Table 4.
AUC of the functional similarity measures for three GOs using BMA in the PPI task on human dataset (IEA+ and IEA-)
| Methods | BP_IEA+ | BP_IEA- | CC_IEA+ | CC_IEA- | MF_IEA+ | MF_IEA- |
|---|---|---|---|---|---|---|
| simUI | 0.8747 | 0.8684 | 0.7803 | 0.7579 | 0.7125 | 0.6752 |
| Teng | 0.8916 | 0.8896 | 0.7856 | 0.7662 | 0.8089 | 0.7731 |
| simGIC | 0.9027 | 0.8959 | 0.8026 | 0.7796 | 0.7863 | 0.7531 |
| Wang | 0.9180 | 0.9088 | 0.8281 | 0.8231 | 0.8150 | 0.7670 |
| Resnik | 0.9404 | 0.9291 | 0.8537 | 0.8091 | 0.8682 | 0.8150 |
| JC | 0.8716 | 0.8828 | 0.7522 | 0.7968 | 0.7610 | 0.7601 |
| Lin | 0.9260 | 0.9172 | 0.8129 | 0.8151 | 0.8241 | 0.7772 |
| ResnikGrasm | 0.9249 | 0.9240 | 0.7991 | 0.7588 | 0.7963 | 0.8032 |
| WangWV | 0.8901 | 0.8905 | 0.8152 | 0.8189 | 0.8192 | 0.7673 |
| simRel | 0.9317 | 0.9306 | 0.8542 | 0.8291 | 0.8299 | 0.8178 |
| WIS | 0.9269 | 0.9300 | 0.8302 | 0.8110 | 0.8578 | 0.8463 |
The best results are in bold