A utilizes a nonlinear subspace to extract cell line and drug features as primary characteristics; Module B, named GraphMorpher, adaptively sparsify the input graph structure; Module C is a contrastive learning module, which enhances the model’s discriminative ability by processing and comparing multiple graph structures.