Author

J. G. Meyerowitz

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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Biophysics· 2 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:cryo-EM· 2 Approach:experimental assay· 2 Research Focus:protein structure prediction· 2 Approach:biophysical modeling· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1

Frequent Co-Authors

G. Skiniotis· 2 shared M. J. Robertson· 2 shared O. Panova· 2 shared A. B. Seven· 1 shared A. S. Tsai· 1 shared B. A. Pinsky· 1 shared B. Gaudilliere· 1 shared C. M. Warren· 1 shared

Activity by Year

2021-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

G. Skiniotis

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Plasticity in Ligand Recognition at Somatostatin Receptors

M. J. Robertson, J. G. Meyerowitz, O. Panova, K. Borrelli, G. Skiniotis

The paper presents cryo-EM structures of SSTR2 with ligands and Gi protein, revealing ligand recognition mechanisms and subtype selectivity.

bioRxiv · Nov 2, 2021Biophysics

Structure Determination of Inactive-State GPCRs with a Universal Nanobody

M. J. Robertson, M. M. Papasergi-Scott, F. He, A. B. Seven, J. G. Meyerowitz, O. Panova, M.-C. Peroto, T. Che, G. Skiniotis

This paper uses nanobodies to determine cryo-EM structures of inactive-state GPCRs, achieving resolutions comparable to X-ray crystallography and providing insights into ligand binding.

bioRxiv · Nov 2, 2021Biophysics

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

D. Feyaerts, J. Hedou, J. Gillard, H. Chen, E. S. Tsai, L. S. Peterson, K. Ando, M. Manohar, E. Do, G. K. R. Dhondalay, J. Fitzpatrick, M. Artandi, I. Chang, T. T. Snow, R. S. Chinthrajah, , D. R. McIlwain

This study integrates plasma proteomics and single-cell immune features to classify COVID-19 severity and identify biological signatures of disease progression.

bioRxiv · Feb 9, 2021Immunology