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Table 7 Ranges of the applicability score for the different combinations of ADE formulation, kernel and experiment

From: Estimation of the applicability domain of kernel-based machine learning models for virtual screening

ADE Kernel Target Training Set Screening Set
    Min Max Avg. Min Max Avg.
KDE OAK Thrombin 0.70 0.87 0.82 ± 0.04 0.51 0.77 0.64 ± 0.08
   Factor Xa 0.59 0.75 0.71 ± 0.02 0.47 0.72 0.60 ± 0.08
   PDGFRβ 0.81 0.88 0.85 ± 0.02 0.54 0.70 0.62 ± 0.05
  FlexOAK Thrombin 0.69 0.86 0.81 ± 0.04 0.54 0.79 0.66 ± 0.08
   Factor Xa 0.60 0.74 0.70 ± 0.02 0.53 0.69 0.61 ± 0.05
   PDGFRβ 0.80 0.88 0.85 ± 0.02 0.54 0.68 0.61 ± 0.04
  MARG Thrombin 0.81 0.95 0.92 ± 0.03 0.57 0.91 0.74 ± 0.11
   Factor Xa 0.74 0.94 0.91 ± 0.02 0.52 0.88 0.70 ± 0.11
   PDGFRβ 0.92 0.96 0.95 ± 0.01 0.74 0.91 0.82 ± 0.05
wKDE OAK Thrombin 0.70 0.87 0.82 ± 0.04 0.51 0.79 0.65 ± 0.09
   Factor Xa 0.59 0.76 0.71 ± 0.02 0.47 0.71 0.59 ± 0.07
   PDGFRβ 0.81 0.88 0.85 ± 0.02 0.54 0.70 0.62 ± 0.05
  FlexOAK Thrombin 0.69 0.87 0.82 ± 0.04 0.54 0.79 0.66 ± 0.08
   Factor Xa 0.60 0.74 0.71 ± 0.02 0.53 0.70 0.62 ± 0.05
   PDGFRβ 0.80 0.89 0.85 ± 0.02 0.54 0.68 0.61 ± 0.04
  MARG Thrombin 0.80 0.96 0.93 ± 0.04 0.56 0.93 0.75 ± 0.12
   Factor Xa 0.74 0.94 0.91 ± 0.02 0.52 0.87 0.69 ± 0.11
   PDGFRβ 0.91 0.97 0.95 ± 0.01 0.72 0.91 0.82 ± 0.06
One-Class OAK Thrombin -6.52 1.61 -0.33 ± 1.51 -15.70 -0.79 -8.25 ± 4.65
   Factor Xa -22.21 4.98 -0.90 ± 3.41 -55.36 -3.94 -29.65 ± 16.01
   PDGFRβ -1.14 0.92 0.0 ± 0.43 -17.08 -6.63 -11.86 ± 3.24
  FlexOAK Thrombin -5.62 1.35 -0.37 ± 2.07 -16.87 -2.42 -9.65 ± 4.50
   Factor Xa -20.2.0 3.52 -0.96 ± 2.96 -38.80 -3.68 -21.24 ± 10.94
   PDGFRβ -1.41 0.61 -0.12 ± 0.47 -17.01 -8.46 -12.74 ± 2.66
  MARG Thrombin -5.22 1.04 -0.35 ± 1.21 -20.82 -0.03 -10.42 ± 6.45
   Factor Xa -26.29 2.85 -0.77 ± 3.39 -27.55 0.00 -13.78 ± 8.55
   PDGFRβ -1.11 0.50 -0.01 ± 0.31 -9.56 -1.37 -5.47 ± 2.54