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Garry P. Nolan

Researcher at Stanford University

Publications -  519
Citations -  54521

Garry P. Nolan is an academic researcher from Stanford University. The author has contributed to research in topics: Immune system & T cell. The author has an hindex of 104, co-authored 474 publications receiving 46025 citations. Previous affiliations of Garry P. Nolan include Massachusetts Institute of Technology & New York University.

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Journal ArticleDOI

Isolation and characterization of the gene for the murine T cell differentiation antigen and immunoglobulin-related molecule, Lyt-2

TL;DR: The sequence of the 5310 base pair Hind III-cleaved genomic DNA segment that includes the gene for the Lyt-2, a murine differentiation antigen expressed on most immature T lymphocytes as well as the cytotoxic suppressing T cell subset is presented.
Patent

Device and method for processing cell samples

Todd Covey, +1 more
TL;DR: A cell analysis device and method is described in this paper, which enables the user to efficiently treat cells in a sample by treating with reagents at a time and place proximate to collection and may be handled in a automated or semi automated fashion.
Posted ContentDOI

SARS-CoV-2 infects human adipose tissue and elicits an inflammatory response consistent with severe COVID-19

TL;DR: In this article, the authors demonstrate that human adipose tissue from multiple depots is permissive to SARS-CoV-2 infection and that infection elicits an inflammatory response, including the secretion of known inflammatory mediators of severe COVID-19.
Journal ArticleDOI

Single Cell Analysis and Selection of Living Retrovirus Vector-corrected Mucopolysaccharidosis VII Cells Using a Fluorescence-activated Cell Sorting-based Assay for Mammalian β-Glucuronidase Enzymatic Activity

TL;DR: A fluorescence-activated cell sorter-based assay is described for the quantitative analysis of β-glucuronidase activity in viable cells for the efficacy of gene therapy for mucopolysaccharidosis VII and it is revealed that sorted cells have elevated levels ofβ-glUCuronid enzyme activity and secrete higher levels of cross-correcting enzyme than the population from which they were sorted.
Journal ArticleDOI

A Cancer Biologist's Primer on Machine Learning Applications in High-Dimensional Cytometry.

TL;DR: This work introduces the reader to several keystone machine learning-based analytic approaches with an emphasis on defining key terms and introducing a conceptual framework for making translational or clinically relevant discoveries in cancer biology.