Chon Lok Lei

Chon Lok Lei

A physicist-turned-computational biologist. Assistant Professor at the University of Macau. DPhil at the University of Oxford. BSc at Imperial College.

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Chon Lok Lei’s research homepage.

Posts

preprints

Using flexible noise models to avoid noise model misspecification in inference of differential equation time series models

Published in arXiv, 2020

This paper develops two flexible noise models handle unknown noise generating processes when performing inference of differential equation time series models.

Recommended citation: Creswell, R., Lambert, B., Lei, C.L., Robinson, M., and Gavaghan, D. (2020). "Using flexible noise models to avoid noise model misspecification in inference of differential equation time series models." arXiv. http://arxiv.org/abs/2011.04854

Empirical quantification of predictive uncertainty due to model discrepancy by training with an ensemble of experimental designs: an application to ion channel kinetics

Published in arXiv, 2023

This paper develops an empirical approach to quantify predictive uncertainty due to model discrepancy using an ensemble of experimental designs.

Recommended citation: Shuttleworth, J.G., Lei, C.L., Whittaker, D.G., et al. (2023). "Empirical quantification of predictive uncertainty due to model discrepancy by training with an ensemble of experimental designs: an application to ion channel kinetics." arXiv. http://arxiv.org/abs/2302.02942

publications

Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology

Published in Frontiers in Physiology, 2017

This paper shows that tailoring a mathematical model of hiPSC-CMs to a specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs.

Recommended citation: Lei, C.L., Wang, K., Clerx, M., Johnstone, R.H., et al. (2017). "Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology." Frontiers in Physiology, 8, 986. https://doi.org/10.3389/fphys.2017.00986

Probabilistic Inference on Noisy Time Series (PINTS)

Published in Journal of Open Research Software, 2019

This paper introduces our open-source Python library, PINTS, that provides researchers with a broad suite of non-linear optimisation and sampling methods.

Recommended citation: Clerx, M., Robinson, M., Lambert, B., Lei, C.L., et al. (2019). "Probabilistic Inference on Noisy Time Series (PINTS)." Journal of Open Research Software, 7(1), p.23. https://doi.org/10.5334/jors.252

Rapid characterization of hERG channel kinetics I: using an automated high-throughput system

Published in Biophysical Journal, 2019

This paper presents a method for high-throughput characterization of hERG potassium channel kinetics via fitting a mathematical model to results of over 100 single-cell patch-clamp measurements collected simultaneously on an automated voltage-clamp platform.

Recommended citation: Lei, C.L., Clerx, M., Gavaghan, D.J., et al. (2019). "Rapid characterization of hERG channel kinetics I: using an automated high-throughput system." Biophysical Journal, 117, 12, p.2438-2454. https://doi.org/10.1016/j.bpj.2019.07.029

Rapid characterization of hERG channel kinetics II: temperature dependence

Published in Biophysical Journal, 2019

This paper shows that the commonly used Q10 and Eyring formulations are incapable of describing the parameters’ temperature dependence, and care is needed to avoid misleading extrapolations in their many scientific and industrial pharmaceutical applications.

Recommended citation: Lei, C.L., Clerx, M., Beattie, K.A., et al. (2019). "Rapid characterization of hERG channel kinetics II: temperature dependence." Biophysical Journal, 117, 12, p.2455-2470. https://doi.org/10.1016/j.bpj.2019.07.030

An audit of uncertainty in multi-scale cardiac electrophysiology models

Published in Philosophical Transactions of the Royal Society A, 2020

This paper reviews the source of uncertainty in multi-scale cardiac electrophysiology models.

Recommended citation: Clayton, R.H., Aboelkassem, T., Cantwell, C.D., Corrado, C., Delhaas, T., Huberts, W., Lei, C.L., et al. (2020). "An audit of uncertainty in multi-scale cardiac electrophysiology models." Phil. Trans. R. Soc. A. 378: 20190335. https://doi.org/10.1098/rsta.2019.0335

Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments

Published in Philosophical Transactions of the Royal Society A, 2020

This paper studies the source of variability of the ion channel recordings by constructing a model that describes not just ion current dynamics, but the entire voltage-clamp experiment.

