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Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications
Fluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the quantitative measurement of biomolecular dynamics and interactions. Improvements in biology, computation, and detection technology enable real-time FCS experiments with multiplexed detection even in vivo. These n...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328937/ https://www.ncbi.nlm.nih.gov/pubmed/37419967 http://dx.doi.org/10.1038/s42003-023-05069-6 |
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author | Sankaran, Jagadish Wohland, Thorsten |
author_facet | Sankaran, Jagadish Wohland, Thorsten |
author_sort | Sankaran, Jagadish |
collection | PubMed |
description | Fluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the quantitative measurement of biomolecular dynamics and interactions. Improvements in biology, computation, and detection technology enable real-time FCS experiments with multiplexed detection even in vivo. These new imaging modalities of FCS generate data at the rate of hundreds of MB/s requiring efficient data processing tools to extract information. Here, we briefly review FCS’s capabilities and limitations before discussing recent directions that address these limitations with a focus on imaging modalities of FCS, their combinations with super-resolution microscopy, new evaluation strategies, especially machine learning, and applications in vivo. |
format | Online Article Text |
id | pubmed-10328937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103289372023-07-09 Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications Sankaran, Jagadish Wohland, Thorsten Commun Biol Mini Review Fluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the quantitative measurement of biomolecular dynamics and interactions. Improvements in biology, computation, and detection technology enable real-time FCS experiments with multiplexed detection even in vivo. These new imaging modalities of FCS generate data at the rate of hundreds of MB/s requiring efficient data processing tools to extract information. Here, we briefly review FCS’s capabilities and limitations before discussing recent directions that address these limitations with a focus on imaging modalities of FCS, their combinations with super-resolution microscopy, new evaluation strategies, especially machine learning, and applications in vivo. Nature Publishing Group UK 2023-07-07 /pmc/articles/PMC10328937/ /pubmed/37419967 http://dx.doi.org/10.1038/s42003-023-05069-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Mini Review Sankaran, Jagadish Wohland, Thorsten Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title | Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title_full | Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title_fullStr | Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title_full_unstemmed | Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title_short | Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications |
title_sort | current capabilities and future perspectives of fcs: super-resolution microscopy, machine learning, and in vivo applications |
topic | Mini Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328937/ https://www.ncbi.nlm.nih.gov/pubmed/37419967 http://dx.doi.org/10.1038/s42003-023-05069-6 |
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