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Table 2 Top 25 features selected using RELIEFF algorithm.

From: Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder

Rank Feature Merit Score P-value Adj. P-value Significance
1 w+E_2 0.355474 0.00E+00 0.00E+00 *
2 Consensus 0.261813 0.00E+00 0.00E+00 *
3 wDE 0.164459 1.66E-41 3.23E-40 *
4 w+2_Hydro 0.160149 3.90E-83 1.33E-81 *
5 w-I_3 0.105916 1.18E-107 5.33E-106 *
6 w-3_Hydro 0.104835 8.12E-58 1.84E-56 *
7 wK 0.078651 1.33E-02 4.03E-02 *
8 w-V_3 0.075073 1.92E-58 5.22E-57 *
9 w-2_Hydro 0.057669 1.48E-02 4.37E-02 *
10 w+3_Hydro 0.056496 1.49E-01 2.93E-01  
11 w+1_Hydro 0.05232 7.13E-02 1.62E-01  
12 w-1_Hydro 0.051279 4.22E-02 9.89E-02  
13 w-L_3 0.051001 1.96E-03 7.00E-03 *
14 w+K_2 0.050248 1.70E-08 1.78E-07 *
15 w+P_2 0.045911 3.39E-02 8.23E-02  
16 w+P_3 0.043573 2.11E-25 3.58E-24 *
17 w-K_3 0.043208 4.33E-04 1.96E-03 *
18 Flexibility 0.042334 7.52E-07 7.31E-06 *
19 w+D_2 0.041784 7.14E-01 7.77E-01  
20 w-S_2 0.041097 2.95E-01 4.57E-01  
21 DisorderBinary 0.040666 7.27E-14 9.88E-13 *
22 w-E_3 0.039548 6.14E-05 3.79E-04 *
23 w-A_3 0.03804 3.04E-02 7.95E-02  
24 w-P_1 0.037893 4.46E-06 3.80E-05 *
25 w-E_2 0.035935 4.16E-01 5.74E-01  
  1. 93 out of 137 features has been selected based on 10-fold classification performance. Features are ranked using RELIEFF [26] algorithm, implemented in Weka [39]. Details of statistical testing can be found in Methods section. For assessing significance, adjusted p-value cutoff of 0.05 is used. Feature name explanations can be found in Methods section and Figure 2a.