Table 3 Comparison of H-SVM-LR with other β-turns prediction methods on the BT426 dataset.
From: Predicting beta-turns in proteins using support vector machines with fractional polynomials
Prediction method | Qtotal | Qpredicted | Qobserved | MCC |
|---|---|---|---|---|
H-SVM-LR | 82.87 | 64.83 | 70.66 | 0.56 |
Zheng and Kurgan [2] | 80.9 | 62.7 | 55.6 | 0.47 |
Liu et al. [20] | 80.9 | 63.6 | 49.2 | 0.44 |
Hu and Li [19] | 79.8 | 55.6 | 68.9 | 0.47 |
DEBT [21] | 79.2 | 54.8 | 70.1 | 0.48 |
BTSVM [17] | 78.7 | 56.0 | 62.0 | 0.45 |
NetTurnP [1] | 78.2 | 54.4 | 75.6 | 0.50 |
MOLEBRNN [15] | 77.9 | 53.9 | 66.0 | 0.45 |
Zhang et al.(multiple alignment) [18] | 77.3 | 53.1 | 67.0 | 0.45 |
BetaTPred2 [14] | 75.5 | 49.8 | 72.3 | 0.43 |
Kim [16] | 75.0 | 46.5 | 66.7 | 0.40 |
COUDES [9] | 74.8 | 48.8 | 69.9 | 0.42 |
BTPRED [13] | 74.4 | 48.3 | 57.3 | 0.35 |