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Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisit...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567899/ https://www.ncbi.nlm.nih.gov/pubmed/37700120 http://dx.doi.org/10.1007/s00424-023-02855-3 |
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author | Stopper, Gebhard Caudal, Laura C. Rieder, Phillip Gobbo, Davide Stopper, Laura Felix, Lisa Everaerts, Katharina Bai, Xianshu Rose, Christine R. Scheller, Anja Kirchhoff, Frank |
author_facet | Stopper, Gebhard Caudal, Laura C. Rieder, Phillip Gobbo, Davide Stopper, Laura Felix, Lisa Everaerts, Katharina Bai, Xianshu Rose, Christine R. Scheller, Anja Kirchhoff, Frank |
author_sort | Stopper, Gebhard |
collection | PubMed |
description | Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisite for the analysis of physiological molecular signaling. Automated detection and analysis of fluorescence signals require to overcome several challenges, including correct estimation of fluorescence fluctuations at basal concentrations of messenger molecules, detection, and extraction of events themselves as well as proper segmentation of neighboring events. Moreover, event detection algorithms need to be sensitive enough to accurately capture localized and low amplitude events exhibiting a limited spatial extent. Here, we present two algorithms (PBasE and CoRoDe) for accurate baseline estimation and automated detection and segmentation of fluorescence fluctuations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00424-023-02855-3. |
format | Online Article Text |
id | pubmed-10567899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-105678992023-10-13 Novel algorithms for improved detection and analysis of fluorescent signal fluctuations Stopper, Gebhard Caudal, Laura C. Rieder, Phillip Gobbo, Davide Stopper, Laura Felix, Lisa Everaerts, Katharina Bai, Xianshu Rose, Christine R. Scheller, Anja Kirchhoff, Frank Pflugers Arch Neuroscience Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisite for the analysis of physiological molecular signaling. Automated detection and analysis of fluorescence signals require to overcome several challenges, including correct estimation of fluorescence fluctuations at basal concentrations of messenger molecules, detection, and extraction of events themselves as well as proper segmentation of neighboring events. Moreover, event detection algorithms need to be sensitive enough to accurately capture localized and low amplitude events exhibiting a limited spatial extent. Here, we present two algorithms (PBasE and CoRoDe) for accurate baseline estimation and automated detection and segmentation of fluorescence fluctuations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00424-023-02855-3. Springer Berlin Heidelberg 2023-09-13 2023 /pmc/articles/PMC10567899/ /pubmed/37700120 http://dx.doi.org/10.1007/s00424-023-02855-3 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Neuroscience Stopper, Gebhard Caudal, Laura C. Rieder, Phillip Gobbo, Davide Stopper, Laura Felix, Lisa Everaerts, Katharina Bai, Xianshu Rose, Christine R. Scheller, Anja Kirchhoff, Frank Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title | Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title_full | Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title_fullStr | Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title_full_unstemmed | Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title_short | Novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
title_sort | novel algorithms for improved detection and analysis of fluorescent signal fluctuations |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567899/ https://www.ncbi.nlm.nih.gov/pubmed/37700120 http://dx.doi.org/10.1007/s00424-023-02855-3 |
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