ArticleFrontiers in immunology2022
Unsupervised Mining of HLA-I Peptidomes Reveals New Binding Motifs and Potential False Positives in the Community Database.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Mass Spectrometry-Driven Epitope Mapping: Application of Diethylpyrocarbonate Covalent Labeling for the Immunotherapeutic Target Programmed Cell Death Protein 1.Journal of the American Society for Mass Spectrometry · 2025Article
- MHCSeqNet2-improved peptide-class I MHC binding prediction for alleles with low data.Bioinformatics (Oxford, England) · 2024Article
- A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics.Cell reports methods · 2023Article
- Improved predictions of antigen presentation and TCR recognition with MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8Cell systems · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern vaccine designs and studies of human leukocyte antigen (HLA)-mediated immune responses rely heavily on the knowledge of HLA allele-specific binding motifs and computational prediction of HLA-peptide binding affinity. Breakthroughs in HLA peptidomics have considerably expanded the databases of natural HLA ligands and enabled detailed characterizations of HLA-peptide binding specificity. However, cautions must be made when analyzing HLA peptidomics data because identified peptides may be contaminants in mass spectrometry or may weakly bind to the HLA molecules. Here, a hybrid
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Registered trials
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