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DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.
Wu, Jingcheng; Li, Jiaoyang; Chen, Shuqing; Zhou, Zhan.
Afiliación
  • Wu J; Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
  • Li J; College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
  • Chen S; Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
  • Zhou Z; Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. zhanzhou@zju.edu.cn.
Methods Mol Biol ; 2809: 237-244, 2024.
Article en En | MEDLINE | ID: mdl-38907901
ABSTRACT
Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA binding affinity. In this chapter, we introduce a user-friendly tool named DeepHLApan, which utilizes deep learning techniques to predict neoantigens by considering both peptide-HLA binding affinity and immunogenicity. We provide the application of DeepHLApan, along with the source code, docker version, and web-server. These resources are freely available at https//github.com/zjupgx/deephlapan and http//pgx.zju.edu.cn/deephlapan/ .
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos / Programas Informáticos / Biología Computacional / Aprendizaje Profundo / Antígenos HLA Límite: Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos / Programas Informáticos / Biología Computacional / Aprendizaje Profundo / Antígenos HLA Límite: Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos