Table 4 The performances of the MQAPRank on 3DRobot dataset based on GDT_TS score
From: MQAPRank: improved global protein model quality assessment by learning-to-rank
Method | Method Type | Diff | MCC | AUC | Loss | mPCC | PCC |
|---|---|---|---|---|---|---|---|
MQAPRank | quasi-clustering | 0.68 | 0.98 | 0.99 | 0.80 | 0.99 | 0.99 |
RFMQA | single | 9.73 | 0.74 | 0.96 | 1.70 | 0.92 | 0.87 |
ModFOLDclust2 | clustering | 11.42 | 0.80 | 0.99 | 7.51 | 0.95 | 0.90 |
Pcons | clustering | 25.12 | 0.17 | 0.99 | 5.19 | 0.96 | 0.90 |