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Outputs (30)

Optimising experimental designs for model selection of ion channel drug binding mechanisms (2024)
Preprint / Working Paper
Patten-Elliott, F., Lei, C. L., Preston, S. P., Wilkinson, R. D., & Mirams, G. R. Optimising experimental designs for model selection of ion channel drug binding mechanisms

The rapid delayed rectifier current carried by the human Ether-à-go-go-Related Gene (hERG) channel is susceptible to drug-induced reduction which can lead to an increased risk of cardiac arrhythmia. Establishing the mechanism by which a specific drug... Read More about Optimising experimental designs for model selection of ion channel drug binding mechanisms.

Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs (2024)
Preprint / Working Paper
Shuttleworth, J. G., Lei, C. L., Windley, M. J., Hill, A. P., Preston, S. P., & Mirams, G. R. Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs

Mathematical models are increasingly being relied upon to provide quantitatively accurate predictions of cardiac electrophysiology. Many such models concern the behaviour of particular subcellular components (namely, ion channels) which, together, al... Read More about Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs.

Modelling the role of enzymatic pathways in the metabolism of docosahexaenoic acid by monocytes and its association with osteoarthritic pain (2024)
Journal Article
Franks, S. J., Gowler, P. R., Dunster, J. L., Turnbull, J., Gohir, S. A., Kelly, A., Valdes, A. M., King, J. R., Barrett, D. A., Chapman, V., & Preston, S. (2024). Modelling the role of enzymatic pathways in the metabolism of docosahexaenoic acid by monocytes and its association with osteoarthritic pain. Mathematical Biosciences, 374, Article 109228. https://doi.org/10.1016/j.mbs.2024.109228

Chronic pain is a major cause of disability and suffering in osteoarthritis (OA) patients. Endogenous specialised pro-resolving molecules (SPMs) curtail pro-inflammatory responses. One of the SPM intermediate oxylipins, 17-hydroxydocasahexaenoic acid... Read More about Modelling the role of enzymatic pathways in the metabolism of docosahexaenoic acid by monocytes and its association with osteoarthritic pain.

Using many different voltage protocols to characterise discrepancy in mathematical ion channel models (2023)
Journal Article
Shuttleworth, J. G., Lok Lei, C., Windley, M., Hill, A. P., Perry, M. D., Preston, S., & Mirams, G. R. (2023). Using many different voltage protocols to characterise discrepancy in mathematical ion channel models. Biophysical Journal, 122(3, Suppl. 1), 242a. https://doi.org/10.1016/j.bpj.2022.11.1415

The Kv11.1 protein encoded by the hERG gene forms the primary subunit of a voltage-sensitive ion channel responsible for IKr in cardiomyocytes. Mathematical models of the macroscopic current are fitted to data from patch-clamp experiments - in which... Read More about Using many different voltage protocols to characterise discrepancy in mathematical ion channel 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.

Invariance and identifiability issues for word embeddings (2019)
Presentation / Conference Contribution
Carrington, R., Bharath, K., & Preston, S. (2019). Invariance and identifiability issues for word embeddings. In Advances in Neural Information Processing Systems 32 (NIPS 2019)

Word embeddings are commonly obtained as optimisers of a criterion function f of 1 a text corpus, but assessed on word-task performance using a different evaluation 2 function g of the test data. We contend that a possible source of disparity in 3 pe... Read More about Invariance and identifiability issues for word embeddings.

Spherical regression models with general covariates and anisotropic errors (2019)
Journal Article
Paine, P. J., Preston, S. P., Tsagris, M., & Wood, A. T. A. (2020). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing, 30(1), 153–165. https://doi.org/10.1007/s11222-019-09872-2

Existing parametric regression models in the literature for response data on the unit sphere assume that the covariates have particularly simple structure, for example that they are either scalar or are themselves on the unit sphere, and/or that the... Read More about Spherical regression models with general covariates and anisotropic errors.

Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis (2019)
Journal Article
Carson, J., Crucifix, M., Preston, S., & Wilkinson, R. (2019). Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 475(2224), https://doi.org/10.1098/rspa.2018.0854

The study of palaeoclimates relies on information sampled in natural archives such as deep sea cores. Scientific investigations often use such information in multi- stage analyses, typically with an age model being fitted to a core to convert depths... Read More about Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis.

Parameter inference to motivate asymptotic model reduction: an analysis of the gibberellin biosynthesis pathway (2018)
Journal Article
Band, L. R., & Preston, S. P. (2018). Parameter inference to motivate asymptotic model reduction: an analysis of the gibberellin biosynthesis pathway. Journal of Theoretical Biology, 457, 66-78. https://doi.org/10.1016/j.jtbi.2018.05.028

Developing effective strategies to use models in conjunction with experimental data is essential to understand the dynamics of biological regulatory networks. In this study, we demonstrate how combining parameter estimation with asymptotic analysis c... Read More about Parameter inference to motivate asymptotic model reduction: an analysis of the gibberellin biosynthesis pathway.

