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Table 6 Performance on balanced dataset for MTS vs SP vs N-signal-free protein prediction using SVM classifier

From: Plus ça change – evolutionary sequence divergence predicts protein subcellular localization signals

  Divergence Classical features Combination
  AUC MCC AUC MCC AUC MCC
MTS 0.67±0.10 0.35±0.20 0.84±0.07 0.68±0.13 0 . 8 8±0.05 0 . 7 8±0.09
SP 0.71±0.09 0.41±0.16 0.92±0.05 0.85±0.10 0 . 9 4±0.01 0 . 8 8±0.03
N-signal-free 0.79±0.07 0.60±0.13 0.78±0.09 0.57±0.18 0 . 8 6±0.07 0 . 7 4±0.13
% accuracy 62.86±5.84 79.92±5.54 8 6 . 1 9±4.67
  1. The 5-fold cross-validation performance of an SVM classifier using: divergence features only, classical features only, and the two combined; is shown for three-way classification on a balanced dataset (53 proteins from each class, yeast curated orthologs).