Machine learning inference of continuous single-cell state transitions during myoblast differentiation and fusion

Abstract Cells modify their internal organization during continuous state transitions, supporting functions from cell division to differentiation. However, tools to measure dynamic physiological states of individual transitioning cells are lacking. We combined live-cell imaging and machine learning...

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Bibliographic Details

Published in:	Molecular Systems Biology
Main Authors:	Amit Shakarchy, Giulia Zarfati, Adi Hazak, Reut Mealem, Karina Huk, Tamar Ziv, Ori Avinoam, Assaf Zaritsky
Format:	Article
Language:	English
Published:	Springer Nature 2024-01-01
Subjects:	State Transition Machine Learning Myogenesis Myoblast Fusion Differentiation
Online Access:	https://doi.org/10.1038/s44320-024-00010-3