Author

Myrna Chang

University of Wisconsin–Madison

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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Bioengineering· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:fluorescence / live-cell microscopy· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Research Focus:spatial domain detection· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Dominique R. SmithiD· 2 shared Joshua M. BrockmaniD· 2 shared Kartikey KansaliD· 2 shared Hemakshi J. Mishra· 1 shared Hemakshi MishraiD· 1 shared Juan C. CaicedoiD· 1 shared Lauren MahoneyiD· 1 shared Luke Kalcheim· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioengineering

Dominique R. SmithORCID

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2 papers

Recent·Most cited

Prediction of Piconewton Receptor Tension Images using Deep Learning

Kartikey Kansal, Monica Umesh, Myrna Chang, Dominique R. Smith, Hemakshi Mishra, Juan C. Caicedo, Joshua M. Brockman

This paper introduces TensionDL, a deep learning model that predicts pN receptor tension maps from cell morphology and vinculin images, validated across cell types and substrate stiffnesses.

bioRxiv · Dec 23, 2025 · PreprintBioengineering

Chimeric Antigen Receptors Transmit Co-stimulatory Domain Dependent Piconewton Forces to their Target

Hemakshi J. Mishra, Lauren Mahoney, Dominique R. Smith, Luke Kalcheim, Kartikey Kansal, Nat Murren, Myrna Chang, Rebecca M. Richards, Joshua M. Brockman

This study measures piconewton forces transmitted by CARs during antigen engagement, showing co-stimulatory domains are essential for force generation and early signaling.

bioRxiv · Oct 22, 2025 · PreprintImmunology