Published in arXiv, 2020
This paper develops a new algorithm called Tree Quadrature to approximate high dimensional integration, including calculation of model evidence.
Recommended citation: Foster, T., Lei, C.L., Robinson, M., et al. (2020). "Model evidence with fast tree based quadrature." arXiv. http://arxiv.org/abs/2005.11300
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
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
Published in arXiv, 2023
This paper investigates how numerical sovlers of differential equation models can affect their parameter inference
Recommended citation: Creswell, R., ..., Lei, C.L., Tavener, S., Robinson, M., and Gavaghan, D. (2020). "Understanding the impact of numerical solvers on inference for differential equation models." arXiv. http://arxiv.org/abs/2307.00749
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
Published in Islets, 2018
This paper explores the importance of hub cells in human by constructing mathematical models of Ca2+ activity in human islets.
Recommended citation: Lei, C.L., Kellard, J., Hara, M., Johnson, J., Rodriguez, B. and Briant, L. (2018). "Beta-cell hubs maintain Ca2+ oscillations in human and mouse islet simulations." Islets, 10(4): 151-167. https://doi.org/10.1080/19382014.2018.1493316
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
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
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
Published in WIREs Systems Biology and Medicine, 2020
This review is on parameter fitting in cardiac ion channel and action potential models: what we wish we’d known when we started.
Recommended citation: Whittaker, D.G., Clerx, M., Lei, C.L., et al. (2020). "Calibration of ionic and cellular cardiac electrophysiology" WIREs Syst Biol Med., e1482. https://doi.org/10.1002/wsbm.1482
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
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
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
Published in Frontiers in Physiology, 2021
This paper models ion channel dynamics with a neural network differential equation approach with a special focus on model discrepancy.
Recommended citation: Lei, C.L. and Mirams, G.R. (2021). "Neural network differential equations for ion channel modelling." Front. Physiol.. 12, 1166. https://doi.org/10.3389/fphys.2021.708944
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
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
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
Published in Mathematical Biosciences, 2022
This paper introduces an open-source R package comomodels for compartmental modelling of transmission dynamics.
Recommended citation: van der Vegt, S.A., ..., Lei, C.L., Gavaghan, D.J. and Lambert, B. (2022). "Learning transmission dynamics modelling of COVID-19 using comomodels." Mathematical Biosciences, p.108824. https://doi.org/10.1016/j.mbs.2022.108824
Published in Scientific Reports, 2022
This paper introduces a novel way of building a extrusion 3D printer for soft materials.
Recommended citation: Lei, I.M., Sheng, Y., Lei, C.L., Leow, C., and Huang, Y.Y.S. (2022). "A hackable, multi-functional, and modular extrusion 3D printer for soft materials." Scientific Reports, 12, 12294. https://doi.org/10.1038/s41598-022-16008-6
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
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
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
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
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
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
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
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
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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.
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.
Postgraduate practical session, University of Oxford, Doctoral Training Centre, 2019
This course provides the basics for research software engineering (RSE).
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.
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.
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.
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.
Published:
My thesis submitted for the degree of Doctor of Philosophy at the University of Oxford in 2020.
Recommended citation: Lei, C.L. (2020). "Model-driven design and uncertainty quantification for cardiac electrophysiology experiments" [PhD thesis]. University of Oxford. https://ora.ox.ac.uk/objects/uuid:528c2771-ae4f-4f3c-b649-44904acdf259