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Improved MHC II epitope prediction — a step towards personalized medicine
Numerous neoepitope-based vaccination strategies are in testing for clinical use in the treatment of cancer. Rapid identification of immunostimulatory neoantigen targets hastens neoantigen vaccine development. Papers recently published in Nature Biotechnology describe two independent machine-learnin...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7223749/ https://www.ncbi.nlm.nih.gov/pubmed/31836878 http://dx.doi.org/10.1038/s41571-019-0315-0 |
Sumario: | Numerous neoepitope-based vaccination strategies are in testing for clinical use in the treatment of cancer. Rapid identification of immunostimulatory neoantigen targets hastens neoantigen vaccine development. Papers recently published in Nature Biotechnology describe two independent machine-learning-based algorithms that demonstrate improved identification of MHC class II-binding peptides. Herein, we outline the benefits of these algorithms and their implications for future immunotherapies. |
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