Fast protein structure comparison through effective representation learning with contrastive graph neural networks
Fig 2
Architecture of GNN-based encoder.
The BiLSTM module extracts low-level node features from the primary structures of proteins. The graph convolution module extracts high-level node features based on the adjacency matrices . The readout module transforms node features to the descriptors by a global max pooling layer. The residual blocks (ResBlock) used in the graph convolutional module consists of two graph convolutional (GC) layers.