TrambaHLApan: a transformer and mamba-based neoantigen prediction method considering both antigen presentation and immunogenicity
Description
Neoantigens represent ideal targets for tumor immunotherapy. This study introduces TrambaHLApan, a neoantigen prediction method that utilizes Transformer and Mamba models to consider both antigen presentation potential (TrambaHLApan-EL) and immunogenicity (TrambaHLApan-IM). Data S1: Antigen presentation training set Data S2: Immunogenicity training set Data S3: Allele24 independent antigen presentation test dataset Data S4: Allele36 independent antigen presentation test set Data S5: Cancer neoantigen immunogenicity test set (GBM) Data S6: Cancer neoantigen immunogenicity test set (MANAFEST) fivefold_val_flags(DataS1): Five-fold cross-validation division file for DataS1 fivefold_val_flags(DataS2): Five-fold cross-validation division file for DataS2