Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples
Ruusuvuori, P., Paavolainen, L., Rutanen, K., Mäki, A., Huttunen, H., & Marjomäki, V. (2014). Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples. PLoS ONE, 9(1), Article e94245. https://doi.org/10.1371/journal.pone.0094245
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2014Copyright
© 2014 Ruusuvuori et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of
rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also
introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our
approach to quantifying the association between tagged proteins is to use an object-based method where the exact match
of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets
under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between
image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern
matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where
traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest
Points registration method. Results for fixed and live experimental data shows the association method to perform
comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for
live cells.
...


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