Recommended citation: Lei, C.L., Clerx, M., Whittaker, D.G., et al. (2020). "Accounting for variability in ion current recordings using a mathematical model of artefacts in voltage-clamp experiments." Phil. Trans. R. Soc. A. 378: 20190348. https://doi.org/10.1098/rsta.2019.0348

Considering discrepancy when calibrating a mechanistic electrophysiology model

Published in Philosophical Transactions of the Royal Society A, 2020

This paper reviews the pitfalls and methods to account for the uncertainty in the model/equations structure, and provides detailed examples with electrophysiology models.

Recommended citation: Lei, C.L., Ghosh, S., Whittaker, D.G., et al. (2020). "Considering discrepancy when calibrating a mechanistic electrophysiology model." Phil. Trans. R. Soc. A. 378: 20190349. https://doi.org/10.1098/rsta.2019.0349

3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients

Published in Nature Communications, 2021

This paper uses 3D bio-printed cochleae and machine learning to model and study cochlear implants.

Recommended citation: Lei, I.M., Jiang, C., Lei, C.L. et al. (2021). "3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients." Nat. Commun.. 12, 6260. https://doi.org/10.1038/s41467-021-26491-6

A nonlinear and time-dependent leak current in the presence of calcium fluoride patch-clamp seal enhancer

Published in Wellcome Open Research, 2021

This paper studies a nonlinear-in-voltage and time-dependent leak current due to the effect of a commonly-used seal enhancer in patch-clamping.

Recommended citation: Lei, C.L., Fabbri, A., Whittaker, D.G., et al. (2021). "A nonlinear and time-dependent leak current in the presence of calcium fluoride patch-clamp seal enhancer [version 2]." Wellcome Open Res., 5:152. https://doi.org/10.12688/wellcomeopenres.15968.2

Nicotinamide promotes cardiomyocyte derivation and survival through kinase inhibition in human pluripotent stem cells

Published in Cell Death and Disease, 2021

This paper studies the effects of nicotinamide on cardiomyocyte derivation and survival in human pluripotent stem cells.

Recommended citation: Meng, Y., Song, C., Ren, Z., et al. (2021). "Nicotinamide promotes cardiomyocyte derivation and survival through kinase inhibition in human pluripotent stem cells." Cell Death Dis., 12:1119. https://doi.org/10.1038/s41419-021-04395-z

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification

Published in iScience, 2023

This paper develops an novel approach to extract the information and classify genetic variant types through results of molecular dynamics simulations using a deep learning algorithm.

Recommended citation: Tam, B., Qin, Z., ..., Lei, C.L. (2023). "Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification." iScience, 26, 106122. https://doi.org/10.1016/j.isci.2023.106122

A Bayesian nonparametric method for detecting rapid changes in disease transmission

Published in Journal of Theoretical Biology, 2023

This paper introduces a Bayesian nonparametric way to detect changes in disease transmission, applying to various real-world data including COVID-19.

Recommended citation: Creswell, R., ..., Lei, C.L. and Lambert, B. (2023). "A Bayesian nonparametric method for detecting rapid changes in disease transmission." Journal of Theoretical Biology, 558, 111351. https://doi.org/10.1016/j.jtbi.2022.111351

Autocorrelated measurement processes and inference for ordinary differential equation models of biological systems

Published in Journal of The Royal Society Interface, 2023

This paper studies the effects of ignoring autocorrelated measurement processes on inferring ODE models of biological systems.

Recommended citation: Lambert, B., Lei, C.L., Robinson, M., et al. (2023). "Autocorrelated measurement processes and inference for ordinary differential equation models of biological systems." Journal of The Royal Society Interface, 20, 20220725. https://doi.org/10.1098/rsif.2022.0725

Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment

Published in Frontiers in Pharmacology, 2023

This paper compares the two main different types of modelling approaches of hERG drug binding used in predicting drug-induced action potential prolongations for drug safety assessment.

