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• W4221076420 endingPage "146445" @default.
• W4221076420 startingPage "146445" @default.
• W4221076420 abstract "Post-translational modification (PTM) is defined as the enzymatic changes of proteins after the translation process in protein biosynthesis. Nitrotyrosine, which is one of the most important modifications of proteins, is interceded by the active nitrogen molecule. It is known to be associated with different diseases including autoimmune diseases characterized by chronic inflammation and cell damage. Currently, nitrotyrosine sites are identified using experimental approaches which are laborious and costly. In this study, we propose a new machine learning method called PredNitro to accurately predict nitrotyrosine sites. To build PredNitro, we use sequence coupling information from the neighboring amino acids of tyrosine residues along with a support vector machine as our classification technique.Our results demonstrates that PredNitro achieves 98.0% accuracy with more than 0.96 MCC and 0.99 AUC in both 5-fold cross-validation and jackknife cross-validation tests which are significantly better than those reported in previous studies. PredNitro is publicly available as an online predictor at: http://103.99.176.239/PredNitro." @default.
• W4221076420 created "2022-04-03" @default.
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• W4221076420 date "2022-06-01" @default.
• W4221076420 modified "2023-10-16" @default.
• W4221076420 title "Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information" @default.
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• W4221076420 doi "https://doi.org/10.1016/j.gene.2022.146445" @default.
• W4221076420 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35358650" @default.
• W4221076420 hasPublicationYear "2022" @default.
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