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The random walker's toolbox for analyzing single-particle tracking data

Title data

Rehfeldt, Florian ; Weiss, Matthias:
The random walker's toolbox for analyzing single-particle tracking data.
In: Soft Matter. Vol. 19 (2023) Issue 28 . - pp. 5206-5222.
ISSN 1744-6848
DOI: https://doi.org/10.1039/D3SM00557G

Official URL: Volltext

Abstract in another language

Technological advances and a burst of new microscopy methods have boosted the use of quantitative tracking experiments, in Soft Matter and Biological Physics but also in the Life Sciences. However, in contrast to highly advanced measurement techniques and tracking tools, subsequent analyses of trajectories frequently do not exploit the data's full potential. Aiming especially at experimental laboratories and early-career scientists, we introduce, discuss, and apply in this Tutorial Review a large set of versatile measures that have proven to be useful for analyzing trajectories from single-particle tracking experiments, beyond a simple extraction of diffusion constants from mean squared displacements. To support a direct test and application of these measures, we supplement the text with a download package that comprises a low-threshold toolbox of ready-to-use routines and training data sets, hence relaxing the need to develop home-brewed solutions and/or to create suitable benchmark data.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Physics > Chair Experimental Physics I - Physics of Living Matter > Chair Experimental Physics I - Physics of Living Matter - Univ.-Prof. Dr. Matthias Weiss
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Physics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Physics > Chair Experimental Physics I - Physics of Living Matter
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 530 Physics
500 Science > 570 Life sciences, biology
Date Deposited: 21 Jul 2023 06:20
Last Modified: 21 Nov 2023 14:38
URI: https://eref.uni-bayreuth.de/id/eprint/86237