Table 1 Average performance of our algorithm on the CMI-20208, CMI-9589, and CMI-9905 datasets
From: DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions
Dataset | Specificity | Precision | Sensitivity | MCC | Accuracy | AUC | AUPR |
|---|---|---|---|---|---|---|---|
CMI-20208 | 0.9439 | 0.9294 | 0.7394 | 0.6981 | 0.8417 | 0.9546 | 0.9415 |
CMI-9589 | 0.9437 | 0.9318 | 0.7758 | 0.7297 | 0.8596 | 0.9610 | 0.9501 |
CMI-9905 | 0.9452 | 0.9352 | 0.7988 | 0.7521 | 0.8719 | 0.9645 | 0.9546 |
Average | 0.9443 | 0.9321 | 0.7713 | 0.7266 | 0.8577 | 0.9600 | 0.9487 |