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Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis

Open source analytical software for the analysis of electrophysiological cardiomyocyte data offers a variety of new functionalities to complement closed-source, proprietary tools. Here, we present the Cardio PyMEA application, a free, modifiable, and open source program for the analysis of microelec...

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Autores principales: Dunham, Christopher S., Mackenzie, Madelynn E., Nakano, Haruko, Kim, Alexis R., Nakano, Atsushi, Stieg, Adam Z., Gimzewski, James K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135279/
https://www.ncbi.nlm.nih.gov/pubmed/35617323
http://dx.doi.org/10.1371/journal.pone.0266647
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author Dunham, Christopher S.
Mackenzie, Madelynn E.
Nakano, Haruko
Kim, Alexis R.
Nakano, Atsushi
Stieg, Adam Z.
Gimzewski, James K.
author_facet Dunham, Christopher S.
Mackenzie, Madelynn E.
Nakano, Haruko
Kim, Alexis R.
Nakano, Atsushi
Stieg, Adam Z.
Gimzewski, James K.
author_sort Dunham, Christopher S.
collection PubMed
description Open source analytical software for the analysis of electrophysiological cardiomyocyte data offers a variety of new functionalities to complement closed-source, proprietary tools. Here, we present the Cardio PyMEA application, a free, modifiable, and open source program for the analysis of microelectrode array (MEA) data obtained from cardiomyocyte cultures. Major software capabilities include: beat detection; pacemaker origin estimation; beat amplitude and interval; local activation time, upstroke velocity, and conduction velocity; analysis of cardiomyocyte property-distance relationships; and robust power law analysis of pacemaker spatiotemporal instability. Cardio PyMEA was written entirely in Python 3 to provide an accessible, integrated workflow that possesses a user-friendly graphical user interface (GUI) written in PyQt5 to allow for performant, cross-platform utilization. This application makes use of object-oriented programming (OOP) principles to facilitate the relatively straightforward incorporation of custom functionalities, e.g. power law analysis, that suit the needs of the user. Cardio PyMEA is available as an open source application under the terms of the GNU General Public License (GPL). The source code for Cardio PyMEA can be downloaded from Github at the following repository: https://github.com/csdunhamUC/cardio_pymea.
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spelling pubmed-91352792022-05-27 Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis Dunham, Christopher S. Mackenzie, Madelynn E. Nakano, Haruko Kim, Alexis R. Nakano, Atsushi Stieg, Adam Z. Gimzewski, James K. PLoS One Research Article Open source analytical software for the analysis of electrophysiological cardiomyocyte data offers a variety of new functionalities to complement closed-source, proprietary tools. Here, we present the Cardio PyMEA application, a free, modifiable, and open source program for the analysis of microelectrode array (MEA) data obtained from cardiomyocyte cultures. Major software capabilities include: beat detection; pacemaker origin estimation; beat amplitude and interval; local activation time, upstroke velocity, and conduction velocity; analysis of cardiomyocyte property-distance relationships; and robust power law analysis of pacemaker spatiotemporal instability. Cardio PyMEA was written entirely in Python 3 to provide an accessible, integrated workflow that possesses a user-friendly graphical user interface (GUI) written in PyQt5 to allow for performant, cross-platform utilization. This application makes use of object-oriented programming (OOP) principles to facilitate the relatively straightforward incorporation of custom functionalities, e.g. power law analysis, that suit the needs of the user. Cardio PyMEA is available as an open source application under the terms of the GNU General Public License (GPL). The source code for Cardio PyMEA can be downloaded from Github at the following repository: https://github.com/csdunhamUC/cardio_pymea. Public Library of Science 2022-05-26 /pmc/articles/PMC9135279/ /pubmed/35617323 http://dx.doi.org/10.1371/journal.pone.0266647 Text en © 2022 Dunham et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dunham, Christopher S.
Mackenzie, Madelynn E.
Nakano, Haruko
Kim, Alexis R.
Nakano, Atsushi
Stieg, Adam Z.
Gimzewski, James K.
Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title_full Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title_fullStr Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title_full_unstemmed Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title_short Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
title_sort cardio pymea: a user-friendly, open-source python application for cardiomyocyte microelectrode array analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135279/
https://www.ncbi.nlm.nih.gov/pubmed/35617323
http://dx.doi.org/10.1371/journal.pone.0266647
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