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Table 1 The Mean Absolute Error (MAE) of different feature combinations with the DBRM method

From: Deep learning methods for protein torsion angle prediction

Number of features Feature combinationa phi psi avgb
1 PSSM 23.28 35.12 29.2
8-state secondary structure (8stateSS) 25.12 33.52 29.32
Contacts_number_15_classes (CN15) 25.58 37.26 31.42
Error_distribution_of_fragment_based_angles (fragsion) 24.24 40 32.12
3-state secondary structure (3SS) 25.8 38.95 32.38
Contacts_number_1_real_value (CN1) 26.92 44.71 35.82
7 physicochemical properties (7PC) 27.27 52.18 39.73
Solvent_accessibility (SA) 29.15 53.84 41.5
Disorder 30.8 64.69 47.75
2 PSSM_8stateSS 22.18 30.73 26.46
PSSM_CN15 22.41 33.14 27.78
PSSM_Fragsion 22.19 34.29 28.24
PSSM_7PC 22.42 35.75 29.09
PSSM_DISORDER 22.96 35.23 29.1
PSSM_SA 23.47 35.53 29.5
3 PSSM_8stateSS_7PC 21.48 30.36 25.92
PSSM_8stateSS_Fragsion 21.63 30.72 26.18
PSSM_8stateSS_CN15 21.99 30.12 26.06
PSSM_SS8_Disorder 22.91 31.08 27
PSSM_8stateSS_SA 23.09 31.41 27.25
4 PSSM_8stateSS_7PC_CN15 21.48 30.27 25.88
PSSM_8stateSS_7PC_SA 21.88 30.89 26.39
PSSM_8stateSS_7PC_Disorder 22.17 30.97 26.57
PSSM_8stateSS_7PC_Fragsion 22.08 31.11 26.595
5 PSSM_8stateSS_7PC_CN15_Disorder 21.54 29.94 25.74
PSSM_8stateSS_7PC_CN15_SA 21.93 30.39 26.16
PSSM_8stateSS_7PC_CN15_Fragsion 21.81 30.83 26.32
6 PSSM_8stateSS_7PC_CN15_Disorder_Fragsion 21.11 30.33 25.72
PSSM_8stateSS_7PC_CN15_Disorder_SA 22.24 30.60 26.42
7 PSSM_8stateSS_7PC_CN15_Disorder_Fragsion_SA 21.36 29.83 25.6
  1. aFeatures combination: for example “PSSM_8stateSS” represent the combination of PSSM and 8-state secondary structure as input features. The bold font denotes the best combination selected for a specific number of features in terms of the average MAE of phi and psi angles
  2. bavg.: Average of phi and psi values for each features combination