ArticleBioinformatics (Oxford, England)2023
EMNGly: predicting N-linked glycosylation sites using the language models for feature extraction.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
- Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.Journal of translational medicine · 2025Pooled it
- ViralMap: predicting features in viral proteins from primary sequence.Journal of virology · 2026Article
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026Review
- Glycosylated NS3/NS3A protein of bluetongue virus facilitates efficient viral egress via lipid raft anchoring.Journal of virology · 2026Article
- Review
- Future Sequon Finder - A novel approach for predicting future N-linked glycosylation sequon locations on viral surface proteins.PloS one · 2025Article
- Integrated analysis of N-glycosylation and Alzheimer's disease: identifying key biomarkers and mechanisms.Frontiers in aging neuroscience · 2025Article
- Large Language Model (LLM)-Based Advances in Prediction of Post-translational Modification Sites in Proteins.Methods in molecular biology (Clifton, N.J.) · 2025Review
- DNA sequence analysis landscape: a comprehensive review of DNA sequence analysis task types, databases, datasets, word embedding methods, and language models.Frontiers in medicine · 2025Review
- Advances in Prediction of Posttranslational Modification Sites Known to Localize in Protein Supersecondary Structures.Methods in molecular biology (Clifton, N.J.) · 2025Article
- StackGlyEmbed: prediction of N-linked glycosylation sites using protein language models.Bioinformatics advances · 2025Article
- 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
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationN-linked glycosylation is a frequently occurring post-translational protein modification that serves critical functions in protein folding, stability, trafficking, and recognition. Its involvement spans across multiple biological processes and alterations to this process can result in various diseases. Therefore, identifying N-linked glycosylation sites is imperative for comprehending the mechanisms and systems underlying glycosylation. Due to the inherent experimental complexities, machine learning and deep learning have become indispensable tools for predicting these sites.
resultsIn this context, a new approach called EMNGly has been proposed. The EMNGly approach utilizes pretrained protein language model (Evolutionary Scale Modeling) and pretrained protein structure model (Inverse Folding Model) for features extraction and support vector machine for classification. Ten-fold cross-validation and independent tests show that this approach has outperformed existing techniques. And it achieves Matthews Correlation Coefficient, sensitivity, specificity, and accuracy of 0.8282, 0.9343, 0.8934, and 0.9143, respectively on a benchmark independent test set.
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Registered trials
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.