ArticleBMC bioinformatics2015
A two-layered machine learning method to identify protein O-GlcNAcylation sites with O-GlcNAc transferase substrate motifs.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- The human O-GlcNAcome database and meta-analysis.Scientific data · 2021Pooled it
- O-GlcNAc informatics: advances and trends.Analytical and bioanalytical chemistry · 2025Review
- Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.International journal of molecular sciences · 2024Article
- Site-specific prediction of O-GlcNAc modification in proteins using evolutionary scale model.PloS one · 2024Article
- Integrating Embeddings from Multiple Protein Language Models to Improve ProteinInternational journal of molecular sciences · 2023Article
- Article
- Advances, obstacles, and opportunities for machine learning in proteomics.Cell reports. Physical science · 2022Article
- Cancer-cell-secreted miR-122 suppresses O-GlcNAcylation to promote skeletal muscle proteolysis.Nature cell biology · 2022Article
- dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data.Nucleic acids research · 2022Article
- OGP: A Repository of Experimentally Characterized O-glycoproteins to Facilitate Studies on O-glycosylation.Genomics, proteomics & bioinformatics · 2021Article
- On the Need to Tell Apart Fraternal Twins eEF1A1 and eEF1A2, and Their Respective Outfits.International journal of molecular sciences · 2021Review
- Residue-Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites.Frontiers in genetics · 2021Article
- Article
- Regulation of DELLA Proteins by Post-translational Modifications.Plant & cell physiology · 2020Review
- The Emerging Role of Galectins andCells · 2020Review
- OGT suppresses S6K1-mediated macrophage inflammation and metabolic disturbance.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- O-GlcNAc transferase inhibits visceral fat lipolysis and promotes diet-induced obesity.Nature communications · 2020Article
- OGT-Mediated KEAP1 Glycosylation Accelerates NRF2 Degradation Leading to High Phosphate-Induced Vascular Calcification in Chronic Kidney Disease.Frontiers in physiology · 2020Article
- Critical observations that shaped our understanding of the function(s) of intracellular glycosylation (O-GlcNAc).FEBS letters · 2018Review
- OGT (Cells · 2018Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein O-GlcNAcylation, involving the β-attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues, is an O-linked glycosylation catalyzed by O-GlcNAc transferase (OGT). Molecular level investigation of the basis for OGT's substrate specificity should aid understanding how O-GlcNAc contributes to diverse cellular processes. Due to an increasing number of O-GlcNAcylated peptides with site-specific information identified by mass spectrometry (MS)-based proteomics, we were motivated to characterize substrate site motifs of O-GlcNAc transferases. In this investigation, a non-redundant dataset of 410 experimentally verified O-GlcNAcylation sites were manually extracted from dbOGAP, OGlycBase and UniProtKB. After detection of conserved motifs by using maximal dependence decomposition, profile hidden Markov model (profile HMM) was adopted to learn a first-layered model for each identified OGT substrate motif. Support Vector Machine (SVM) was then used to generate a second-layered model learned from the output values of profile HMMs in first layer. The two-layered predictive model was evaluated using a five-fold cross validation which yielded a sensitivity of 85.4%, a specificity of 84.1%, and an accuracy of 84.7%. Additionally, an independent testing set from PhosphoSitePlus, which was really non-homologous to the training data of predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (84.05%) and outperform other O-GlcNAcylation site prediction tools. A case study indicated that the proposed method could be a feasible means of conducting preliminary analyses of protein O-GlcNAcylation and has been implemented as a web-based system, OGTSite, which is now freely available at http://csb.cse.yzu.edu.tw/OGTSite/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.