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in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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-scale in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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-scale in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental
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understand how genetic variation shapes biological function. At the heart of our research is MAGESTIC ( https://doi.org/10.1038/nbt.4137 ), a CRISPR-based technology that enables precise engineering of
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technologies to understand how genetic variation shapes biological function. At the heart of our research is MAGESTIC ( https://doi.org/10.1038/nbt.4137 ), a CRISPR-based technology that enables precise