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Title: Individual Based Modelling of Bacteria-Bacteriophage Interactions
Author: Grew, Edward Nicholas Delung
ISNI:       0000 0001 3518 9999
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2007
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This thesis presents a novel individual based model capable of simulating the types of behaviour observed between bacteria and phage. Parasite-host relationships in bacterial ecology have commonly been modelled using a top-down differential ~quation approach tnat describes populations as single entities. These biological systems are intrinsically based on individuals whose behaviour relies on the interactions of many. A bottom-up, individualbased modelling approach has been used to simulate the behaviour observed between a bacterium and its corresponding bacteriophage. The use of individual based models has gained in popularity with the development of more powerful computers and is firmly established within current literature. The object-oriented programming language Java has been used to create Single, Co and Super infection models and the agent-based software Netlogo used to create a spatially explicit model. All the models were able to successfully recreate the real-life dynamics of bacteria and bacteriophage. Parameter space was explored within the models to investigate the effect of resource enrichment and flow rate within· a chemostat environment and to predict the persistence of phag~ within a bacterial population. An emergent individual based methodology founded on solid experimental data has forged a novel model that can highlight specific areas for further research and provide support for the outcome of investigational studies. Predicted future improvements In computing power will allow for the boundaries and possibilities of ecological modelling to be expanded and this work provides a basis from which to examine this pote~tial. These models provide scope for the investigation of a wide range of organisms as well as studies of parasite virulence, spatial dynamics and adaptive responses to selection pressures.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available