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SeqPalm

Represents a reliable identification method for protein S-palmitoylation sites which is based on a series of composed features from protein sequence and the synthetic minority oversampling technique. The SeqPalm interface allows to study all types of disease associated variations. With this tool, users are able to discover the molecular basis of pathogenesis associated with abnormal palmitoylation, annotate the palmitoylation sites of proteins and distinguish loss or gain of palmitoylation sites by protein variations.

NBA-Palm

A computational method based on naive Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation.

CKSAAP-Palm

A tool for predicting palmitoylation sites based on protein sequence. For a sequence segment in a given protein, the encoding scheme based on the composition of k-spaced amino acid pairs (CKSAAP) is introduced, and then the support vector machine is used as the predictor. The proposed prediction model CKSAAP-Palm outperforms the existing method CSS-Palm2.0 on both cross-validation experiments and some independent testing data sets. These results imply that our CKSAAP-Palm is able to predict more potential palmitoylation sites and increases research productivity in palmitoylation sites discovery.