Author

Kimberly Young

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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Evolutionary Biology· 1 Neuroscience· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:spatial transcriptomics· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Organism:Drosophila· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Joseph BeechemiD· 2 shared Lidan WuiD· 2 shared Aaron Berliner· 1 shared Akua A. Agyemang· 1 shared Alicia AlonsoiD· 1 shared André F. RendeiroiD· 1 shared Arjumand Wani· 1 shared Ashley HeckiD· 1 shared

Activity by Year

2016-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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2 shared papersNeuroscience

Joseph BeechemORCID

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Author profile →

3 papers

Recent·Most cited

Single-cell Spatial Transcriptional Profiling Uncovers Heterogeneous Cellular Responses to Pathogenic Tau in a Mouse Model of Neurodegeneration

Xuehan Sun, Lidan Wu, Timothy C. Orr, Ashley Heck, Kimberly Young, Nathan Dunaway, Jose Ceja Navarro, Joseph Beechem, Miranda E. Orr

The paper uses single-cell spatial transcriptomics to analyze tau pathology in mouse brains, revealing cell-autonomous and non-autonomous effects of tau accumulation on gene expression and pathways.

bioRxiv · Nov 19, 2025 · PreprintNeuroscience

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

Jiwoon Park, Roberto De Gregorio, Erika Hissong, Elif Ozcelik, Nicholas Bartelo, Felipe Segato Dezem, Luke Zhang, Maycon Marção, Hannah Chasteen, Yimin Zheng, Ernesto Abila, Junbum Kim, Theodore M. Nelson, Jacqueline Proszynski, Akua A. Agyemang, , Christopher E. Mason

SAHA creates a multimodal, subcellular-resolution reference atlas of healthy human tissues, revealing spatial organization and disease-associated disruptions across multiple organ systems.

bioRxiv · Jun 16, 2025 · PreprintSystems Biology

Estimating seven coefficients of pairwise relatedness using population genomic data

Matthew Ackerman, Parul Johri, Ken Spitze, Thomas Doak, Kimberly Young, Michael Lynch, Sen Xu

This paper estimates seven pairwise relatedness coefficients from population genomic data and applies them to Daphnia pulex populations to identify related individuals and asexual clones.

bioRxiv · Apr 20, 2016Evolutionary Biology