Please use this identifier to cite or link to this item: doi:10.22028/D291-40760
Title: Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
Author(s): Stopper, Gebhard
Caudal, Laura C.
Rieder, Phillip
Gobbo, Davide
Stopper, Laura
Felix, Lisa
Everaerts, Katharina
Bai, Xianshu
Rose, Christine R.
Scheller, Anja
Kirchhoff, Frank
Language: English
Title: Pflügers Archiv
Volume: 475
Issue: 11
Pages: 1283-1300
Publisher/Platform: Springer Nature
Year of Publication: 2023
Free key words: Calcium signal analysis
ROI detection
Background correction
Transient classifcation
Interactive user interface
Glial calcium signals
Neuronal SBFI imaging
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: Fluorescent dyes and genetically encoded fuorescence indicators (GEFI) are common tools for visualizing concentration changes of specifc ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fuorescence indicators are a prerequisite for the analysis of physiological molecular signaling. Automated detection and analysis of fuorescence signals require to overcome several challenges, including correct estimation of fuorescence fuctuations 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 fuorescence fuctuations.
DOI of the first publication: 10.1007/s00424-023-02855-3
URL of the first publication: https://doi.org/10.1007/s00424-023-02855-3
Link to this record: urn:nbn:de:bsz:291--ds-407608
hdl:20.500.11880/36632
http://dx.doi.org/10.22028/D291-40760
ISSN: 1432-2013
0031-6768
Date of registration: 19-Oct-2023
Description of the related object: Supplementary information
Related object: https://static-content.springer.com/esm/art%3A10.1007%2Fs00424-023-02855-3/MediaObjects/424_2023_2855_MOESM1_ESM.docx
Faculty: M - Medizinische Fakultät
Department: M - Physiologie
Professorship: M - Prof. Dr. Frank Kirchhoff
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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