Automated Analysis of Intracellular Dynamic Processes

Publication date

2017

Authors

Yao, Yao
Smal, Ihor
Grigoriev, IlyaISNI 0000000492860971
Martin, Melissa JISNI 000000050602529X
Akhmanova, AnnaISNI 0000000390996464
Meijering, Erik

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

taverne

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.

Keywords

Intracellular dynamics, fluorescence microscopy, image analysis, particle tracking, trajectory analysis, feature extraction, feature visualization, software tools, Taverne

Citation

Yao, Y, Smal, I, Grigoriev, I, Martin, M, Akhmanova, A & Meijering, E 2017, 'Automated Analysis of Intracellular Dynamic Processes', Methods in Molecular Biology, vol. 1563, pp. 209-228. https://doi.org/10.1007/978-1-4939-6810-7_14