ArticleBiophysical journal2016
The Cardiac Electrophysiology Web Lab.
Article in Biophysical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Comparison of in silico predictions of action potential duration in response to inhibition of IKr and ICaL with new human ex vivo recordings.PLoS computational biology · 2025Article
- Models of the cardiac L-type calcium current: A quantitative review.WIREs mechanisms of disease · 2023Review
- A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability.Bulletin of mathematical biology · 2022Article
- Seven challenges in the multiscale modeling of multicellular tissues.WIREs mechanisms of disease · 2022Review
- NLIMED: Natural Language Interface for Model Entity Discovery in Biosimulation Model Repositories.Frontiers in physiology · 2022Article
- A Parameter Representing Missing Charge Should Be Considered when Calibrating Action Potential Models.Frontiers in physiology · 2022Article
- Article
- Electrophysiological characterization of the hERG R56Q LQTS variant and targeted rescue by the activator RPR260243.The Journal of general physiology · 2021Article
- cellmlmanip and chaste_codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians.Wellcome open research · 2021Article
- Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence.Biophysical journal · 2019Article
- Required GBiophysical journal · 2019Article
- A demonstration of modularity, reuse, reproducibility, portability and scalability for modeling and simulation of cardiac electrophysiology using Kepler Workflows.PLoS computational biology · 2019Article
- Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Reproducible model development in the cardiac electrophysiology Web Lab.Progress in biophysics and molecular biology · 2018Article
- Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.The Journal of physiology · 2018Article
- Notions of similarity for systems biology models.Briefings in bioinformatics · 2018Article
- Identifying frequent patterns in biochemical reaction networks: a workflow.Database : the journal of biological databases and curation · 2018Article
- Validation and Trustworthiness of Multiscale Models of Cardiac Electrophysiology.Frontiers in physiology · 2018Review
- MAGPIE: Simplifying access and execution of computational models in the life sciences.PLoS computational biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.