Proteomics

Dataset Information

0

Fully unsupervised identification of HLA-I motifs


ABSTRACT: The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across publicly available as well as ten newly generated high quality HLA peptidomics datasets, we show that we can rapidly and accurately identify HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. This fully unsupervised approach uncovers new motifs for several alleles without known ligands and significantly improves neo-epitope predictions in three melanoma patients.

INSTRUMENT(S): Orbitrap Fusion, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): B Cell, T Cell

SUBMITTER: Michal Bassani-Sternberg  

LAB HEAD: Michal Bassani-Sternberg

PROVIDER: PXD005231 | Pride | 2017-08-18

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20160513_TIL1_R1.raw Raw
20160513_TIL1_R2.raw Raw
20160513_TIL2_R1.raw Raw
20160513_TIL2_R2.raw Raw
20160513_TIL3_R1.raw Raw
Items per page:
1 - 5 of 42

Similar Datasets

2019-07-31 | PXD009925 | Pride
2021-09-17 | PXD028088 | Pride
2021-12-03 | PXD028874 | Pride
2019-10-16 | PXD012308 | Pride
2019-12-18 | PXD013831 | Pride
2018-04-10 | PXD007756 | Pride
2021-04-16 | PXD019643 | Pride
2019-02-25 | PXD011257 | Pride
2022-02-14 | PXD026184 | Pride
2016-12-12 | PXD005084 | Pride