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Perfecting antigen prediction

delete2022-08-16
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OA
AI
D
David Hoyos
B
Benjamin D. Greenbaum *
DOI:10.1084/jem.20220846delete
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摘要

摘要

En 中文
Advances in genomics and precision measurement have continued to demonstrate the importance of the immune system across many disease types. At the heart of many emerging approaches to leverage these insights for precision immunotherapies is the computational antigen prediction problem. We propose a threefold approach to improving antigen predictions: further defining the geometry of the antigen landscape, incorporating the coupling of antigen recognition to other cellular processes, and diversifying the training sets used for models that predict immunogenicity.
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期刊

J
Journal of Experimental Medicine
IF:
10.6
论文数:
2.4W
被引数:
6.2W

机构

M
Memorial Sloan Kettering Cancer Center
学者数:
3.4W
论文数: 2.4W
被引数: 4.6W
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