ReviewQuarterly reviews of biophysics2006
Computational biology in the study of cardiac ion channels and cell electrophysiology.
Review in Quarterly reviews of biophysics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 1 of them a synthesis that pooled it.
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
102 citing papers in PubMed, 1 synthesis or guideline pooled it, 273 citations in OpenAlex.
- Systems approach to understanding electromechanical activity in the human heart: a national heart, lung, and blood institute workshop summary.Circulation · 2008Guideline
- Exploring wave propagation dynamics in heterogeneous excitable media: effects of intermittent cellular inactivation.Frontiers in physiology · 2026Article
- Learning cardiac activation and repolarization times with operator learning.PLoS computational biology · 2026Article
- Electrophysiological Modeling and Molecular Dynamics Simulations of Cardiac Sodium Channels in Brugada Syndrome.BioMed research international · 2026Article
- Development and Clinical Validation of a Cross-Sex Translator of ECG Drug Responses.JACC. Clinical electrophysiology · 2025Article
- Reduced gap junction coupling amplifies the effects of cardiomyocyte variability and destabilizes the heartbeat.Physiological reports · 2025Article
- The effects of voltage dependence and ion-binding reaction rates on a thermodynamically constrained mathematical model of the Na/Ca exchanger.Scientific reports · 2025Article
- Electrodiffusion dynamics in the cardiomyocyte dyad at nano-scale resolution using the Poisson-Nernst-Planck (PNP) equations.PLoS computational biology · 2025Article
- Evaluating the predictive accuracy of ion-channel models using data from multiple experimental designs.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue.Scientific reports · 2024Article
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
- A range of voltage-clamp protocol designs for rapid capture of hERG kinetics.Wellcome open research · 2024Article
- The conducted vasomotor response and the principles of electrical communication in resistance arteries.Physiological reviews · 2024Review
- Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics.Bulletin of mathematical biology · 2023Article
- Diversity of cells and signals in the cardiovascular system.The Journal of physiology · 2023Article
- Emerging methods to model cardiac ion channel and myocyte electrophysiology.Biophysics reviews · 2023Review
- Dynamic mechanobiology of cardiac cells and tissues: Current status and future perspective.Biophysics reviews · 2023Review
- Models of the cardiac L-type calcium current: A quantitative review.WIREs mechanisms of disease · 2023Review
- Molecular Modeling of Cardiac Sodium Channel with Mexiletine.Membranes · 2022Article
- Deep learning to decompose macromolecules into independent Markovian domains.Nature communications · 2022Article
42 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The cardiac cell is a complex biological system where various processes interact to generate electrical excitation (the action potential, AP) and contraction. During AP generation, membrane ion channels interact nonlinearly with dynamically changing ionic concentrations and varying transmembrane voltage, and are subject to regulatory processes. In recent years, a large body of knowledge has accumulated on the molecular structure of cardiac ion channels, their function, and their modification by genetic mutations that are associated with cardiac arrhythmias and sudden death. However, ion channels are typically studied in isolation (in expression systems or isolated membrane patches), away from the physiological environment of the cell where they interact to generate the AP. A major challenge remains the integration of ion-channel properties into the functioning, complex and highly interactive cell system, with the objective to relate molecular-level processes and their modification by disease to whole-cell function and clinical phenotype. In this article we describe how computational biology can be used to achieve such integration. We explain how mathematical (Markov) models of ion-channel kinetics are incorporated into integrated models of cardiac cells to compute the AP. We provide examples of mathematical (computer) simulations of physiological and pathological phenomena, including AP adaptation to changes in heart rate, genetic mutations in SCN5A and HERG genes that are associated with fatal cardiac arrhythmias, and effects of the CaMKII regulatory pathway and beta-adrenergic cascade on the cell electrophysiological function.
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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.