Table 1.
The statistics of datasets.
Fig 1.
The diagram of HGC-GAN.
Fig 2.
Node aggregation.
Fig 3.
K_mer.
Fig 4.
ROC curve under 10-fold cross-validation.
Fig 5.
P-R curves under 10-fold cross-validation.
Fig 6.
ROC curve under 5-fold cross-validation.
Fig 7.
P-R curves under 5-fold cross-validation.
Fig 8.
ROC curves of training and validation sets.
Fig 9.
P-R curves of training and validation sets.
Fig 10.
ROC curve for model comparison.
Fig 11.
P-R curves for model comparison.
Table 2.
AUC values for model comparison on dataset 3.
Table 3.
AUC values for model comparison on dataset 4.
Fig 12.
HGC-GAN AUC on different datasets.
Fig 13.
HGC-GAN AUPR on different datasets.
Fig 14.
Heatmap of the CASC9 sequence.
Fig 15.
Weighting of nucleotide fragments.
Fig 16.
Nucleotides in positive and negative contributions.
Fig 17.
Ablative study of HGC-GAN.
Fig 18.
Effect of different layers on the model.
Fig 19.
Effect of embedding size on the model.
Table 4.
Top 20 diseases associated with linc00152.
Table 5.
Top 20 lncRNAs associated with breast cancer.