Skip to main content

Table 2 Performance comparison between the proposed and the competing methods based on the 7 fold cross validation test on the BT426 dataset

From: Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

Prediction method [reference]

Qtotal

Qpredicted

Qobserved

MCC

This paper

80.9

62.7

55.6

0.47

SVM [33]

79.8

55.6

68.9

0.47

MOLEBRNN [28]

77.9

53.9

66.0

0.45

SVM (multiple alignment) [32]

77.3

53.1

67.0

0.45

BTSVM [31]

78.7

56.0

62.0

0.45

BETATPRED2 (multiple alignment) [26, 27]

75.5

49.8

72.3

0.43

COUDES (ψthreshold = 0 for PSSM) [4]

74.8

48.8

69.9

0.42

COUDES (ψthreshold = -100 for PSSM) [4]

75.5

49.8

66.6

0.41

SVM (single sequence) [32]

74.8

49.1

67.9

0.41

BETATPRED2 (single sequence) [26, 27]

74.3

48.4

71.2

0.41

KNN [29]

75.0

46.5

66.7

0.40

BTPRED1 [25]

74.9

55.3

48.0

0.35

BTPRED [25, 35]

74.4

48.3

57.3

0.35

Chou-Fasman [10, 35]

65.2

37.6

63.5

0.26

Thornton [17, 35]

68.0

38.6

52.4

0.23

GORBTURN [18, 35]

70.5

39.3

37.3

0.19

1–4 & 2–3 correlation [19, 35]

59.1

32.4

61.9

0.17

Sequence coupled [20, 35]

53.3

32.4

72.8

0.17

  1. 1 Results reported on a different dataset with 300 chains.