1. Physiology-based regularization of the electrocardiographic inverse problem Matthijs Cluitmans, Michael Clerx, Nele Vandersickel, Ralf L.M. Peeters, Paul G.A. Volders, Ronald L. Westra 2017 Medical & Biological Engineering & Computing Volume 55, pages 1353-1365 doi: 10.1007/s11517-016-1595-5
  2. Myokit: A simple interface to cardiac cellular electrophysiology Michael Clerx, Pieter Collins, Enno de Lange, Paul G.A. Volders 2016 Progress in Biophysics and Molecular Biology Volume 120, issues 1-3, pages 100-114 doi: 10.1016/j.pbiomolbio.2015.12.008


  1. Multi-scale modeling and variability in cardiac cellular electrophysiology Michael Clerx 2017 Download


  1. Applying novel identification protocols to Markov models of INa Michael Clerx, Pieter Collins, Paul G.A. Volders 2015 Computing in Cardiology Volume 42, pages 889-892 Download from
  2. Myokit: A Framework for Computational Cellular Electrophysiology Michael Clerx, Paul G.A. Volders, Pieter Collins 2014 Computing in Cardiology Volume 41, pages 229-232 Download from
  3. Reducing run-times of excitable cell models by replacing computationally expensive functions with splines Michael Clerx, Pieter Collins 2014 21st International Symposium on Mathematical Theory of Networks and Systems, July 7-11, 2014, University of Groningen, Groningen, The Netherlands Pages 84-89 Download author's copy (copyright IEEE)


  1. Myokit is a toolkit for computational cellular electrophysiology. It aims to reduce the time spent programming and implementing low-level solvers, while maintaining the performance and flexibility of powerful custom-made software. Its development was started in 2011 during my PhD thesis at Maastricht University.

    Myokit is open source and can be downloaded from