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Table 7 DEBT's prediction of β-turn types on three different datasets.

From: Predicting β-turns and their types using predicted backbone dihedral angles and secondary structures

Dataset β-turn type MCC Sensitivity (%) Specificity (%) Q total (%) S(%) AUC
GR426 I 0.36 (0.31) 75.2 (67.5) 78.9 (78.4) 78.6 (77.9) 30.1 (26.2) 0.85 (0.82)
  II 0.29 (0.27) 63.4 (65.0) 88.3 (86.4) 87.4 (85.7) 23.1 (20.6) 0.87 (0.86)
  IV 0.27 (0.23) 71.2 (63.4) 71.5 (73.5) 71.5 (72.5) 20.4 (18.5) 0.78 (0.76)
  VIII 0.14 (0.10) 68.7 (29.1) 71.1 (89.8) 71.1 (88.1) 8.0 (7.7) 0.77 (0.73)
  NS 0.31 (0.28) 18.0 (19.8) 99.7 (99.4) 97.6 (97.4) 26.5 (26.1) 0.81 (0.81)
FA547 I 0.38 (0.31) 71.6 (66.6) 82.6 (79.5) 81.6 (78.3) 33.0 (26.0) 0.85 (0.82)
  II 0.33 (0.27) 63.0 (64.9) 90.8 (86.8) 89.8 (85.9) 27.8 (20.9) 0.88 (0.86)
  IV 0.27 (0.24) 69.8 (61.3) 73.3 (75.6) 73.0 (74.3) 21.0 (19.2) 0.79 (0.77)
  VIII 0.14 (0.10) 47.8 (28.4) 84.4 (90.2) 83.4 (88.5) 9.5 (7.9) 0.77 (0.73)
  NS 0.37 (0.28) 21.1 (21.2) 99.7 (99.2) 97.7 (97.2) 31.2 (26.3) 0.84 (0.82)
FA823 I 0.39 (0.30) 70.6 (64.3) 84.2 (80.7) 83.0 (79.3) 34.5 (26.0) 0.86 (0.82)
  II 0.33 (0.28) 62.7 (65.1) 91.2 (87.2) 90.2 (86.4) 27.9 (21.1) 0.88 (0.86)
  IV 0.27 (0.23) 68.3 (58.6) 74.4 (77.1) 73.9 (75.5) 21.0 (18.9) 0.79 (0.76)
  VIII 0.14 (0.08) 42.2 (12.4) 87.2 (96.6) 86.1 (94.5) 9.4 (7.3) 0.77 (0.72)
  NS 0.38 (0.29) 23.6 (24.2) 99.7 (98.9) 97.7 (97.0) 33.9 (27.9) 0.85 (0.83)
  1. In the parentheses is the prediction using PSSM-only input without predicted dihedral angles or secondary structure. Notably, there is improvement in the predictive performance when the input vector is augmented by predicted dihedral angles and secondary structures.