ReviewProteomics2018
Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes.
Review in Proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 50 citations in OpenAlex.
- Computational design of class II MHC binding peptide with sequence-based evolution information.Bioinformatics advances · 2026Article
- On the impact of local protein structure features on prediction of major histocompatibility complex class I and II antigen presentation.Briefings in bioinformatics · 2025Article
- Immunopeptidomics ofBiology · 2024Article
- Crucial Parameters for Immunopeptidome Characterization: A Systematic Evaluation.International journal of molecular sciences · 2024Article
- The physiological interactome of TCR-like antibody therapeutics in human tissues.Nature communications · 2024Article
- MHCII-peptide presentation: an assessment of the state-of-the-art prediction methods.Frontiers in immunology · 2024Review
- Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome.Communications biology · 2023Article
- Article
- Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome.Frontiers in immunology · 2022Article
- Peptidomes and Structures Illustrate How SLA-I Micropolymorphism Influences the Preference of Binding Peptide Length.Frontiers in immunology · 2022Article
- Advanced strategies for development of vaccines against human bacterial pathogens.World journal of microbiology & biotechnology · 2021Review
- Peptidomes and Structures Illustrate Two Distinguishing Mechanisms of Alternating the Peptide Plasticity Caused by Swine MHC Class I Micropolymorphism.Frontiers in immunology · 2021Article
- DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.Proteomics · 2020Article
- Repertoire-scale determination of class II MHC peptide binding via yeast display improves antigen prediction.Nature communications · 2020Article
- A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.Briefings in bioinformatics · 2020Review
- NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data.Nucleic acids research · 2020Article
- A Systematic, Unbiased Mapping of CD8Frontiers in immunology · 2020Article
- The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.Molecular & cellular proteomics : MCP · 2020Article
- Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.Frontiers in immunology · 2020Article
- NNAlign_MA; MHC Peptidome Deconvolution for Accurate MHC Binding Motif Characterization and Improved T-cell Epitope Predictions.Molecular & cellular proteomics : MCP · 2019Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Recent advances in proteomics and mass-spectrometry have widely expanded the detectable peptide repertoire presented by major histocompatibility complex (MHC) molecules on the cell surface, collectively known as the immunopeptidome. Finely characterizing the immunopeptidome brings about important basic insights into the mechanisms of antigen presentation, but can also reveal promising targets for vaccine development and cancer immunotherapy. This report describes a number of practical and efficient approaches to analyze immunopeptidomics data, discussing the identification of meaningful sequence motifs in various scenarios and considering current limitations. Guidelines are provided for the filtering of false hits and contaminants, and to address the problem of motif deconvolution in cell lines expressing multiple MHC alleles, both for the MHC class I and class II systems. Finally, it is demonstrated how machine learning can be readily employed by non-expert users to generate accurate prediction models directly from mass-spectrometry eluted ligand data sets.
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What OpenQuestion holds
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.