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Outputs (10)

Nitrogen isotopes in herbaria document historical nitrogen sewage pollution in the Mersey Estuary, England (2024)
Journal Article
Alldred, F. C., Gröcke, D. R., Jackson, S. E., & Reid, G. (2024). Nitrogen isotopes in herbaria document historical nitrogen sewage pollution in the Mersey Estuary, England. Environmental Science: Advances, 3(5), 676-685. https://doi.org/10.1039/D4VA00015C

A macroalgae (seaweed) herbarium nitrogen isotope (δ15N) record is produced for the River Mersey and Liverpool South Docks (England) between 1821 and 2018. A modern macroalgae δ15N record was also produced from September 2022. The herbaria δ15N recor... Read More about Nitrogen isotopes in herbaria document historical nitrogen sewage pollution in the Mersey Estuary, England.

Extremism, segregation and oscillatory states emerge through collective opinion dynamics in a novel agent-based model (2022)
Journal Article
Stokes, B., Jackson, S., Garnett, P., & Luo, J. (2022). Extremism, segregation and oscillatory states emerge through collective opinion dynamics in a novel agent-based model. The Journal of Mathematical Sociology, https://doi.org/10.1080/0022250x.2022.2124246

Using mathematics to model the evolution of opinions among interacting agents is a rich and growing field. We present a novel agent-based model that enhances the explanatory power of existing theoretical frameworks, corroborates experimental findings... Read More about Extremism, segregation and oscillatory states emerge through collective opinion dynamics in a novel agent-based model.

Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimension (2022)
Journal Article
Jackson, S. E., & Vernon, I. (2023). Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimension. Bayesian Analysis, 18(1), 165-191. https://doi.org/10.1214/22-ba1304

Emulation has been successfully applied across a wide variety of scientific disciplines for efficiently analysing computationally intensive models. We develop known boundary emulation strategies which utilise the fact that, for many computer models,... Read More about Efficient Emulation of Computer Models Utilising Multiple Known Boundaries of Differing Dimension.

Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching (2020)
Journal Article
Jackson, S., Vernon, I., Liu, J., & Lindsey, K. (2020). Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching. Statistical Applications in Genetics and Molecular Biology, 19(2), Article 20180053. https://doi.org/10.1515/sagmb-2018-0053

A major challenge in plant developmental biology is to understand how plant growth is coordinated by interacting hormones and genes. To meet this challenge, it is important to not only use experimental data, but also formulate a mathematical model. F... Read More about Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching.

In situ statistical measurement of local morphology in carbon-epoxy composites using synchrotron X-ray computed tomography (2019)
Journal Article
Rosini, S., Mavrogordato, M. N., Egorova, O., Matthews, E. S., Jackson, S. E., Mark Spearing, S., & Sinclair, I. (2019). In situ statistical measurement of local morphology in carbon-epoxy composites using synchrotron X-ray computed tomography. Composites Part A: Applied Science and Manufacturing, 125, https://doi.org/10.1016/j.compositesa.2019.105543

Known Boundary Emulation of Complex Computer Models (2019)
Journal Article
Vernon, I., Jackson, S., & Cumming, J. (2019). Known Boundary Emulation of Complex Computer Models. SIAM/ASA Journal on Uncertainty Quantification, 7(3), 838-876. https://doi.org/10.1137/18m1164457

Computer models are now widely used across a range of scientific disciplines to describe various complex physical systems, however to perform full uncertainty quantification we often need to employ emulators. An emulator is a fast statistical constru... Read More about Known Boundary Emulation of Complex Computer Models.

The correlation threshold as a strategy for gene filtering, with application to irritable bowel syndrome and breast cancer microarray data (2016)
Journal Article
Jackson, S. E., Einbeck, J., Kasim, A., & Talloen, W. (2016). The correlation threshold as a strategy for gene filtering, with application to irritable bowel syndrome and breast cancer microarray data. Reinvention, 9(2),

It is well established in the literature that certain disease-associated gene signatures can be identified as a source for predicting the classification of samples or cell lines into diagnostic groups – for example, healthy and diseased. Using standa... Read More about The correlation threshold as a strategy for gene filtering, with application to irritable bowel syndrome and breast cancer microarray data.

Hotspots in Hindsight (2015)
Book Chapter
Julian, B., Foulger, G., Hatfield, O., Jackson, S., Simpson, E., Einbeck, J., & Moore, A. (2015). Hotspots in Hindsight. In G. Foulger, M. Lustrino, & S. King (Eds.), The Interdisciplinary Earth: A Volume in Honor of Don L. Anderson (105-121). The Geological Society of America / AGU. https://doi.org/10.1130/2015.2514%2808%29

Several workers have suggested that the locations of melting anomalies (hotspots) and the original locations of large igneous provinces (LIPs) and kimberlite pipes lie preferentially above the margins of two large low-shear-velocity provinces, or LLS... Read More about Hotspots in Hindsight.

A summer with genes: Simple disease classification from microarray data (2015)
Journal Article
Einbeck, J., Jackson, S. E., & Kasim, A. (2015). A summer with genes: Simple disease classification from microarray data. Mathematics today, 51(4), 186-188

In this article we report on the work carried out within the framework of a summer project, part-funded by an IMA small grant, in which an undergraduate student (the second author of this manuscript) developed and implemented methodology for disease... Read More about A summer with genes: Simple disease classification from microarray data.