Author

Samuel G. Berryman

University of British ColumbiaORCID 0009-0005-2288-6791Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:fluorescence / live-cell microscopy· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Hongshen MaiD· 2 shared Simon P. DuffyiD· 2 shared Deasung JangiD· 1 shared Jeong Hyun LeeiD· 1 shared Kerryn MatthewsiD· 1 shared Pan Deng· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 11 mutual co-author links

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2 shared papersBioengineering

Hongshen MaORCID

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2 papers

Recent·Most cited

BioengineeringSmall MethodsPeer-reviewedJan 23, 2026

Regularized Single-cell Imaging Enables Generalizable AI models for Stain-free Cell Viability Screening

Pan Deng, Deasung Jang, Samuel G. Berryman…·Hongshen Ma

Regularized single-cell imaging in nanowells enables training of generalizable AI models for accurate, stain-free viability screening across previously unseen cell types and contexts.

1 citation

fluorescence / live-cell microscopydeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 24, 2019

Image-based Cell Phenotyping Using Deep Learning

Samuel G. Berryman, Kerryn Matthews, Jeong Hyun Lee…·Hongshen Ma

This paper develops a deep learning method to phenotype cells using low-resolution microscopy images, achieving 94.6% accuracy in identifying cancer cell lines.

5 citations

humanimaging

𝕏 PostBluesky