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...
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: | |
Online Access: | https://elifesciences.org/articles/64653 |
Similar Items
-
Novel Human Rhinoviruses and Exacerbation of Asthma in Children
by: Nino Khetsuriani, et al.
Published: (2008-11-01) -
Studies on the acid lability of rhinoviruses.
by: Hughes, John Henry
Published: (1972) -
Genetic studies on the rhinovirus subgroup of picornaviruses /
by: Evans, Martin Rupert
Published: (1977) -
Rhinovirus – From bench to bedside
by: Kelvin K.W. To, et al.
Published: (2017-07-01) -
Mechanisms of Rhinovirus Neutralisation by Antibodies
by: Lila Touabi, et al.
Published: (2021-02-01)