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The Cardiac Electrophysiology Web Lab

Computational modeling of cardiac cellular electrophysiology has a long history, and many models are now available for different species, cell types, and experimental preparations. This success brings with it a challenge: how do we assess and compare the underlying hypotheses and emergent behaviors...

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Detalles Bibliográficos
Autores principales: Cooper, Jonathan, Scharm, Martin, Mirams, Gary R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Biophysical Society 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724653/
https://www.ncbi.nlm.nih.gov/pubmed/26789753
http://dx.doi.org/10.1016/j.bpj.2015.12.012
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author Cooper, Jonathan
Scharm, Martin
Mirams, Gary R.
author_facet Cooper, Jonathan
Scharm, Martin
Mirams, Gary R.
author_sort Cooper, Jonathan
collection PubMed
description Computational modeling of cardiac cellular electrophysiology has a long history, and many models are now available for different species, cell types, and experimental preparations. This success brings with it a challenge: how do we assess and compare the underlying hypotheses and emergent behaviors so that we can choose a model as a suitable basis for a new study or to characterize how a particular model behaves in different scenarios? We have created an online resource for the characterization and comparison of electrophysiological cell models in a wide range of experimental scenarios. The details of the mathematical model (quantitative assumptions and hypotheses formulated as ordinary differential equations) are separated from the experimental protocol being simulated. Each model and protocol is then encoded in computer-readable formats. A simulation tool runs virtual experiments on models encoded in CellML, and a website (https://chaste.cs.ox.ac.uk/WebLab) provides a friendly interface, allowing users to store and compare results. The system currently contains a sample of 36 models and 23 protocols, including current-voltage curve generation, action potential properties under steady pacing at different rates, restitution properties, block of particular channels, and hypo-/hyperkalemia. This resource is publicly available, open source, and free, and we invite the community to use it and become involved in future developments. Investigators interested in comparing competing hypotheses using models can make a more informed decision, and those developing new models can upload them for easy evaluation under the existing protocols, and even add their own protocols.
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spelling pubmed-47246532017-01-19 The Cardiac Electrophysiology Web Lab Cooper, Jonathan Scharm, Martin Mirams, Gary R. Biophys J Computational Tool Computational modeling of cardiac cellular electrophysiology has a long history, and many models are now available for different species, cell types, and experimental preparations. This success brings with it a challenge: how do we assess and compare the underlying hypotheses and emergent behaviors so that we can choose a model as a suitable basis for a new study or to characterize how a particular model behaves in different scenarios? We have created an online resource for the characterization and comparison of electrophysiological cell models in a wide range of experimental scenarios. The details of the mathematical model (quantitative assumptions and hypotheses formulated as ordinary differential equations) are separated from the experimental protocol being simulated. Each model and protocol is then encoded in computer-readable formats. A simulation tool runs virtual experiments on models encoded in CellML, and a website (https://chaste.cs.ox.ac.uk/WebLab) provides a friendly interface, allowing users to store and compare results. The system currently contains a sample of 36 models and 23 protocols, including current-voltage curve generation, action potential properties under steady pacing at different rates, restitution properties, block of particular channels, and hypo-/hyperkalemia. This resource is publicly available, open source, and free, and we invite the community to use it and become involved in future developments. Investigators interested in comparing competing hypotheses using models can make a more informed decision, and those developing new models can upload them for easy evaluation under the existing protocols, and even add their own protocols. The Biophysical Society 2016-01-19 2016-01-19 /pmc/articles/PMC4724653/ /pubmed/26789753 http://dx.doi.org/10.1016/j.bpj.2015.12.012 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computational Tool
Cooper, Jonathan
Scharm, Martin
Mirams, Gary R.
The Cardiac Electrophysiology Web Lab
title The Cardiac Electrophysiology Web Lab
title_full The Cardiac Electrophysiology Web Lab
title_fullStr The Cardiac Electrophysiology Web Lab
title_full_unstemmed The Cardiac Electrophysiology Web Lab
title_short The Cardiac Electrophysiology Web Lab
title_sort cardiac electrophysiology web lab
topic Computational Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724653/
https://www.ncbi.nlm.nih.gov/pubmed/26789753
http://dx.doi.org/10.1016/j.bpj.2015.12.012
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