Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples, Pekka Ruusuvuori, Lassi Paavolainen, Kalle Rutanen, Anita Mäki, Heikki Huttunen, Varpu Marjomäki, PLoS ONE 9 (4), 2014.
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.
The effect of matching distance parameter on the matching accuracy:
Here is the data that were used for the experiments:
Here is the software that were used to compute the results:
Computational Systems Biology Research Group at the Department of Signal Processing, Tampere University of Technology.
Virus Entry and Regulation of Membrane Traffic at the Nanoscience Center / Department of Biological and Environmental Science, University of Jyväskylä.
Tampere University of Technology
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