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28 September 2023 Exploring spatiotemporal dynamics in living cells through a data-driven approach
Carlo Manzo
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Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC126550N (2023) https://doi.org/10.1117/12.2676671
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States
Abstract
Observing the dynamics of living cells and subcellular components is crucial for understanding fundamental biological processes. Time-lapse microscopy at the cellular and molecular level is a valuable tool for this purpose, but extracting quantitative information from these experiments can be challenging. In this talk, I will present our advances in data-driven methods for object tracking and analysis, including machine learning algorithms that offer remarkable improvements over classical methods. Specifically, I will discuss the results of an objective assessment of the performance of these methods for trajectory analysis and their follow-up applications. Furthermore, I will introduce novel strategies that we are currently developing to move beyond the tracking-by-detection paradigm. Through these methods, we hope to uncover new insights into the interactions between cellular components and their role in signaling and function regulation.
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Carlo Manzo "Exploring spatiotemporal dynamics in living cells through a data-driven approach", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550N (28 September 2023); https://doi.org/10.1117/12.2676671
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KEYWORDS
Biological research
Detection and tracking algorithms
Machine learning
Time lapse microscopy
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