Article

Dynamics of ML-based Morphological Features Indicate a Shear Stress-Dependent Bifurcation of hiPSC-Derived Endothelial Cell States

2026-07-11

Abstract excerpt

Cell states are increasingly conceptualized as attractors of high-dimensional dynamical systems, yet quantitative approaches for integrating phenotypic information into this framework remain limited. Here, we take an image-based approach that combines unsupervised machine learning (ML) with timelapse imaging to extract and characterize the temporal dynamics of morphological features. Using a cell line with endogen...

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Literature Corpus work: f2cbdcee-518e-5f28-90e5-5ffcaeae52af
DOI: 10.64898/2026.07.07.736803

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Dynamics of ML-based Morphological Features Indicate a Shear Stress-Dependent Bifurcation of hiPSC-Derived Endothelial Cell StatesDOI 10.64898/2026.07.07.736803Read

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