ReviewThe Journal of physiology2012
Exploiting mathematical models to illuminate electrophysiological variability between individuals.
Review in The Journal of physiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.
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Who cites it
83 citing papers in PubMed.
- Role of natural inter-individual variability in the different penetrance of congenital long QT syndromes (LQTS) types 1 and 2: an in silico approach.Scientific reports · 2026Article
- Population Modeling Approach for Human Cardiac Arrhythmia Risk Prediction.Circulation. Arrhythmia and electrophysiology · 2026Article
- Toward Standardized Methodologies for Drug-Induced Proarrhythmia Classification: An In Silico Proof of Concept.Computational and structural biotechnology journal · 2026Article
- Efficient Generation of Populations of Cardiac Models.Computing in cardiology · 2025Article
- Cell-to-cell heterogeneity in ion channel conductance impacts substrate vulnerability to arrhythmia.American journal of physiology. Heart and circulatory physiology · 2024Article
- Crossing the Great Sex-Specific Divide in Cardiac Electrophysiology.JACC. Clinical electrophysiology · 2023Article
- Estimating the probability of early afterdepolarizations and predicting arrhythmic risk associated with long QT syndrome type 1 mutations.Biophysical journal · 2023Article
- Lysosomal calcium loading promotes spontaneous calcium release by potentiating ryanodine receptors.Biophysical journal · 2023Article
- Emergent activity, heterogeneity, and robustness in a calcium feedback model of the sinoatrial node.Biophysical journal · 2023Article
- Electrophysiological heterogeneity in large populations of rabbit ventricular cardiomyocytes.Cardiovascular research · 2022Article
- Comparison of fluid dynamics changes due to physical activity in 3D printed patient specific coronary phantoms with the Windkessel equivalent model of coronary flow.3D printing in medicine · 2022Article
- Metabolically driven maturation of human-induced-pluripotent-stem-cell-derived cardiac microtissues on microfluidic chips.Nature biomedical engineering · 2022Article
- Neuronal population models reveal specific linear conductance controllers sufficient to rescue preclinical disease phenotypes.iScience · 2021Article
- Interactive 3D Human Heart Simulations on Segmented Human MRI Hearts.Computing in cardiology · 2021Article
- A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes.PLoS computational biology · 2021Article
- Mechanisms underlying age-associated manifestation of cardiac sodium channel gain-of-function.Journal of molecular and cellular cardiology · 2021Article
- Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes.PLoS computational biology · 2021Article
- In Silico Assessment of Class I Antiarrhythmic Drug Effects onInternational journal of molecular sciences · 2021Article
- Inflammation as a Risk Factor in Cardiotoxicity: An Important Consideration for Screening During Drug Development.Frontiers in pharmacology · 2021Article
- A distinct molecular mechanism by which phenytoin rescues a novel long QT 3 variant.Journal of molecular and cellular cardiology · 2020Article
23 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Across individuals within a population, several levels of variability are observed, from the differential expression of ion channels at the molecular level, to the various action potential morphologies observed at the cellular level, to divergent responses to drugs at the organismal level. However, the limited ability of experiments to probe complex interactions between components has hitherto hindered our understanding of the factors that cause a range of behaviours within a population. Variability is a challenging issue that is encountered in all physiological disciplines, but recent work suggests that novel methods for analysing mathematical models can assist in illuminating its causes. In this review, we discuss mathematical modelling studies in cardiac electrophysiology and neuroscience that have enhanced our understanding of variability in a number of key areas. Specifically, we discuss parameter sensitivity analysis techniques that may be applied to generate quantitative predictions based on considering behaviours within a population of models, thereby providing novel insight into variability. Our discussion focuses on four issues that have benefited from the utilization of these methods: (1) the comparison of different electrophysiological models of cardiac myocytes, (2) the determination of the individual contributions of different molecular changes in complex disease phenotypes, (3) the identification of the factors responsible for the variable response to drugs, and (4) the constraining of free parameters in electrophysiological models of heart cells. Together, the studies that we discuss suggest that rigorous analyses of mathematical models can generate quantitative predictions regarding how molecular-level variations contribute to functional differences between experimental samples. These strategies may be applicable not just in cardiac electrophysiology, but in a wide range of disciplines.
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