Dr Andrew Hoyle

Senior Lecturer

Mathematics University of Stirling, Stirling, FK9 4LA

Dr Andrew Hoyle

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About me

About me

2015-date Senior Lecturer - University of Stirling 2006-2015 Lecturer - University of Stirling 2005-2006 Research Assistant - The University of Liverpool 2002-2005 PhD - The University of Liverpool 1999-2002 BSc in Mathematics - The University of Liverpool

Education

PhD Mathematical Biology
University of Liverpool

BSc Mathematics
University of Liverpool


Research (4)

Antibiotic resistance in aquatic environments: Antibiotic resistance is one of the biggest threats the world is facing, and it affects all areas of life. We are using mathematical modelling techniques to study how resistance is spread through a bacterial population in an aquatic environment. Furthermore we use computational optimisations techniques to derive antibiotic usage strategies that will slow/prevent the build up of resistance, given various set-ups in terms of the objective function and constraints. Modelling the long-term impact of Gyrodactylus salaris on UK Atlantic salmon population: At present the UK is free of G. salaris. We are using mathematical modelling techniques to estimate the impact of a outbreak of this macro-parasite on UK Atlantic salmon population, and subsequently how the host (Salmon) will evolve a natural resistance if the parasite is left to persist in the long-term, as demonstrated by equivelnt populations in other countries. However this resistance is not free, we therefore look at how the creation of the immune response is trade-off against costs in other life-history traits. Evolution of host resistance, immunity and immune range: The immune response is one of the most powerful weapons hosts have evolved to fight parasitic infections, however there is still a lot we do not know. Here we use evolutionary techniques, including adaptive dynamics, to understand how the hosts immune system has developed. In particular, the host's immune range (whether immunity to one strain protects a host from similar strains), which will help understand why we have life-long immunity to some infections, but see continual outbreaks to various strains of another parasite over time.

Projects

Introduction to Mathematical Modelling for the environmental and biological sciences
PI: Dr Andrew Hoyle
Funded by: Natural Environment Research Council

Introduction to mathematical modelling for the environmental and biological sciences
PI: Professor Rachel Norman
Funded by: Natural Environment Research Council

Introduction to mathematical modelling for the environmental and biological sciences
PI: Professor Rachel Norman
Funded by: Natural Environment Research Council

Evolutionary behaviour
PI: Dr Andrew Hoyle
Funded by: The Carnegie Trust

Outputs (25)

Outputs

Conference Proceeding

Scott E, Nicol J, Coulter J, Hoyle A & Shankland C (2017) Process Algebra with Layers: Multi-scale Integration Modelling applied to Cancer Therapy. In: Bracciali A, Caravagna G, Gilbert D & Tagliaferri R (eds.) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science, 10477. CIBB2016: 13th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, Stirling, UK, 01.09.2016-03.09.2016. Cham, Switzerland: Springer, pp. 118-133. https://doi.org/10.1007/978-3-319-67834-4_10

Article

Denholm SJ, Hoyle A, Shinn A, Paladini G, Taylor NGH & Norman R (2016) Predicting the potential for natural recovery of Atlantic salmon (Salmo salar L.) populations following the introduction of Gyrodactylus salaris Malmberg, 1957 (Monogenea). PLoS ONE, 11 (12), Art. No.: e0169168. https://doi.org/10.1371/journal.pone.0169168

Conference Proceeding

Scott E, Hoyle A & Shankland C (2016) Process Algebra with Layers: A Language for Multi-scale Integration Modelling, Illustrated by a Cell Cycle and DNA Damage Case Study. In: Bracciali A & Caravagna G (eds.) Proceedings of Computational Intelligence Methods for Bioinformatics and Biostatistics. 13th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, Stirling, 01.09.2016-03.09.2016. Stirling: University of Stirling, pp. 240-246. http://www.cs.stir.ac.uk/events/cibb2016/index.html

Conference Paper

Scott E, Hoyle A & Shankland C (2013) PEPA'd Oysters: Converting Dynamic Energy Budget Models to Bio-PEPA, illustrated by a Pacific oyster case study. Bradley J (Editor), Heljanko K (Editor), Knottenbelt W (Editor) & Thomas N (Editor) PASM'12: Sixth International Workshop on Practical Applications of Stochastic Modelling, Imperial College London, UK, 17.09.2012-17.09.2012. Electronic Notes in Theoretical Computer Science, 296, pp. 211-228. https://doi.org/10.1016/j.entcs.2013.07.014

Research centres/groups