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A method to automate the prediction of the proline and lysine hydroxylation sites based on position weight amino acids composition, 8 high-quality amino acid indices and support vector machines. The PredHydroxy achieved a promising performance with an area under the receiver operating characteristic curve (AUC) of 82.72% and a Matthew's correlation coefficient (MCC) of 69.03% for hydroxyproline as well as an AUC of 87.41% and a MCC of 66.68% for hydroxylysine in jackknife cross-validation.


A plugin implemented with the commonly used visualization software PyMOL. PyTMs enables users to introduce a set of common post-translational modifications (PTMs) into protein/peptide models and can be used to address research questions related to PTMs. Ten types of modification are currently supported, including acetylation, carbamylation, citrullination, cysteine oxidation, malondialdehyde adducts, methionine oxidation, methylation, nitration, proline hydroxylation and phosphorylation.


Predicts the identifying protein hydroxylation sites. iHyd-PseCp is a predictor that incorporates the sequence-coupled information into the general pseudo amino acid composition (PseAAC). It can become a useful high throughput tool for both basic research and drug development in the areas relevant to the protein hydroxylation. To obtain the predicted result with the anticipated success rate, the entire sequence of the query protein rather than its fragment should be used as an input.