From: Predicting protein residue-residue contacts using random forests and deep networks
Method | Top 10 | L/10 | L/5 |
---|---|---|---|
CONSIP2 (94) | 88.01% | 82.35% | 76.21% |
RaptorX-Contact (94) | 80.96% | 78.93% | 73.89% |
rf_full (78) | 78.59% | 73.15% | 66.05% |
MULTICOM-NOVEL (94) | 78.52% | 75.60% | 74.03% |
rf_select (78) | 74.74% | 69.23% | 63.14% |
PLCT (91) | 71.17% | 72.42% | 72.54% |
sda_Ensemble (78) | 68.21% | 63.92% | 59.56% |
sda_unbalanced (78) | 62.52% | 61.87% | 61.90% |
sda_balanced (78) | 61.67% | 57.52% | 53.51% |
svm (78) | 59.23% | 57.88% | 56.81% |
IASL-COPE (91) | 47.46% | 45.43% | 45.36% |
Pcons-net (87) | 45.83% | 44.11% | 43.88% |
raghavagps-paaint (76) | 34.47% | 35.89% | 35.43% |
DCA (88) | 31.46% | 27.34% | 25.51% |
FoDTcm (32) | 19.06% | 21.50% | 22.34% |
MLiD (94) | N/A | N/A | N/A |