Recommended citation: Farm, H.J., Clerx, M., ..., Lei, C.L. (2023). "Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment." Frontiers in Pharmacology, 14:1110555. https://doi.org/10.3389/fphar.2023.1110555

Heterologous vaccination with inactivated vaccine and mRNA vaccine augments antibodies against both spike and nucleocapsid proteins of SARS-CoV-2: a local study in Macao

Published in Frontiers in Immunology, 2023

This paper studies the effects of heterologous vaccination with inactivated vaccine and mRNA vaccine on the antibodies against both spike and nucleocapsid proteins of SARS-CoV-2.

Recommended citation: Ng, H.M., Lei, C.L., Fu, S., et al. (2023). "Heterologous vaccination with inactivated vaccine and mRNA vaccine augments antibodies against both spike and nucleocapsid proteins of SARS-CoV-2: a local study in Macao." Frontiers in Immunology, 14:1131985. https://doi.org/10.3389/fimmu.2023.1131985

Model-driven optimal experimental design for calibrating cardiac electrophysiology models

Published in Computer Methods and Programs in Biomedicine, 2023

This paper develops an automated, objective approach to optimise experimental designs for calibrating cardiac electrophysiology models.

Recommended citation: Lei, C.L., Clerx, M., Gavaghan, D.J., and Mirams, G.R. (2023). "Model-driven optimal experimental design for calibrating cardiac electrophysiology models." Computer Methods and Programs in Biomedicine, 107690. https://doi.org/10.1016/j.cmpb.2023.107690

Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings

Published in EP Europace, 2023

This paper studies the effect leak current in stem cell-derived cardiomyocyte action potential recordings.

Recommended citation: Clark, A.P., Clerx, M., Wei, S., Lei, C.L. et al. (2022). "Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings." EP Europace, 25:9, euad243. https://doi.org/10.1093/europace/euad243

The impact of uncertainty in hERG binding mechanism on in silico predictions of drug-induced proarrhythmic risk

Published in British Journal of Pharmacology, 2023

This paper studies how uncertainty in hERG binding mechanism may affect the in silico predictions of drug-induced proarrhythmic risk.

Recommended citation: Lei, C.L., Whittaker, D.G. and Mirams, G.R. (2023). "The impact of uncertainty in hERG binding mechanism on in silico predictions of drug-induced proarrhythmic risk." British Journal of Pharmacology. https://doi.org/10.1111/bph.16250

talks

teaching

Mathematical Methods

Undergraduate tutorial, University of Oxford, University College, 2018

This tutorial is a part of the Mathematical Methods course for the second year Physics undergraduate degree at the University of Oxford.

Essential Mathematics

Postgraduate course, University of Oxford, Doctoral Training Centre, 2019

This course gives students a solid grounding in mathematical topics essential for the analysis of biological systems.

Research Software Engineering

Postgraduate practical session, University of Oxford, Doctoral Training Centre, 2019

This course provides the basics for research software engineering (RSE).

Scientific Computing

Postgraduate practical session, University of Oxford, Doctoral Training Centre, 2019

This course gives a solid introduction to different methods and algorithms in scientific computing with applications in biological science.

GEST1002 Quantitative Reasoning for Social Sciences

Undergraduate course, University of Macau, Lecture Theatre E4-G078, 2021

This course introduces basic concept of finance, logic, probability and statistics and basics of mathematical modelling. Real-life applications will be emphasised.

HSCI7001 Artificial Intelligence in Medicine

Postgraduate course, University of Macau, Lecture Room E12-1057, 2022

This course introduces the concept of artificial intelligence (AI) in medicine, the associated big data analysis, and analytic programming.

GEST1002 Quantitative Reasoning for Social Sciences

Undergraduate course, University of Macau, Lecture Theatre E4-G078, 2022

This course introduces basic concept of finance, logic, probability and statistics and basics of mathematical modelling. Real-life applications will be emphasised.

thesis