Outputs (33)

Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics (2023)
Journal Article
Shuttleworth, J. G., Lei, C. L., Whittaker, D. G., Windley, M. J., Hill, A. P., Preston, S. P., & Mirams, G. R. (2024). Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics. Bulletin of Mathematical Biology, 86(1), Article 2. https://doi.org/10.1007/s11538-023-01224-6

When using mathematical models to make quantitative predictions for clinical or industrial use, it is important that predictions come with a reliable estimate of their accuracy (uncertainty quantification). Because models of complex biological system... Read More about Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics.

Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models (2022)
Journal Article
Whittaker, D. G., Herrera-Reyes, A. D., Hendrix, M., Owen, M. R., Band, L. R., Mirams, G. R., …Preston, S. P. (2023). Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models. Journal of Theoretical Biology, 558, Article 111337. https://doi.org/10.1016/j.jtbi.2022.111337

During the SARS-CoV2 pandemic, epidemic models have been central to policy-making. Public health responses have been shaped by model-based projections and inferences, especially related to the impact of various non-pharmaceutical interventions. Accom... Read More about Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models.

Modelling reveals post-transcriptional regulation of GA metabolism enzymes in response to drought and cold (2022)
Journal Article
Band, L. R., Nelissen, H., Preston, S. P., Rymen, B., Prinsen, E., Abd Elgawad, H., & Beemster, G. T. S. (2022). Modelling reveals post-transcriptional regulation of GA metabolism enzymes in response to drought and cold. Proceedings of the National Academy of Sciences, 119(31), Article e2121288119. https://doi.org/10.1073/pnas.2121288119

The hormone gibberellin (GA) controls plant growth and regulates growth responses to environmental stress. In monocotyledonous leaves, GA controls growth by regulating division-zone size. We used a systems approach to investigate the establishment of... Read More about Modelling reveals post-transcriptional regulation of GA metabolism enzymes in response to drought and cold.

Manifold valued data analysis of samples of networks, with applications in corpus linguistics (2022)
Journal Article
Severn, K. E., Dryden, I. L., & Preston, S. P. (2022). Manifold valued data analysis of samples of networks, with applications in corpus linguistics. Annals of Applied Statistics, 16(1), 368-390. https://doi.org/10.1214/21-aoas1480

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical analysis of samples of networks, motivated by networks representing text... Read More about Manifold valued data analysis of samples of networks, with applications in corpus linguistics.

The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania (2022)
Journal Article
Seymour, R. G., Sirl, D., Preston, S. P., Dryden, I. L., Ellis, M. J., Perrat, B., & Goulding, J. (2022). The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society: Series C, 71(2), 288-308. https://doi.org/10.1111/rssc.12532

Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often surprisingly challenging in developing countries. Due to the logistic... Read More about The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania.

Gaussian process models of potential energy surfaces with boundary optimization (2021)
Journal Article
Broad, J., Preston, S., Wheatley, R. J., & Graham, R. S. (2021). Gaussian process models of potential energy surfaces with boundary optimization. Journal of Chemical Physics, 155(14), Article 144106. https://doi.org/10.1063/5.0063534

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at a long range, and the crossover distance between this mo... Read More about Gaussian process models of potential energy surfaces with boundary optimization.

Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation (2021)
Journal Article
Broad, J., Preston, S., Wheatley, R. J., & Graham, R. S. (2021). Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation. Journal of Chemical Physics, 155(14), Article 144106. https://doi.org/10.1063/5.0063534

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at long range and the cross-over distance between this mode... Read More about Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation.

Approximate Maximum Likelihood Estimation for One-Dimensional Diffusions Observed on a Fine Grid (2021)
Journal Article
Lu, K. W., Paine, P. J., Preston, S. P., & Wood, A. T. A. (2022). Approximate Maximum Likelihood Estimation for One-Dimensional Diffusions Observed on a Fine Grid. Scandinavian Journal of Statistics, 49(3), 1085-1114. https://doi.org/10.1111/sjos.12556

We consider a one-dimensional stochastic differential equation that is observed on a fine grid of equally spaced time points. A novel approach for approximating the transition density of the stochastic differential equation is presented, which is bas... Read More about Approximate Maximum Likelihood Estimation for One-Dimensional Diffusions Observed on a Fine Grid.

Non?parametric regression for networks (2021)
Journal Article
Severn, K. E., Dryden, I. L., & Preston, S. P. (2021). Non?parametric regression for networks. Stat, 10(1), Article e373. https://doi.org/10.1002/sta4.373

Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which are a type of manifold-valued data. Our main objective i... Read More about Non?parametric regression for networks.

Positioning the Root Elongation Zone Is Saltatory and Receives Input from the Shoot (2020)
Journal Article
Baskin, T. I., Preston, S., Zelinsky, E., Yang, X., Elmali, M., Bellos, D., …Bennett, M. J. (2020). Positioning the Root Elongation Zone Is Saltatory and Receives Input from the Shoot. iScience, 23(7), Article 101309. https://doi.org/10.1016/j.isci.2020.101309

In the root, meristem and elongation zone lengths remain stable, despite growth and division of cells. To gain insight into zone stability, we imaged individual Arabidopsis thaliana roots through a horizontal microscope, and used image analysis to ob... Read More about Positioning the Root Elongation Zone Is Saltatory and Receives Input from the Shoot.