Perfecting antigen prediction

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...

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Vydané v:The Journal of experimental medicine Ročník 219; číslo 9
Hlavní autori: Hoyos, David, Greenbaum, Benjamin D
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 05.09.2022
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ISSN:1540-9538, 1540-9538
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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content type line 23
ISSN:1540-9538
1540-9538
DOI:10.1084/jem.20220846