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
Descripción
Sumario: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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