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Updated: Aug 26, 2025

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Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
Published on: March 3, 2023
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Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations
Ritvik Vasan1, Meagan P Rowan2, Christopher T Lee1
1Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, United States.
Abstract:
In this perspective, we examine three key aspects of an end-to-end pipeline for realistic cellular simulations: reconstruction and segmentation of cellular structures; generation of cellular structures; and mesh generation, simulation, and data analysis. We highlight some of the relevant prior work in these distinct but overlapping areas, with a particular emphasis on current use of machine learning technologies, as well as on future opportunities.

