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Table 2 Performance on disulfide connectivity prediction obtained with different SVR-based methods

From: Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations

# bonds

SVR

SVR+iCOV

SVR+MI

SVR+MI+iCOV

 

Pb = Rb

Qp

Pb = Rb

Qp

Pb = Rb

Qp

Pb = Rb

Qp

2

75

75

76

76

73

73

76

76

3

60

48

62.8

55.3

59.6

50.6

62.8

55.3

4

57

44

67.1

51.2

61

46.3

67.7

51.2

5

46

19

55.1

27

54.1

29.7

58.9

32.4

All

60

54

65.2

58.6

61.9

55.5

66.2

59.3

  1. # bonds: number of disulfide bonds; MIp: corrected Mutual Information; iCOV: sparse inverse COVariance estimation; SVR: Support Vector Regression; and their combinations as indicated. For details see Methods. Results are evaluated on the PDBCYS dataset [12]. SVR results are taken from [12]. For index definition see Performance measures.