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MuscleJ: a high-content analysis method to study skeletal muscle with a new Fiji tool

Abstract : Skeletal muscle has the capacity to adapt to environmental changes and regenerate upon injury. To study these processes, most experimental methods use quantification of parameters obtained from images of immunostained skeletal muscle. Muscle cross-sectional area, fiber typing, localization of nuclei within the muscle fiber, the number of vessels, and fiber-associated stem cells are used to assess muscle physiology. Manual quantification of these parameters is time consuming and only poorly reproducible. While current state-of-the-art software tools are unable to analyze all these parameters simultaneously, we have developed MuscleJ, a new bioinformatics tool to do so.
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Submitted on : Monday, November 19, 2018 - 10:02:15 AM
Last modification on : Wednesday, October 21, 2020 - 3:41:57 AM
Long-term archiving on: : Wednesday, February 20, 2019 - 12:54:38 PM

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Alicia Mayeuf-Louchart, David Hardy, Quentin Thorel, Pascal Roux, Lorna Gueniot, et al.. MuscleJ: a high-content analysis method to study skeletal muscle with a new Fiji tool. Skeletal Muscle, BioMed Central, 2018, 8 (1), pp.25. ⟨10.1186/s13395-018-0171-0⟩. ⟨pasteur-01926223⟩

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