Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines
Abstract Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computati...
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| Main Authors: | Kevin A. Kovalchik, David J. Hamelin, Peter Kubiniok, Benoîte Bourdin, Fatima Mostefai, Raphaël Poujol, Bastien Paré, Shawn M. Simpson, John Sidney, Éric Bonneil, Mathieu Courcelles, Sunil Kumar Saini, Mohammad Shahbazy, Saketh Kapoor, Vigneshwar Rajesh, Maya Weitzen, Jean-Christophe Grenier, Bayrem Gharsallaoui, Loïze Maréchal, Zhaoguan Wu, Christopher Savoie, Alessandro Sette, Pierre Thibault, Isabelle Sirois, Martin A. Smith, Hélène Decaluwe, Julie G. Hussin, Mathieu Lavallée-Adam, Etienne Caron |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54734-9 |
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