From: Predicting protein residue-residue contacts using random forests and deep networks
Method | Top 10 | L/10 | L/5 |
---|---|---|---|
CONSIP2 (94) | 71.71% | 70.18% | 67.30% |
RaptorX-Contact (94) | 61.60% | 56.80% | 55.63% |
rf_full (78) | 54.49% | 52.98% | 52.09% |
MLiD (94) | 53.51% | 49.98% | 46.99% |
svm (78) | 52.44% | 48.75% | 46.25% |
rf_select (78) | 50.77% | 50.05% | 48.66% |
DCA _cpp(88) | 47.07% | 44.10% | 40.82% |
sda_Ensemble (78) | 43.85% | 42.65% | 42.16% |
sda_unbalanced (78) | 37.91% | 38.81% | 37.78% |
IASL-COPE (91) | 37.58% | 34.87% | 33.70% |
sda_balanced (78) | 35.51% | 33.90% | 34.19% |
MULTICOM-NOVEL (94) | 27.97% | 27.25% | 27.12% |
raghavagps-paaint (76) | 26.50% | 26.37% | 26.68% |
Pcons-net (87) | 17.72% | 18.41% | 18.93% |
FoDTcm (32) | 17.71% | 17.45% | 18.10% |
PLCT (91) | 16.87% | 17.24% | 17.08% |