Author

Galina Popova

University of California, San FranciscoORCID 0000-0001-8249-219XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Developmental Biology· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:human· 2 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Chang N. KimiD· 2 shared Tomasz Jan NowakowskiiD· 2 shared Agnieszka A. WendorffiD· 1 shared Albert WangiD· 1 shared Andy J. ChangiD· 1 shared Astrid GillichiD· 1 shared Baby Martin-McNulty· 1 shared Bernd J. WranikiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersDevelopmental Biology

Chang N. KimORCID

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3 papers

Recent·Most cited

NeurosciencebioRxivPreprintSep 2, 2025

Heterochronic myeloid cell replacement reveals the local brain environment as key driver of microglia aging

Claire Gizowski, Galina Popova, Heather Shin…·Oliver Hahn

This study uses heterochronic myeloid cell replacement to show that the local brain environment, not intrinsic factors, drives microglia aging.

3 citations

mousespatial transcriptomics

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Developmental BiologyeLifePeer-reviewedMay 23, 2023

Rubella virus tropism and single cell responses in human primary tissue and microglia-containing organoids

Galina Popova, Hanna Retallack, Chang N. Kim…·Tomasz Jan Nowakowski

This study investigates rubella virus tropism in human brain slices and organoids, showing microglia as the primary target and revealing an interferon response in non-microglial cells.

28 citationstop 3%

humanexperimental assay

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BioinformaticsMolecular Biology of the CellPeer-reviewedFeb 9, 2022

DynaMorph: self-supervised learning of morphodynamic states of live cells

Zhenqin Wu, Bryant B. Chhun, Galina Popova…·Shalin B. Mehta

DynaMorph uses self-supervised learning to analyze morphodynamic states of live human microglia, identifying distinct states and transitions in response to disease-relevant stimuli.

46 citationstop 5%

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