ArticlePloS one2020
Genetic algorithm-based personalized models of human cardiac action potential.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- Patient-Specific Heart Rate Modulates Developmental Electrophysiology in Transcriptomic-Guided In Silico Models of Pediatric Human Atrial Cardiomyocytes.bioRxiv : the preprint server for biology · 2026Article
- IonBench: A benchmark of optimisation strategies for mathematical models of ion channel currents.PLoS computational biology · 2025Article
- Advanced Cardiovascular Toxicity Screening: Integrating Human iPSC-Derived Cardiomyocytes with 2D In Silico Models.Cardiovascular toxicology · 2025Article
- Connecting transcriptomics with computational modeling to reveal developmental adaptations in pediatric human atrial tissue.American journal of physiology. Heart and circulatory physiology · 2024Article
- Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modelling.Royal Society open science · 2023Article
- Diversity of cells and signals in the cardiovascular system.The Journal of physiology · 2023Article
- Computational design of custom therapeutic cells to correct failing human cardiomyocytes.Frontiers in systems biology · 2023Article
- A Parameter Representing Missing Charge Should Be Considered when Calibrating Action Potential Models.Frontiers in physiology · 2022Article
- AnFrontiers in physiology · 2021Article
- Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators.Frontiers in physiology · 2021Article
- Arrhythmogenic Effects of Genetic Mutations Affecting Potassium Channels in Human Atrial Fibrillation: A Simulation Study.Frontiers in physiology · 2021Article
- Minimally invasive system to reliably characterize ventricular electrophysiology from living donors.Scientific reports · 2020Article
- Creation and application of virtual patient cohorts of heart models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
- Correction: Genetic algorithm-based personalized models of human cardiac action potential.PloS one · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a novel modification of genetic algorithm (GA) which determines personalized parameters of cardiomyocyte electrophysiology model based on set of experimental human action potential (AP) recorded at different heart rates. In order to find the steady state solution, the optimized algorithm performs simultaneous search in the parametric and slow variables spaces. We demonstrate that several GA modifications are required for effective convergence. Firstly, we used Cauchy mutation along a random direction in the parametric space. Secondly, relatively large number of elite organisms (6-10% of the population passed on to new generation) was required for effective convergence. Test runs with synthetic AP as input data indicate that algorithm error is low for high amplitude ionic currents (1.6±1.6% for IKr, 3.2±3.5% for IK1, 3.9±3.5% for INa, 8.2±6.3% for ICaL). Experimental signal-to-noise ratio above 28 dB was required for high quality GA performance. GA was validated against optical mapping recordings of human ventricular AP and mRNA expression profile of donor hearts. In particular, GA output parameters were rescaled proportionally to mRNA levels ratio between patients. We have demonstrated that mRNA-based models predict the AP waveform dependence on heart rate with high precision. The latter also provides a novel technique of model personalization that makes it possible to map gene expression profile to cardiac function.
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