Author

William Taylor Kimberly

Harvard UniversityORCID 0000-0002-2519-8530Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Assay:imaging· 1 Assay:metabolomics· 1

Frequent Co-Authors

Amelia DemopoulosiD· 2 shared Adam de HavenoniD· 1 shared Alzheimer’s Disease Neuroimaging Initiative· 1 shared Annabel Sorby‐AdamsiD· 1 shared Ava D. FarnaniD· 1 shared Chaitali S. DagliiD· 1 shared Dina Zemlyanker· 1 shared Eric Adjei BoakyeiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Amelia DemopoulosORCID

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2 papers

Recent·Most cited

Metabolomic and Lipidomic Signatures of Depressive Symptoms in the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study

Chaitali S. Dagli, Nicole D. Armstrong, Pranali G. Patel, Eric Adjei Boakye, Zsuzsanna Ament, Amelia Demopoulos, Hermant K. Tiwari, Virginia J. Howard, William Taylor Kimberly, Marguerite R. Irvin

The paper identifies metabolomic and lipidomic associations with depressive symptoms in the REGARDS study, finding significant longitudinal links between certain lipids and depressive symptoms, with sex-specific differences.

medRxiv · Aug 12, 2026 · PreprintGenetic & Genomic Medicine

On the accuracy of image registration in portable low-field 3D brain MRI

Juan Eugenio Iglesias, Ian P. Johnson, Jonathan Williams-Ramirez, Dina Zemlyanker, Lin Tian, Karthik Kuduva Gopinath, Mark Olchanyi, Ava D. Farnan, Amelia Demopoulos, Matthew Scott Rosen, Kevin Navin Sheth, Adam de Havenon, William Taylor Kimberly, Annabel Sorby‐Adams, Alzheimer’s Disease Neuroimaging Initiative

This study evaluates image registration accuracy in portable low-field 3D brain MRI, finding that synthesis-based methods perform best despite acquisition artifacts.

bioRxiv · Feb 14, 2026 · PreprintNeuroscience