PredIG: an interpretable predictor of T-cell epitope immunogenicity
Overall, we demonstrate how PredIG immunogenicity scores are instrumental to refine and expand the prioritization of actionable T-cell (neo)epitopes in infection and cancer, including non-canonical antigens not seen during training. Furthermore, PredIG displays an unprecedented immunological interpretability determining important immunogenicity drivers beyond HLA-I binding affinity. Ultimately, PredIG enables large throughput antigen discovery in open-source containerized environments ( https://github.com/BSC-CNS-EAPM/PredIG ) and facilitates accessibility via a streamlined webserver ( https://horus.bsc.es/predig ).
Authors
- Miguél Vázquez (ORCID: https://orcid.org/0000-0002-5713-1058)
- Albert Cañellas-Solé (ORCID: https://orcid.org/0000-0001-8120-888X)
- Roc Farriol-Duran
- Christian Domínguez-Dalmases (ORCID: https://orcid.org/0000-0002-3725-5790)
- Vı́ctor Guallar (ORCID: https://orcid.org/0000-0002-4580-1114)
- Eduard Porta‐Pardo (ORCID: https://orcid.org/0000-0001-7900-4239)
Institutions
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Barcelona Supercomputing Center (ES)
- Josep Carreras Leukaemia Research Institute (ES)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Genome Medicine
- Published
- 2025-11-12
- DOI
- https://doi.org/10.1186/s13073-025-01569-8
- Citations
- 3
- Primary Topic
- vaccines and immunoinformatics approaches
- Type
- article
- Field-Weighted Citation Impact
- 2.42