Publications

Journal publications

1. Optimal experimental designs for characterising ion channel gating by filling the phase-voltage space of model dynamics Gary R. Mirams, Michael Clerx, Dominic G. Whittaker, Chon Lok Lei 2024 Mathematics in Medical and Life Sciences Volume 1(1), 2375494
   doi: 10.1080/29937574.2024.2375494 code
2. Model-driven optimal experimental design for calibrating cardiac electrophysiology models Chon Lok Lei, Michael Clerx, David J. Gavaghan, Gary R. Mirams 2023 Computer Methods and Programs in Biomedicine Volume 240, 107690 doi: 10.1016/j.cmpb.2023.107690 code
3. Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings Alexander P. Clark, Michael Clerx, Siya Wei, Chon Lok Lei, Teun de Boer, Gary R. Mirams, David J. Christini, Trine Krogh-Madsen 2023 Europace Volume 25, issue 9, page euad243
   doi: 10.1093/europace/euad243 code
4. Importance of modelling hERG binding in predicting drug-induced action potentials for drug safety assessment Hui Jia Farm, Michael Clerx, Fergus Cooper, Liudmila Polonchuck, Ken Wang, David J. Gavaghan, Chon Lok Lei 2023 Frontiers in Pharmacology Volume 14, page 546
   doi: 10.3389/fphar.2023.1110555 code
5. CellML 2.0.1 Michael Clerx, Michael T. Cooling, Jonathan Cooper, Alan Garny, Keri Moyle, David Nickerson, Hugh Sorby 2023 Journal of Integrative Bioinformatics 2023003 doi: 10.1515/jib-2023-0003 code
6. Autocorrelated measurement processes and inference for ordinary differential equation models of biological systems Ben Lambert, Chon Lok Lei, Martin Robinson, Michael Clerx, Richard Creswell, Sanmitra Ghosh, Simon Tavener, David J. Gavaghan 2023 Journal of the Royal Society: Interface Volume 20, Issue 199
   doi: 10.1098/rsif.2022.0725 see paper for various code sources
7. Models of the cardiac L‐type calcium current: A quantitative review Aditi Agrawal, Ken Wang, Liudmila Polonchuk, Jonathan Cooper, Maurice Hendrix, David J. Gavaghan, Gary R. Mirams, Michael Clerx 2022 WIREs Mechanisms of disease Volume 15, page e1581
   doi: 10.1002/wsbm.1581 code Interactive results one and two
8. A parameter representing missing charge should be considered when calibrating action potential models Yann-Stanislas H. M. Barral, Joseph Shuttleworth, Michael Clerx, Dominic G. Whittaker, Ken Wang, Liudmila Polonchuk, David J. Gavaghan, Gary R. Mirams 2022 Frontiers in Physiology
   doi: 10.3389/fphys.2022.879035 code
9. cellmlmanip and chaste codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians Maurice Hendrix, Michael Clerx, Asif U. Tamuri, Sarah M. Keating, Ross H. Johnstone, Jonathan Cooper, Gary R. Mirams 2022 Wellcome Open Research
   doi: 10.12688/wellcomeopenres.17206.1 code
10. A nonlinear and time-dependent leak current in the presence of calcium fluoride patch-clamp seal enhancer Chon Lok Lei, Alan Fabbri, Dominic G. Whittaker, Michael Clerx, Monique J. Windley, Adam P. Hill, Gary R. Mirams, Teun P. de Boer 2021 Wellcome Open Research
    doi: 10.12688/wellcomeopenres.15968.2 code
11. Immediate and delayed response of simulated human atrial myocytes to clinically-relevant hypokalemia Michael Clerx, Gary R. Mirams, Albert J. Rogers, Sanjiv M. Narayan, Wayne R. Giles 2021 Frontiers in Physiology 12:493 doi: 10.3389/fphys.2021.651162 code
12. CellML 2.0 Michael Clerx, Michael T. Cooling, Jonathan Cooper, Alan Garny, Keri Moyle, David Nickerson, Hugh Sorby 2020 Journal of Integrative Bioinformatics Volume 17, number 2-3
    doi: 10.1515/jib-2020-0021 code
13. Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments Chon Lok Lei, Michael Clerx, Dominic G. Whittaker, David J. Gavaghan, Teun P. de Boer, Gary R. Mirams 2020 Philosophical Transactions of the Royal Society A 378: 20190348
    doi: 10.1098/rsta.2019.0348 code
14. Calibration of ionic and cellular cardiac electrophysiology models Dominic G. Whittaker*, Michael Clerx*, Chon Lok Lei, David J. Christini, Gary R. Mirams 2020 WIREs Systems Biology and Medicine 12:e1482 (*shared first authors) doi: 10.1002/wsbm.1482 code
15. Maastricht antiarrhythmic drug evaluator (MANTA): a computational tool for better understanding of antiarrhythmic drugs Henry Sutanto, Lian Laudy, Michael Clerx, Dobromir Dobrev, Harry JGM Crijns, Jordi Heijman 2019 Pharmacological Research 148: 104444 doi: 10.1016/j.phrs.2019.104444 code
16. Four ways to fit an ion channel model Michael Clerx, Kylie A. Beattie, David J. Gavaghan, Gary R. Mirams 2019 Biophysical Journal Volume 117, pages 2420-2437 doi: 10.1016/j.bpj.2019.08.001 code
17. Rapid characterisation of hERG channel kinetics I: using an automated high-throughput system Chon Lok Lei, Michael Clerx, David J. Gavaghan, Liudmila Polonchuk, Gary R. Mirams, Ken Wang 2019 Biophysical Journal Volume 117, pages 2438-2454 doi: 10.1016/j.bpj.2019.07.029 code
18. Rapid characterisation of hERG channel kinetics II: temperature dependence Chon Lok Lei, Michael Clerx, Kylie A. Beattie, Dario Melgari, Jules C. Hancox, David J. Gavaghan, Liudmila Polonchuk, Ken Wang, Gary R. Mirams 2019 Biophysical Journal Volume 117, pages 2455-2470 doi: 10.1016/j.bpj.2019.07.030 code
19. Probabilistic Inference on Noisy Time Series (PINTS) Michael Clerx*, Martin Robinson*, Ben Lambert, Chon Lok Lei, Sanmitra Ghosh, Gary R. Mirams, David J. Gavaghan 2019 Journal of Open Research Software 7(1): 23 (*shared first authors)
    doi: 10.5334/jors.252 code
20. Predicting changes to INa from missense mutations in human SCN5A Michael Clerx, Jordi Heijman, Pieter Collins, Paul G.A. Volders 2018 Scientific Reports 8 (1), 12797 doi: 10.1038/s41598-018-30577-5 code
21. Reproducible model development in the Cardiac Electrophysiology Web Lab Aidan Daly, Michael Clerx, Kylie A. Beattie, Jonathan Cooper, David J. Gavaghan, Gary R. Mirams 2018 Progress in Biophysics and Molecular Biology doi: 10.1016/j.pbiomolbio.2018.05.011 code
22. Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their Electrophysiology Chon Lok Lei, Ken Wang, Michael Clerx, Ross H. Johnstone, Maria P. Hortigon-Vinagre, Victor Zamora, Andrew Allan, Godfrey L. Smith, David J. Gavaghan, Gary R. Mirams, Liudmila Polonchuk 2017 Frontiers in Physiology 8:986 doi: 10.3389/fphys.2017.00986 code
23. 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 (*shared first authors) doi: 10.1007/s11517-016-1595-5
24. 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 code

