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The leave-one-out test on the training dataset reached the accuracy of 0.7733, and the independent test on the testing dataset got 0.8889. Furthermore, the classifier also successfully identified 144 of 160 putative malonylation sites. Analyses on the differences between malonylation and non-malonylation segments implicated that lysine malonylation should follow a specific pattern, e.g. lysine with its neighbors being Glycine and Alanine might be more likely to be malonylated. Therefore, the proposed method is expected to be a promising tool to identify malonylation sites.

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