Myokit: A simple interface to cardiac cellular electrophysiology

Michael Clerx, Pieter Collins, Enno De Lange, Paul G. A. Volders*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

52 Citations (Web of Science)

Abstract

Myokit is a new powerful and versatile software tool for modeling and simulation of cardiac cellular electrophysiology. Myokit consists of an easy-to-read modeling language, a graphical user interface, single and multi-cell simulation engines and a library of advanced analysis tools accessible through a Python interface. Models can be loaded from Myokit's native file format or imported from CelIML. Model export is provided to C, MATLAB, CellML, CUDA and OpenCL. Patch-clamp data can be imported and used to estimate model parameters. In this paper, we review existing tools to simulate the cardiac cellular action potential to find that current tools do not cater specifically to model development and that there is a gap between easy-to-use but limited software and powerful tools that require strong programming skills from their users. We then describe Myokit's capabilities, focusing on its model description language, simulation engines and import/export facilities in detail. Using three examples, we show how Myokit can be used for clinically relevant investigations, multi-model testing and parameter estimation in Markov models, all with minimal programming effort from the user. This way, Myokit bridges a gap between performance, versatility and user-friendliness.
Original languageEnglish
Pages (from-to)100-114
JournalProgress in Biophysics & Molecular Biology
Volume120
Issue number1-3
DOIs
Publication statusPublished - Jan 2016

Keywords

  • Computational models
  • Cardiac action potential
  • Software tools
  • Ion channels
  • Simulation

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