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Thesis

Efficient simulation techniques for biochemical reaction networks

Abstract:

Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemical processes. The mathematical formulations that such models lead to are opaque, and, due to their complexity, are often considered analytically intractable. As such, a variety of Monte Carlo simulation algorithms have been developed to explore model dynamics empirically. Whilst well-known methods, such as the Gillespie Algorithm, can be implemented to investigate a given model, the computat...

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Division:
MPLS
Department:
Mathematical Institute
Department:
University of Oxford
Role:
Author

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Department:
University of Oxford
Role:
Supervisor
Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
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UUID:
uuid:bb804e01-b1de-409f-b843-4806c2c990c2
Deposit date:
2017-10-26

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