Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
Methods Mol Biol. 2024;2809:237-244. doi: 10.1007/978-1-0716-3874-3_15.
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/ .
新抗原在区分癌细胞和正常细胞方面起着至关重要的作用，并且在癌症免疫疗法中具有重要作用。肿瘤新抗原的生物信息学预测领域发展迅速，主要集中在肽-HLA 结合亲和力的预测上。在本章中，我们介绍了一个名为 DeepHLApan 的用户友好工具，该工具利用深度学习技术来预测新抗原，同时考虑了肽-HLA 结合亲和力和免疫原性。我们提供了 DeepHLApan 的应用，以及源代码、docker 版本和 web 服务器。这些资源可在 https://github.com/zjupgx/deephlapan 和 http://pgx.zju.edu.cn/deephlapan/ 免费获取。
