Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks

Calcium signaling data analysis has become increasing complex as the size of acquired datasets increases. In this paper we present a Ca(2+) signaling data analysis method that employs custom written software scripts deployed in a collection of Jupyter-Lab “notebooks” which were designed to cope with...

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Detalles Bibliográficos
Autores principales: Rugis, John, Chaffer, James, Sneyd, James, Yule, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312663/
https://www.ncbi.nlm.nih.gov/pubmed/37398053
http://dx.doi.org/10.1101/2023.06.13.544740
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author Rugis, John
Chaffer, James
Sneyd, James
Yule, David
author_facet Rugis, John
Chaffer, James
Sneyd, James
Yule, David
author_sort Rugis, John
collection PubMed
description Calcium signaling data analysis has become increasing complex as the size of acquired datasets increases. In this paper we present a Ca(2+) signaling data analysis method that employs custom written software scripts deployed in a collection of Jupyter-Lab “notebooks” which were designed to cope with this complexity. The notebook contents are organized to optimize data analysis workflow and efficiency. The method is demonstrated through application to several different Ca(2+) signaling experiment types.
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spelling pubmed-103126632023-07-01 Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks Rugis, John Chaffer, James Sneyd, James Yule, David bioRxiv Article Calcium signaling data analysis has become increasing complex as the size of acquired datasets increases. In this paper we present a Ca(2+) signaling data analysis method that employs custom written software scripts deployed in a collection of Jupyter-Lab “notebooks” which were designed to cope with this complexity. The notebook contents are organized to optimize data analysis workflow and efficiency. The method is demonstrated through application to several different Ca(2+) signaling experiment types. Cold Spring Harbor Laboratory 2023-06-14 /pmc/articles/PMC10312663/ /pubmed/37398053 http://dx.doi.org/10.1101/2023.06.13.544740 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Rugis, John
Chaffer, James
Sneyd, James
Yule, David
Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title_full Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title_fullStr Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title_full_unstemmed Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title_short Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks
title_sort tools for quantitative analysis of calcium signaling data using jupyter-lab notebooks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312663/
https://www.ncbi.nlm.nih.gov/pubmed/37398053
http://dx.doi.org/10.1101/2023.06.13.544740
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