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A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy
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 t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665986/ https://www.ncbi.nlm.nih.gov/pubmed/29093506 http://dx.doi.org/10.1038/s41598-017-14922-8 |
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author | Bermudez-Hernandez, Keria Keegan, Sarah Whelan, Donna R. Reid, Dylan A. Zagelbaum, Jennifer Yin, Yandong Ma, Sisi Rothenberg, Eli Fenyö, David |
author_facet | Bermudez-Hernandez, Keria Keegan, Sarah Whelan, Donna R. Reid, Dylan A. Zagelbaum, Jennifer Yin, Yandong Ma, Sisi Rothenberg, Eli Fenyö, David |
author_sort | Bermudez-Hernandez, Keria |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5665986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-56659862017-11-08 A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy Bermudez-Hernandez, Keria Keegan, Sarah Whelan, Donna R. Reid, Dylan A. Zagelbaum, Jennifer Yin, Yandong Ma, Sisi Rothenberg, Eli Fenyö, David Sci Rep Article 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. Nature Publishing Group UK 2017-11-01 /pmc/articles/PMC5665986/ /pubmed/29093506 http://dx.doi.org/10.1038/s41598-017-14922-8 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Bermudez-Hernandez, Keria Keegan, Sarah Whelan, Donna R. Reid, Dylan A. Zagelbaum, Jennifer Yin, Yandong Ma, Sisi Rothenberg, Eli Fenyö, David A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title | A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title_full | A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title_fullStr | A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title_full_unstemmed | A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title_short | A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy |
title_sort | method for quantifying molecular interactions using stochastic modelling and super-resolution microscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665986/ https://www.ncbi.nlm.nih.gov/pubmed/29093506 http://dx.doi.org/10.1038/s41598-017-14922-8 |
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