Software
GP_emu_UQSA is an open source Python toolkit designed for fitting a Gaussian process (GP) to model inputs and outputs. The GP can then be used for uncertainty and sensitivity analysis.
Workshop slides
Quantifying uncertainty in multiscale models for biomedical applications (21 April 2017)
Journal publications
Chang ET, Strong M, Clayton RH. (2015). Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator. PLoS one, 10 (6), pp. e0130252 (DOI)
Ashcroft P, Michor F, Galla T. (2015). Stochastic tunneling and metastable states during the somatic evolution of cancer. Genetics, 199 (4), pp. 121328 (DOI)
Johnstone RH, Chang ET, Bardenet R, de Boer TP, Gavaghan DJ, Pathmanathan P, Clayton RH. Mirams GR. (2016). Uncertainty and variability in models of the cardiac action potential: Can we build trustworthy models? Journal of Molecular and Cellular Cardiology, pp. 4962 (DOI)
Stewart PS, Jensen OE. (2015). Patterns of recruitment and injury in a heterogeneous airway network model. Journal of the Royal Society, Interface, 12 (111), pp. 20150523 (DOI)
Lin YT, Galla T. (2016). Bursting noise in gene expression dynamics: linking microscopic and mesoscopic models. Journal of the Royal Society, Interface, 13 (114), pp. 20150772 (DOI)
Xu F, Jensen OE. (2016). Drop spreading with random viscosity. Proceedings of the Royal Society A. Mathematical, Physical, and Engineering Sciences, 472 (2194), pp. 20160270 (DOI)
Lin YT, Doering CR. (2016). Gene expression dynamics with stochastic bursts: Construction and exact results for a coarsegrained model. Physical Review. E, 93 (2), pp. 022409 (DOI)
Hufton PG, Lin YT, Galla T, McKane AJ. (2016). Intrinsic noise in systems with switching environments. Physical Review. E, 93 (5), pp. 052119 (DOI)
Russell MJ, Jensen OE, Galla T. (2016). Stochastic transport in the presence of spatial disorder: Fluctuationinduced corrections to homogenization. Physical Review. E, 94 (41), pp. 042121 (DOI)
Chang ET, Lin YT, Galla T, Clayton RH, Eatock J. (2016). A Stochastic IndividualBased Model of the Progression of Atrial Fibrillation in Individuals and Populations. PLoS one, 11 (4), pp. e0152349(DOI)
Pearce P, Brownbill P, Janáček J, Jirkovská M, Kubínová L, Chernyavsky IL, Jensen OE. (2016). ImageBased Modeling of Blood Flow and Oxygen Transfer in FetoPlacental Capillaries. PLoS one, 11 (10), pp. e0165369(DOI)
Mirams GR, Pathmanathan P, Gray RA, Challenor P, Clayton RH. (2016). Uncertainty and variability in computational and mathematical models of cardiac physiology. The Journal of Physiology, 594 (23), pp. 68336847 (DOI)
Lin YT, Chang ETY, Eatock J, Galla T, Clayton RH. (2017). Mechanisms of stochastic onset and termination of atrial fibrillation studied with a cellular automaton model. Journal of the Royal Society Interface 14, pp 20160698. (DOI)
MJ Russell, OE Jensen. Homogenization approximations for unidirectional transport past randomly distributed sinks. (Arxiv preprint)
A NestorBergmann, G Goddard, S Woolner, OE Jensen (2018). Relating cell shape and mechanical stress in a spatially disordered epithelium using a vertexbased model. Mathematical Medicine and Biology: A Journal of the IMA 35 (Suppl 1), pp 127 (DOI)
F Xu, S Coveney, OE Jensen Drop spreading and drifting on a spatially heterogeneous film: capturing variability with asymptotics and emulation. To appear in Journal of Engineering Mathematics (DOI)
F Xu, OE Jensen. (2017) Trapping and displacement of liquid collars and plugs in roughwalled tubes Phys Rev Fluids 2, 094004. (DOI)
HerreríasAzcué F, Galla T. The effects of heterogeneity on stochastic cycles in epidemics. To appear in Nature Scientific Reports. (Arxiv preprint)
Johnson BM, Coveney S, Chang ETY, Johnson PR, Clayton RH. (2018) Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia. Medical and Biological Engineering and Computing 56 (5), pp 761780 (DOI)
NestorBergmann A, Johns E, Woolner S, Jensen OE. (2018) Mechanical characterization of disordered and anisotropic cellular monolayers. Physical Review E 97, 052409 (DOI)
Conference proceedings
Chang ETY, Clayton RH. (2014). Parameter Sensitivity Analysis of a Human Atrial Cell Model using Multivariate Regression. Computing in Cardiology 2014, 41, pp 521524 (Link to paper)
Eatock J, Lin Y, Chang E, Galla T, Clayton R. (2015). Assessing measures of atrial fibrillation clustering via stochastic models of episode recurrence and disease progression. Computing in Cardiology 2014, 42, pp 265268(Link to paper)
Chang E, Clayton R. (2015). Parameter sensitivity from single atrial cell to tissue: How much does it matter? A simulation and multivariate regression study.Computing in Cardiology 2014, 42, pp 441444(Link to paper)
Chang E, Clayton R. (2015). Uncertainty and sensitivity analysis of the CourtemancheRamirezNattel human atrial cell model using Gaussian Process emulators.Computing in Cardiology 2014, 42, pp 857860(Link to paper)
