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Table 1 Performance measures and dimensions for the different features

From: A deep learning method to more accurately recall known lysine acetylation sites

Feature Dimension Accuracy Specificity Sensitivity AUC MCC
One-hot 651 76.25% 74.00% 78.50% 0.7506 0.5256
BLOSUM62 651 76.23% 71.68% 80.77% 0.7880 0.5267
CKSAAP 2205 73.61% 70.79% 76.44% 0.7290 0.4731
IG 1 53.22% 64.02% 42.43% 0.5430 0.0660
AAindex 434 63.65% 53.92% 73.38% 0.6904 0.2783
PSSM 30 49.50% 60.46% 38.53% 0.4941 −0.0103
Word2vec 31 52.78% 56.89% 48.57% 0.4382 0.1814