Author

E. McGowan

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Immunology· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Assay:proteomics· 1 Organism:rat· 1

Frequent Co-Authors

A. Fiore-Gartland· 1 shared A. Kapaata· 1 shared B. YIN· 1 shared C. Streatfield· 1 shared D. Monaco· 1 shared D. Morrison· 1 shared E. Hunter· 1 shared E. Muok· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperImmunology

A. Fiore-Gartland

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2 papers

Recent·Most cited

Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0 identifies proteins enriched within inflammatory lesions in tissue sections and human clinical biopsies.

B. YIN, L. R. Caggiano, R.-C. Li, E. McGowan, J. W. Holmes, S. E. Ewald

AutoSTOMP 2.0 identifies proteins in specific regions of tissue sections and biopsies, revealing inflammatory proteins in cardiac infarcts and IgG4+ lesions.

bioRxiv · Mar 19, 2021 · PreprintImmunology

Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response

E. McGowan, R. Rosenthal, A. Fiore-Gartland, G. Macharia, S. Balinda, A. Kapaata, E. Muok, G. Umviligihozo, J. Dalel, C. Streatfield, H. Coutinho, D. Monaco, D. Morrison, L. Yue, E. Hunter, , J. Hare

The paper uses computational models to identify immunogenic regions in the HIV proteome by analyzing HLA diversity and CD8 T-cell immune repertoires, offering a pipeline for vaccine design.

bioRxiv · Aug 15, 2020Immunology