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Protein Processing, Post-Translational

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Prediction of S-nitrosylation sites by integrating support vector machines and random forest.

Molecular omics
Cysteine S-nitrosylation is a type of reversible post-translational modification of proteins, which controls diverse biological processes. It is associated with redox-based cellular signaling to protect against oxidative stress. The identification of...

Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.

Briefings in bioinformatics
Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse functions and biological processes of proteins. However, because of the large volumes of sequencing data generated from genome-sequencing projects, systematic id...

SPRINT-Gly: predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties.

Bioinformatics (Oxford, England)
MOTIVATION: Protein glycosylation is one of the most abundant post-translational modifications that plays an important role in immune responses, intercellular signaling, inflammation and host-pathogen interactions. However, due to the poor ionization...

DeepPhos: prediction of protein phosphorylation sites with deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Phosphorylation is the most studied post-translational modification, which is crucial for multiple biological processes. Recently, many efforts have been taken to develop computational predictors for phosphorylation site prediction, but m...

Capsule network for protein post-translational modification site prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Computational methods for protein post-translational modification (PTM) site prediction provide a useful approach for studying protein functions. The prediction accuracy of the existing methods has significant room for improvement. A rece...

DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications.

Bioinformatics (Oxford, England)
MOTIVATION: Computational methods that predict differential gene expression from histone modification signals are highly desirable for understanding how histone modifications control the functional heterogeneity of cells through influencing different...

O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling technique.

Bioinformatics (Oxford, England)
MOTIVATION: Protein O-GlcNAcylation (O-GlcNAc) is an important post-translational modification of serine (S)/threonine (T) residues that involves multiple molecular and cellular processes. Recent studies have suggested that abnormal O-G1cNAcylation c...

iPTMnet: an integrated resource for protein post-translational modification network discovery.

Nucleic acids research
Protein post-translational modifications (PTMs) play a pivotal role in numerous biological processes by modulating regulation of protein function. We have developed iPTMnet (http://proteininformationresource.org/iPTMnet) for PTM knowledge discovery, ...

Prediction of Nitrated Tyrosine Residues in Protein Sequences by Extreme Learning Machine and Feature Selection Methods.

Combinatorial chemistry & high throughput screening
BACKGROUND: Accurately recognizing nitrated tyrosine residues from protein sequences would pave a way for understanding the mechanism of nitration and the screening of the tyrosine residues in sequences.

iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines.

Molecular bioSystems
Protein phosphorylation plays a potential role in regulating protein conformation and functions. As a result, identifying an uncharacterized protein sequence as a phosphorylated protein is a very meaningful problem and an urgent issue for both basic ...