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OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework

Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed t...

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Detalles Bibliográficos
Autores principales: Garcia, Samuel, Fourcaud-Trocmé, Nicolas
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694696/
https://www.ncbi.nlm.nih.gov/pubmed/19521545
http://dx.doi.org/10.3389/neuro.11.014.2009
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author Garcia, Samuel
Fourcaud-Trocmé, Nicolas
author_facet Garcia, Samuel
Fourcaud-Trocmé, Nicolas
author_sort Garcia, Samuel
collection PubMed
description Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed to fill this niche. It stores all experiment data and meta-data in a single central MySQL database, and provides a graphic user interface to visualize and explore the data, and a library of functions for user analysis scripting in Python. It implements multiple spike-sorting methods, and oscillation detection based on the ridge extraction methods due to Roux et al. (2007). OpenElectrophy is open source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy.
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spelling pubmed-26946962009-06-11 OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework Garcia, Samuel Fourcaud-Trocmé, Nicolas Front Neuroinformatics Neuroscience Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed to fill this niche. It stores all experiment data and meta-data in a single central MySQL database, and provides a graphic user interface to visualize and explore the data, and a library of functions for user analysis scripting in Python. It implements multiple spike-sorting methods, and oscillation detection based on the ridge extraction methods due to Roux et al. (2007). OpenElectrophy is open source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy. Frontiers Research Foundation 2009-05-27 /pmc/articles/PMC2694696/ /pubmed/19521545 http://dx.doi.org/10.3389/neuro.11.014.2009 Text en Copyright © 2009 Garcia and Fourcaud-Trocmé. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
spellingShingle Neuroscience
Garcia, Samuel
Fourcaud-Trocmé, Nicolas
OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title_full OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title_fullStr OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title_full_unstemmed OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title_short OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
title_sort openelectrophy: an electrophysiological data- and analysis-sharing framework
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694696/
https://www.ncbi.nlm.nih.gov/pubmed/19521545
http://dx.doi.org/10.3389/neuro.11.014.2009
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