Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before di...

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Bibliographic Details
Main Authors: Sierra M Barone, Alberta GA Paul, Lyndsey M Muehling, Joanne A Lannigan, William W Kwok, Ronald B Turner, Judith A Woodfolk, Jonathan M Irish
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2021-08-01
Series:eLife
Subjects:
machine learning
rhinovirus
COVID-19
immune monitoring
systems biology
cytometry
Online Access:https://elifesciences.org/articles/64653

Internet

https://elifesciences.org/articles/64653

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