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TRAP:一种对比学习增强的框架,用于强大的TCR-pMHC绑定预测,并具有更好的概括性

Jingxuan Ge1,2, Jike Wang1,2, Qing Ye1

  • 1College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China kimhsieh@zju.edu.cn tingjunhou@zju.edu.cn.

Chemical science
|May 5, 2025
PubMed
概括

新的机器学习模型TRAP准确地预测T细胞受体 (TCR) 和-MHC (pMHC) 的结合. 它通过优于现有模型的性能来改善免疫疗法开发,特别是与新型表征.

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