Abstract
The study of intracellular dynamic processes is of fundamental importance for understanding a wide variety of diseases and developing effective drugs and therapies. Advanced fluorescence microscopy imaging systems nowadays allow the recording of virtually any type of process in space and time with super-resolved detail and with high sensitivity and specificity. The large volume and high information content of the resulting image data, and the desire to obtain objective, quantitative descriptions and biophysical models of the processes of interest, require a high level of automation in data analysis. Two key tasks in extracting biologically meaningful information about intracellular dynamics from image data are particle tracking and particle trajectory analysis. Here we present state-of-the-art software tools for these tasks and describe how to use them.
*These authors contributed equally to this work
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Acknowledgments
This work was supported by the Dutch Technology Foundation (STW Grants 10443 and 13391).
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Yao, Y., Smal, I., Grigoriev, I., Martin, M., Akhmanova, A., Meijering, E. (2017). Automated Analysis of Intracellular Dynamic Processes. In: Markaki, Y., Harz, H. (eds) Light Microscopy. Methods in Molecular Biology, vol 1563. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6810-7_14
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DOI: https://doi.org/10.1007/978-1-4939-6810-7_14
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