ReviewThe Journal of physiology2012
At the heart of computational modelling.
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 15 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.
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Who cites it
15 citing papers in PubMed.
- Neural Network Approaches for Soft Biological Tissue and Organ Simulations.Journal of biomechanical engineering · 2022Review
- Frank-Starling mechanism, fluid responsiveness, and length-dependent activation: Unravelling the multiscale behaviors with an in silico analysis.PLoS computational biology · 2021Article
- Modeling individual differences in cardiovascular response to gravitational stress using a sensitivity analysis.Journal of applied physiology (Bethesda, Md. : 1985) · 2021Article
- Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models.Journal of the Royal Society, Interface · 2017Article
- Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics.The Journal of physiology · 2017Review
- Heart Valve Biomechanics and Underlying Mechanobiology.Comprehensive Physiology · 2016Review
- There and back again: Iterating between population-based modeling and experiments reveals surprising regulation of calcium transients in rat cardiac myocytes.Journal of molecular and cellular cardiology · 2016Article
- Improving cardiomyocyte model fidelity and utility via dynamic electrophysiology protocols and optimization algorithms.The Journal of physiology · 2016Review
- Hodgkin-Huxley revisited: reparametrization and identifiability analysis of the classic action potential model with approximate Bayesian methods.Royal Society open science · 2015Article
- β-adrenergic effects on cardiac myofilaments and contraction in an integrated rabbit ventricular myocyte model.Journal of molecular and cellular cardiology · 2015Article
- Human cardiac systems electrophysiology and arrhythmogenesis: iteration of experiment and computation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2014Review
- Fibroblast-myocyte electrotonic coupling: does it occur in native cardiac tissue?Journal of molecular and cellular cardiology · 2014Review
- Toward GPGPU accelerated human electromechanical cardiac simulations.International journal for numerical methods in biomedical engineering · 2014Article
- Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies.Cardiovascular research · 2013Review
- Benchmarking electrophysiological models of human atrial myocytes.Frontiers in physiology · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The link between experimental data and biophysically based mathematical models is key to computational simulation meeting its potential to provide physiological insight. However, despite the importance of this link, scrutiny and analysis of the processes by which models are parameterised from data are currently lacking. While this situation is common to many areas of physiological modelling, to provide a concrete context, we use examples drawn from detailed models of cardiac electro-mechanics. Using this biophysically detailed cohort of models we highlight the specific issues of model parameterization and propose this process can be separated into three stages: observation, fitting and validation. Finally, future research challenges and directions in this area are discussed.
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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.