Process parameter optimisation of laser clad iron based alloy: Predictive models of deposition efficiency, porosity and dilution (2018)
Journal Article
Reddy, L., Preston, S. P., Shipway, P., Davis, C., & Hussain, T. (2018). Process parameter optimisation of laser clad iron based alloy: Predictive models of deposition efficiency, porosity and dilution. Surface and Coatings Technology, 349, 198-207. https://doi.org/10.1016/j.surfcoat.2018.05.054

As a candidate coating material for heat-exchanger surfaces in commercial power generation boiler, an amorphous/glass forming Fe-Cr-B alloy NanoSteel SHS 7170 was deposited by a 2 kW fibre laser onto a boiler grade steel substrate (15Mo3). A comprehe... Read More about Process parameter optimisation of laser clad iron based alloy: Predictive models of deposition efficiency, porosity and dilution.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies (2018)
Journal Article
Retkute, R., Townsend, A. J., Murchie, E. H., Jensen, O. E., & Preston, S. P. (2018). Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies. Annals of Botany, 122(2), 291–302. https://doi.org/10.1093/aob/mcy067

Background and Aims Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the comp... Read More about Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies (2018)
Preprint / Working Paper
Retkute, R., Townsend, A. J., Murchie, E. H., Jensen, O. E., & Preston, S. P. Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies

Background and Aims Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the comp... Read More about Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

An elliptically symmetric angular Gaussian distribution (2017)
Journal Article
Paine, P., Preston, S. P., Tsagris, M., & Wood, A. T. (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing, 28(3), 689-697. https://doi.org/10.1007/s11222-017-9756-4

We define a distribution on the unit sphere Sd−1 called the elliptically symmetric angular Gaussian distribution. This distribution, which to our knowledge has not been studied before, is a subfamily of the angular Gaussian distribution closely analo... Read More about An elliptically symmetric angular Gaussian distribution.

Bayesian model selection for the glacial-interglacial cycle (2017)
Journal Article
Carson, J., Crucifix, M., Preston, S., & Wilkinson, R. (2017). Bayesian model selection for the glacial-interglacial cycle. Journal of the Royal Statistical Society: Series C, 67(1), https://doi.org/10.1111/rssc.12222

A prevailing viewpoint in paleoclimate science is that a single paleoclimate record contains insufficient information to discriminate between typical competing explanatory models. Here we show that by using SMC 2 (sequential Monte Carlo squared) comb... Read More about Bayesian model selection for the glacial-interglacial cycle.

Event series prediction via non-homogeneous Poisson process modelling (2016)
Presentation / Conference Contribution
Goulding, J., Preston, S. P., & Smith, G. (2016). Event series prediction via non-homogeneous Poisson process modelling. In 2016 IEEE 16th International Conference on Data Mining (ICDM). https://doi.org/10.1109/ICDM.2016.0027

Data streams whose events occur at random arrival times rather than at the regular, tick-tock intervals of traditional time series are increasingly prevalent. Event series are continuous, irregular and often highly sparse, differing greatly in nature... Read More about Event series prediction via non-homogeneous Poisson process modelling.

Nonparametric hypothesis testing for equality of means on the simplex (2016)
Journal Article
Tsagris, M., Preston, S. P., & Wood, A. T. (in press). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2), https://doi.org/10.1080/00949655.2016.1216554

In the context of data that lie on the simplex, we investigate use of empirical and exponential empirical likelihood, and Hotelling and James statistics, to test the null hypothesis of equal population means based on two independent samples. We perfo... Read More about Nonparametric hypothesis testing for equality of means on the simplex.

High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field (2015)
Journal Article
Burgess, A. J., Retkute, R., Pound, M. P., Foulkes, J., Preston, S. P., Jensen, O. E., …Murchie, E. H. (2015). High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field. Plant Physiology, 169(2), 1192-1204. https://doi.org/10.1104/pp.15.00722

Photoinhibition reduces photosynthetic productivity; however, it is difficult to quantify accurately in complex canopies partly because of a lack of high-resolution structural data on plant canopy architecture, which determines complex fluctuations o... Read More about High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field.

Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution (2013)
Journal Article
White, S. R., Kypraios, T., & Preston, S. P. (2015). Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution. Statistics and Computing, 25(2), 289-301. https://doi.org/10.1007/s11222-013-9432-2

© 2013, The Author(s). Many modern statistical applications involve inference for complicated stochastic models for which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential techni... Read More about Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution.

Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs (2013)
Journal Article
Hirt, B. V., Wattis, J. A., & Preston, S. P. (2014). Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs. Journal of Mathematical Biology, 68(6), 1521-1552. https://doi.org/10.1007/s00285-013-0678-2

Telomeres are guanine-rich sequences at the end of chromosomes which shorten during each replication event and trigger cell cycle arrest and/or controlled death (apoptosis) when reaching a threshold length. The enzyme telomerase replenishes the ends... Read More about Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs.

The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments (2012)
Journal Article
Hirt, B. V., Wattis, J. A., Preston, S. P., & Laughton, C. A. (2012). The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments. Journal of Theoretical Biology, 295, https://doi.org/10.1016/j.jtbi.2011.10.038

The pentacyclic acridinium salt RHPS4 displays anti-tumour properties in vitro as well as in vivo and is potentially cell-cycle specific. We have collected experimental data and formulated a compartmental model using ordinary differential equations t... Read More about The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments.