Fig. 1From: A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associationsROC and PR curves of different methods on Dataset1. In AUROC, VGAELDA (AUROCÂ =Â 0.9680) outperforms GAMCLDA (0.9299), SKFLDA (0.9154), TPGLDA (0.7936), SIMCLDA (0.8293) and LRLSLDA (0.8157). In AUPR, VGAELDA (AUPRÂ =Â 0.8380) outperforms GAMCLDA (0.5794), SKFLDA (0.4024), TPGLDA (0.5308), SIMCLDA (0.5357) and LRLSLDA (0.2035)Back to article page