{"count":4,"items":[{"access":"open","article":"/blog/modele-prezentacji-antygenu","cancer_slugs":["pan-cancer"],"doi":null,"formats":["CSV","JSON"],"hf":null,"huggingface":null,"kind":"registry","license":"free to use; NIAID-funded public resource","modalities":["protein-sequence","immunopeptidomics"],"name":"IEDB \u2014 Immune Epitope Database","page":"/ai-oncology/datasets/iedb","provider":"La Jolla Institute for Immunology, funded by NIAID","size":{"items":1600000,"notes_en":"curated from published literature and direct submissions; includes MHC binding assays, MS-eluted ligands and T-cell assays","notes_pl":"kuratorowane z literatury i zg\u0142osze\u0144 bezpo\u015brednich; zawiera testy wi\u0105zania MHC, ligandy ze spektrometru i testy limfocyt\u00f3w T","unit":"epitope-related records"},"slug":"iedb","summary":"The field's central repository of epitope data and the source of almost every training set for peptide\u2013MHC models \u2014 and of their allele skew.","tasks":["peptide-mhc-binding","antigen-presentation"],"url":"https://www.iedb.org/","verified_at":"2026-09-05T22:25:59.114121"},{"access":"open","article":"/blog/modele-prezentacji-antygenu","cancer_slugs":["pan-cancer"],"doi":null,"formats":["CSV"],"hf":null,"huggingface":null,"kind":"benchmark","license":"public","modalities":["protein-sequence"],"name":"IEDB automated benchmark (MHC class I)","page":"/ai-oncology/datasets/iedb-benchmark","provider":"La Jolla Institute for Immunology","size":{"notes_en":"runs continuously on newly deposited data, before it can leak into anyone's training set","notes_pl":"dzia\u0142a na bie\u017c\u0105co na \u015bwie\u017co deponowanych danych, zanim mog\u0105 trafi\u0107 do czyjegokolwiek zbioru treningowego"},"slug":"iedb-benchmark","summary":"The only prospective, third-party benchmark in the field. Its eight-year summary is sobering: leading methods are statistically indistinguishable, and a new method needs about four years before enough data accumulate to judge it.","tasks":["peptide-mhc-binding","antigen-presentation"],"url":"http://tools.iedb.org/auto_bench/mhci/weekly/","verified_at":"2026-09-05T22:25:59.140589"},{"access":"open","article":"/blog/modele-prezentacji-antygenu","cancer_slugs":["pan-cancer"],"doi":"10.1038/s41587-019-0322-9","formats":["CSV","text"],"hf":null,"huggingface":null,"kind":"dataset","license":"published supplementary data (see papers)","modalities":["immunopeptidomics","protein-sequence"],"name":"Mono-allelic HLA class I peptidome (Sarkizova / Abelin)","page":"/ai-oncology/datasets/monoallelic-peptidome","provider":"Broad Institute / Dana-Farber Cancer Institute","size":{"items":186464,"notes_en":"95 mono-allelic cell lines (31 HLA-A, 40 HLA-B, 21 HLA-C, 3 HLA-G), median 1,860 peptides per allele; the earlier Abelin 2017 set covered 16 alleles and >24,000 peptides","notes_pl":"95 linii monoallelicznych (31 HLA-A, 40 HLA-B, 21 HLA-C, 3 HLA-G), mediana 1860 peptyd\u00f3w na allel; wcze\u015bniejszy zbi\u00f3r Abelin 2017 obj\u0105\u0142 16 alleli i ponad 24 000 peptyd\u00f3w","unit":"peptides"},"slug":"monoallelic-peptidome","summary":"The engineered-cell peptidome that gave the field clean allele labels; fifteen of its alleles had no described motif before, and the panel covers at least one allele in 95% of people worldwide.","tasks":["antigen-presentation","peptide-mhc-binding"],"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC7008090/","verified_at":"2026-09-05T22:25:59.152441"},{"access":"open","article":"/blog/modele-prezentacji-antygenu","cancer_slugs":["pan-cancer"],"doi":null,"formats":["CSV"],"hf":null,"huggingface":null,"kind":"benchmark","license":"public","modalities":["protein-sequence"],"name":"BD2013 \u2014 MHC binding affinity benchmark","page":"/ai-oncology/datasets/bd2013","provider":"IEDB / Kim et al.","size":{"items":176161,"notes_en":"114 alleles across six species \u2014 the historical training core for binding predictors, and a reminder of how small the measured world is","notes_pl":"114 alleli w sze\u015bciu gatunkach \u2014 historyczny rdze\u0144 treningowy modeli wi\u0105zania i przypomnienie, jak ma\u0142y jest \u015bwiat zmierzony","unit":"affinity measurements"},"slug":"bd2013","summary":"The reference affinity dataset behind fifteen years of binding predictors; its size and composition are why dataset composition, not architecture, drives reported performance.","tasks":["peptide-mhc-binding"],"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC4111843/","verified_at":"2026-09-05T22:25:59.496418"}]}