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Table 1 Cross-dataset classification performances.

From: Use B-factor related features for accurate classification between protein binding interfaces and crystal packing contacts

Training dataset

Feature

Tested datasets

  

BNCPCS

DC

Bahadur

Ponstingl

BNCPCS

ΣB

0.93(0.97)

0.32(0.65)

0.65(0.82)

0.82(0.91)

 

ΔASA

0.92(0.96)

-0.18(0.47)

0.59(0.78)

0.73(0.86)

 

avgΣB

0.92(0.96)

0.37(0.68)

0.64(0.82)

0.80(0.90)

 

avgNo.B

0.95(0.98)

0.25(0.60)

0.70(0.84)

0.84(0.92)

 

avgΣB*avgNo.B

0.94(0.97)

0.33(0.66)

0.70(0.85)

0.82(0.91)

 

avgΔASA

0.91(0.96)

-0.16(0.48)

0.64(0.81)

0.72(0.86)

DC

ΣB

0.85(0.92)

0.38(0.69)

0.68(0.85)

0.81(0.90)

 

ΔASA

0.73(0.86)

0.15(0.57)

0.66(0.84)

0.62(0.80)

 

avgΣB

0.88(0.94)

0.45(0.73)

0.73(0.87)

0.80(0.90)

 

avgNo.B

0.80(0.90)

0.46(0.72)

0.74(0.87)

0.70(0.84)

 

avgΣB*avgNo.B

0.86(0.93)

0.45(0.73)

0.75(0.88)

0.81(0.90)

 

avgΔASA

0.76(0.88)

0.27(0.63)

0.68(0.85)

0.66(0.82)

Bahadur

ΣB

0.84(0.92)

0.38(0.69)

0.71(0.86)

0.79(0.89)

 

ΔASA

0.73(0.86)

0.15(0.57)

0.66(0.84)

0.62(0.80)

 

avgΣB

0.84(0.92)

0.41(0.70)

0.75(0.88)

0.81(0.90)

 

avgNo.B

0.86(0.93)

0.33(0.66)

0.75(0.88)

0.77(0.88)

 

avgΣB*avgNo.B

0.88(0.94)

0.45(0.73)

0.77(0.89)

0.83(0.91)

 

avgΔASA

0.81(0.90)

0.21(0.60)

0.69(0.85)

0.69(0.84)

Ponstingl

ΣB

0.88(0.94)

0.39(0.70)

0.69(0.85)

0.81(0.90)

 

ΔASA

0.91(0.96)

-0.18(0.47)

0.59(0.79)

0.72(0.86)

 

avgΣB

0.90(0.95)

0.43(0.71)

0.73(0.87)

0.82(0.91)

 

avgNo.B

0.95(0.98)

0.25(0.60)

0.70(0.84)

0.84(0.92)

 

avgΣB*avgNo.B

0.90(0.95)

0.40(0.70)

0.75(0.88)

0.83(0.92)

 

avgΔASA

0.92(0.96)

-0.19(0.46)

0.65(0.82)

0.78(0.89)

PDBbind

ΣB

0.93(0.97)

0.38(0.68)

0.62(0.79)

0.72(0.86)

 

ΔASA

0.88(0.94)

-0.16(0.48)

0.49(0.68)

0.62(0.79)

 

avgΣB

0.88(0.94)

0.41(0.71)

0.71(0.86)

0.83(0.92)

 

avgNo.B

0.92(0.96)

0.38(0.68)

0.74(0.88)

0.80(0.90)

 

avgΣB*avgNo.B

0.90(0.95)

0.38(0.69)

0.76(0.88)

0.86(0.93)

 

avgΔASA

0.88(0.94)

0.02(0.51)

0.66(0.84)

0.70(0.85)

  1. X.XX(Y.YY) represent the classification performances where X.XX is the MCC score and Y.YY is the accuracy score. The italic numbers are the learning performances, and thus they are not used in the comparison. The bold-font numbers are the better performances when comparing ΣB and avgΣB*avgNo.B with ΔASA, and ΣB with ΔASA.