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- W4280654322 abstract "Systems immunology lacks a framework with which to derive theoretical understanding from high-dimensional datasets. We combined a robotic platform with machine learning to experimentally measure and theoretically model CD8+ T cell activation. High-dimensional cytokine dynamics could be compressed onto a low-dimensional latent space in an antigen-specific manner (so-called antigen encoding). We used antigen encoding to model and reconstruct patterns of T cell immune activation. The model delineated six classes of antigens eliciting distinct T cell responses. We generalized antigen encoding to multiple immune settings, including drug perturbations and activation of chimeric antigen receptor T cells. Such universal antigen encoding for T cell activation may enable further modeling of immune responses and their rational manipulation to optimize immunotherapies." @default.
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- W4280654322 date "2022-05-20" @default.
- W4280654322 modified "2023-10-10" @default.
- W4280654322 title "Universal antigen encoding of T cell activation from high-dimensional cytokine dynamics" @default.
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- W4280654322 doi "https://doi.org/10.1126/science.abl5311" @default.
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