Extending Ring-Recovery Models

This is joint research with Marina Jimenez-Munoz, Eleni Matechou, Stephen Freeman, Rob Robinson and Stephen Baillie. Most of the work was developed as part of Marina's PhD. The research examines how spatial information can be incorporated in integrated population models for BTO data on birds and how historical BTO ringing data can be utilised.

Publication

Jimenez-Munoz, M., Cole, D., Freeman, S., Robinson, R., Baillie, S. and Matechou, E. (2019). Estimating age-dependent survival from age-aggregated ringing data - extending the use of historical records. Ecology and Evolution, 9, 769-779. Open access pdf version of paper

Removal Modelling

This work formed Ming Zhou's PhD thesis supervised by Rachel McCrea, Eleni Matechou and Diana Cole. Protected species are often required to be removed from sites scheduled for development to minimize the loss of biodiversity. Removal models that do not account for temporary emigration will be biased, so a new robust design removal model was developed.

Publication

Zhou, M., McCrea, R., Matechou, E., Cole, D. and Griffiths, R. (2019). Removal models accounting for temporary emigration. Biometrics, 75, 24-35. Open access pdf version of paper.

Models for Camera Trap data

This work formed Natoya Jourdain's PhD thesis supervised by Diana Cole, Martin Ridout and Marcus Rowcliffe. Camera traps can be used to monitor wildlife populations. This research further develops a random encounter model for estimating animal density without individual recogisation of the animal.

Publication

Jourdain, N., Cole, D. J., Ridout, M. S. and Rowcliffe, J. M. (2020). Statistical Development of Animal Density Estimation Using Random Encounter Modelling. Journal of Agricultural, Biological, and Environmental Statistics, 25, 148-167. Paper Link

Stochastic Models for Yeast Prions

This was joint work with Lee Byrne, Mick Tuite, Martin Ridout and Byron Morgan. Certain yeast cells contain elements that behave like the mammalian prion PrP and are called yeast prions. The yeast prion, Sup35p, exists in two stable forms, giving rise to phenotypes [PSI+] and [psi-]. If the chemical guanidine hydrochloride (GdnHCl) is added to a culture medium growing [PSI+] cells, the proportion of [PSI+] cells decreases over time. This process is called curing. We devloped new stochastic models for the process of curing, including cell divsion.

Publications

Byrne, L.J., Cole, D.J., Cox, B.S., Ridout, M.S., Morgan, B.J.T. and Tuite, M.F. (2009) The Number and Transmission of [PSI+] Prion Seeds (Propagons) in the Yeast Saccharomyces cerevisiae. PLoS ONE, 4(3), e4670. doi:10.1371/journal.pone.0004670

Cole, D. J., Morgan, B. J. T., Ridout, M. S., Byrne, L. J. and Tuite, M. F.(2007) Approximations for Expected Generation Number Biometrics, 63, 1023-1030

Byrne, L. J., Cox, B. S., Cole, D. J., Ridout, M. S., Morgan, B. J. T. and Tuite, M. F. (2007) Cell division is essential for elimination of the yeast [PSI+] prion by guanidine hydrochloride. Proceedings of the National Academy of Sciences of the United States of America, 104, 11688-11693

Ridout, M. S., Cole, D. J., Morgan, B. J. T., Byrne, L. J. and Tuite, M. F.(2006) New Approximations to the Malthusian parameter Biometrics, 62, 1216-1223.

Cole, D. J., Morgan, B. J. T., Ridout, M. S., Byrne, L. J. and Tuite, M. F.(2004) Estimating the number of prions in yeast cells. Mathematical Medicine and Biology 26, 369-395.

Modelling the branching structure of strawberry inflorescences

This work was joint research with Martin Ridout and Byron Morgan. Strawberry plants grow on branches structures called inflorescences; each plant producing several of these inflorescences. Strawberry inflorescences have a variable branching structure. We devloped stochastic models for this process.

Publications

Cole, D. J., Morgan, B. J. T. and Ridout, M. S. (2005) Models for strawberry inflorescence data. J. Agric., Biol., and Environ. Statistics, 10, 411-423.

Cole, D. J., Morgan, B. J. T. and Ridout, M. S. (2003) Generalised linear mixed models for strawberry inflorescence data, Statistical Modelling, 3, 273-290