School of Mathematical Sciences

Statistics and Probability Seminar: 2nd year PhD student talks

Date(s)
Thursday 4th December 2014 (15:00-16:00)
Contact

David Sirl

Description

2nd year PhD student talks (see also 27th Nov)

Anthony Hennessey: Determining Amino Acid Conformers using Statistical Shape Analysis

Ryan Howitt: Stochastic modelling of repeat-mediated phase variation in Campylobacter jejuni

Ben Davis: The impact of degree distribution on network epidemic models with casual contacts

Abstracts

 

Anthony Hennessey
Determining Amino Acid Conformers using Statistical Shape Analysis

Ab Initio methods for modeling protein structure from first principles using physical laws rely heavily on rotamer libraries for amino acids. Rotamer libraries are developed from theoretical models which are subsequently adjusted in light of experimental data. This talk describes an alternative approach to creating rotamer libraries using statistical shape analysis of the large amounts of experimentally determined amino acid structure data available in Worldwide Protein Data Bank.

Ryan Howitt
Stochastic modelling of repeat-mediated phase variation in Campylobacter jejuni

The bacteria Campylobacter jejuni is the main cause of foodborne illness in the UK. Particular genes have phase variable properties in which the protein expression experiences a reversible ON or OFF change due to high frequency mutations of poly-G/poly-C tracts. A stochastic model for describing behaviour of phase variation is considered. The model takes into account mutation and selection mechanisms. I shall discuss properties of this model and estimation of its fitness parameters using ABC methods.

Ben Davis
The impact of degree distribution on network epidemic models with casual contacts

We consider a SIR (Susceptible - Infected - Removed) epidemic on a population with network and casual (homogeneously mixing) contacts. For a given degree distribution and epidemics with fixed basic reproduction number (R_0> 1) we examine the effect of the relative transmission rates for network and casual contacts on the final outcome of the epidemic. We will conclude by briefly describing some extensions to the underlying model such as including household structure and vaccination strategies.

School of Mathematical Sciences

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