Fig. 1: Schematic of the computational framework and analysis platform for informing next-generation T-cell vaccine design. | Nature Communications

Fig. 1: Schematic of the computational framework and analysis platform for informing next-generation T-cell vaccine design.

From: Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines

Fig. 1

(1) MS-based immunopeptidomics for data acquisition, (2) MHCvalidator for HLA-I-specific PSMs confidence assessment and optimal identification of both canonical and non-canonical HLA-I viral peptides, (3) population-scale analysis of SARS-CoV-2 proteome diversity using intra-host databases, (4) T-cell epitope immunogenicity assessment, (5) EpiTrack for geo-temporal analysis of epitope conservation across variants, (6) selection of immunogenic and stable epitopes to inform optimal T-cell vaccine design. T-cell epitopes encoded by the BNT162b4 mRNA-based vaccine were analyzed in this study. Created in BioRender. Hamelin, D. (2024) BioRender.com/l76m979.

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