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PredCSO: an ensemble method for prediction of S-sulfenylation sites in proteins

Abstract

Protein S-sulfenylation is a type of reversible post-translational modifications (PTM) through which cysteine (CYS) thiols of proteins are reversibly oxidized to cysteine sulfenic acids (CSO). Recent studies have shown that this event plays essential role in cell signaling, transcriptional regulation and protein functions. Therefore, the identification of S-sulfenylation sites is important to understand the functions of S-sulfenylated proteins. In this study, we proposed PredCSO, a computational method for predicting S-sulfenylation sites in proteins. PredCSO is built on four kinds of features, including position-specific scoring matrix, position-specific amino acid propensity, the absolute solvent accessibility and four-body statistical pseudo-potential. In particular, 21 crucial features were refined out using a two-step feature selection procedure consisting of a max-relevance algorithm and a sequential backward elimination algorithm. To overcome the problem of imbalanced sample sizes, we adopt an ensemble method, which combines bootstrap resampling, gradient tree boosting and majority voting. Our performance evaluation show that PredCSO achieves state-of-the-art performance in identifying S-sulfenylation sites in proteins.

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Publication details

The article was received on 10 Apr 2018, accepted on 13 Jun 2018 and first published on 14 Jun 2018


Article type: Research Article
DOI: 10.1039/C8MO00089A
Citation: Mol. Omics, 2018, Accepted Manuscript
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    PredCSO: an ensemble method for prediction of S-sulfenylation sites in proteins

    L. Deng, X. Xu and H. Liu, Mol. Omics, 2018, Accepted Manuscript , DOI: 10.1039/C8MO00089A

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