Peer-reviewed conference proceedings

1. 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) (partial) code

Pre-prints and undergoing review

1. Where's Ben Nevis? A 2D optimisation benchmark with 957,174 local optima based on Great Britain terrain data Yuhang Wei, Michael Clerx, Gary R. Mirams 2024 arXxiv
   doi: doi.org/10.48550/arXiv.2410.02422 code
2. Resolving artefacts in voltage-clamp experiments with computational modelling: an application to fast sodium current recordings Chon Lok Lei, Alexander P. Clark, Michael Clerx, Siyu Wei, Meye Bloothooft, Teun P. de Boer, David J. Christini, Trine Krogh-Madsen, Gary R. Mirams 2024 bioRxiv
   doi: 10.1101/2024.07.23.604780 code
3. An experimental investigation of rundown of the L-type calcium current Aditi Agrawal, Michael Clerx, Ken Wang, Evgenia Gissinger, David J. Gavaghan, Liudmila Polonchuk, Gary R. Mirams 2024 Wellcome Open Research Volume 9, 250
   doi: 10.12688/wellcomeopenres.20374.1 code
4. Variability in reported midpoints of (in)activation of cardiac INa Michael Clerx, Paul G. A. Volders, Gary R. Mirams 2024 bioRxiv
   doi: 10.1101/2024.05.08.593173 code
5. Treatment response prediction: Is model selection unreliable? David Augustin, Antje-Christine Walz, Ken Wang, Ben Lambert, Michael Clerx, Martin Robinson, David Gavaghan 2022 bioRxiv doi: 10.1101/2022.03.19.483454 code

Non-refereed articles

1. Geometrically-derived action potential markres for model development: a principled approach? Michael Clerx, Gary R. Mirams 2024 Computing in Cardiology Volume 51 Pre-print code
2. Derivative-based Inference for Cell and Channel Electrophysiology Models Michael Clerx, David Augustin, Alister R. Dale-Evans, Gary R. Mirams 2022 Computing in Cardiology Volume 49 Download from cinc.org code
3. Normalisation of Action Potential Data Recorded with Sharp Electrodes Maximises Its Utility for Model Development Yann-Stanislas H. M. Barral, Liudmila Polonchuk, Gary R. Mirams, Michael Clerx, Guy Page, Katrina Sweat, Najah Abi-Gerges, Ken Wang, David J. Gavaghan 2022 Computing in Cardiology Volume 49 Download from cinc.org
4. Modelling the Effect of Intracellular Calcium in the Rundown of L-Type Calcium Current Aditi Agrawal, Michael Clerx, Ken Wang, Liudmila Polonchuk, David J. Gavaghan, Gary R. Mirams 2022 Computing in Cardiology Volume 49 Download from cinc.org
5. Personalisation of cellular electrophysiology models; Utopia? Michael Clerx 2018 Computing in Cardiology Volume 45 (Invited paper for the special session Personalized medicine through integration of imaging and cardiac modeling: state of the art and prospects) Download from cinc.org
6. 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 cinc.org
7. 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 cinc.org code

PhD Thesis

1. Multi-scale modeling and variability in cardiac cellular electrophysiology Michael Clerx 2017
   Full thesis, doi: 10.26481/dis.20170420mc
   Chapter 2 - Background: Bioelectricity in the human heart
   Chapter 5 - Variability in the dynamical properties of human cardiac INa
   Chapter 8 - Discussion

Software

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 https://myokit.org.

2. PINTS (Probabilistic Inference on Noisy Time-Series) is a framework for optimisation and Bayesian inference on ODE models of noisy time-series, such as arise in electrochemistry and cardiac electrophysiology.

   PINTS is open source and can be downloaded from https://github.com/pints-team/pints.