Data Set Construction

The dataset of independent test, which extracted from UniProtKB/Swiss-Prot release 55 which remote the same data in dbPTM, were used as positive dataset. The Negative dataset were randomly selecting from non-acetylation site of acetylated proteins.


The following measures of predictive performance of the trained models are defined: Precision (Prec) = TP / (TP+FP), Sensitivity (Sn) = TP / (TP+FN), Specificity (Sp) = TN / (TN+FP) and Accuracy (Acc) = (TP + TN) / (TP+FP+TN+FN), where TP, TN, FP and FN are true positive, true negative, false positive and false negative predictions, respectively. The independent test set was used to evaluate the predictive performance of N-Ace , Pail and NetAcet.