Fig. 10
From: Dual graph convolutional neural network for predicting chemical networks
Prediction performance for the metabolic reaction network. The performance is given in both ROC-AUC (left) and PR-AUC (right). The proposed method shows the limited performance for this extremely sparse network with the light-tailed degree distribution. Inter-compound links are almost useless as features, and therefore the domain specific features (i.e., Morgan indices) perform the best. The internal convolution also suffers from the lack of the links as the training data