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Sci Rep. 2017 Nov 1;7(1):14882. doi: 10.1038/s41598-017-14922-8.

A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy.

Author information

1
Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
2
Institute for Systems Genetics, New York University School of Medicine, New York, NY, USA.
3
Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA. eli.rothenberg@nyumc.org.
4
Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA. david@fenyolab.org.
5
Institute for Systems Genetics, New York University School of Medicine, New York, NY, USA. david@fenyolab.org.

Abstract

We introduce the Interaction Factor (IF), a measure for quantifying the interaction of molecular clusters in super-resolution microscopy images. The IF is robust in the sense that it is independent of cluster density, and it only depends on the extent of the pair-wise interaction between different types of molecular clusters in the image. The IF for a single or a collection of images is estimated by first using stochastic modelling where the locations of clusters in the images are repeatedly randomized to estimate the distribution of the overlaps between the clusters in the absence of interaction (IF = 0). Second, an analytical form of the relationship between IF and the overlap (which has the random overlap as its only parameter) is used to estimate the IF for the experimentally observed overlap. The advantage of IF compared to conventional methods to quantify interaction in microscopy images is that it is insensitive to changing cluster density and is an absolute measure of interaction, making the interpretation of experiments easier. We validate the IF method by using both simulated and experimental data and provide an ImageJ plugin for determining the IF of an image.

PMID:
29093506
PMCID:
PMC5665986
DOI:
10.1038/s41598-017-14922-8
[Indexed for MEDLINE]
Free PMC Article

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