Table 1 The cross-validation results of different feature combinations and the optimal selected feature set using mRMR-IFS on the RBP170 dataset
From: A boosting approach for prediction of protein-RNA binding residues
Features | ACC | SN | SP | Precision | F-measure | MCC | AUC |
|---|---|---|---|---|---|---|---|
PSSM | 0.72 ± 0.01 | 0.69 ± 0.02 | 0.73 ± 0.01 | 0.30 ± 0.01 | 0.42 ± 0.02 | 0.31 ± 0.02 | 0.79 ± 0.01 |
SiteFs | 0.77 ± 0.01 | 0.74 ± 0.02 | 0.77 ± 0.01 | 0.36 ± 0.01 | 0.48 ± 0.01 | 0.40 ± 0.02 | 0.84 ± 0.01 |
SNF-VDs | 0.75 ± 0.01 | 0.80 ± 0.01 | 0.74 ± 0.01 | 0.35 ± 0.02 | 0.48 ± 0.02 | 0.40 ± 0.02 | 0.85 ± 0.01 |
SNF-EDs | 0.78 ± 0.01 | 0.79 ± 0.02 | 0.78 ± 0.01 | 0.38 ± 0.02 | 0.51 ± 0.01 | 0.44 ± 0.02 | 0.87 ± 0.01 |
SNF-EDs+SNF-VDs | 0.82 ± 0.01 | 0.81 ± 0.02 | 0.82 ± 0.01 | 0.44 ± 0.02 | 0.57 ± 0.02 | 0.51 ± 0.02 | 0.89 ± 0.01 |
SiteFs+SNF-EDs+SNF-VDs | 0.82 ± 0.01 | 0.83 ± 0.01 | 0.83 ± 0.01 | 0.46 ± 0.02 | 0.58 ± 0.01 | 0.53 ± 0.01 | 0.91 ± 0.01 |
mRMR-IFS (Top177) | 0.84 ± 0.01 | 0.85 ± 0.02 | 0.84 ± 0.01 | 0.47 ± 0.02 | 0.60 ± 0.02 | 0.55 ± 0.02 | 0.92 ± 0.01 |