4 research outputs found
Nonequilibrium statistical physics applied to biophysical cellular processes
The methods of statistical physics are increasingly being employed in a range of
interdisciplinary areas. In particular, aspects of complex biological processes have been
elucidated by bringing the problems down to the level of simple interactions studied
in a statistical sense. In nonequilibrium statistical physics, a one dimensional lattice
model known as the totally asymmetric simple exclusion processes (TASEP) has become
prominent as a tool for modelling various cellular transport processes. Indeed the context
in which the TASEP was first introduced (MacDonald et. al., 1968) was to model ribosome
motion along mRNA during protein synthesis. In this work I study a variation of the
TASEP in which particles hop along a one dimensional lattice which extends as they
reach the end. We introduce this model to describe the unique growth dynamics of
filamentous fungi, whereby a narrow fungal filament extends purely from its tip region
while being supplied with growth materials from behind the tip. We find that the steady
state behaviour of our model reflects that of the TASEP, however there is an additional
phase where a dynamic shock is present in the system. I show through Monte Carlo
simulation and theoretical analysis that the qualitative behaviour of this model can be
predicted with a simple mean-field approximation, while the details of the phase behaviour
are accurate only in a refined approximation which takes into account some correlations.
I also discuss a further refined mean-field approximation and give a heuristic argument
for our results. Next I present an extension of the model which allows the particles to
interact with a second lattice, on which they diffuse in either direction. A first order meanfield
continuum approximation suggests that the steady states of this system will exhibit
some novel behaviour. Through Monte Carlo simulation I discuss the qualitative changes
that arise due to the on-off dynamics. Finally I study a model for a second biological
phenomenon: the length fluctuations of microtubules. The model describes stochastic
polymerisation events at the tip of a microtubule. Using a mean-field theory, we find a
transition between regimes where the microtubule grows on average, and where the length
remains finite. For low rates of polymerisation and depolymerisation, the transition is in
good agreement with Monte Carlo simulation
Nonequilibrium statistical physics applied to biophysical cellular processes
The methods of statistical physics are increasingly being employed in a range of interdisciplinary areas. In particular, aspects of complex biological processes have been elucidated by bringing the problems down to the level of simple interactions studied in a statistical sense. In nonequilibrium statistical physics, a one dimensional lattice model known as the totally asymmetric simple exclusion processes (TASEP) has become prominent as a tool for modelling various cellular transport processes. Indeed the context in which the TASEP was first introduced (MacDonald et. al., 1968) was to model ribosome motion along mRNA during protein synthesis. In this work I study a variation of the TASEP in which particles hop along a one dimensional lattice which extends as they reach the end. We introduce this model to describe the unique growth dynamics of filamentous fungi, whereby a narrow fungal filament extends purely from its tip region while being supplied with growth materials from behind the tip. We find that the steady state behaviour of our model reflects that of the TASEP, however there is an additional phase where a dynamic shock is present in the system. I show through Monte Carlo simulation and theoretical analysis that the qualitative behaviour of this model can be predicted with a simple mean-field approximation, while the details of the phase behaviour are accurate only in a refined approximation which takes into account some correlations. I also discuss a further refined mean-field approximation and give a heuristic argument for our results. Next I present an extension of the model which allows the particles to interact with a second lattice, on which they diffuse in either direction. A first order meanfield continuum approximation suggests that the steady states of this system will exhibit some novel behaviour. Through Monte Carlo simulation I discuss the qualitative changes that arise due to the on-off dynamics. Finally I study a model for a second biological phenomenon: the length fluctuations of microtubules. The model describes stochastic polymerisation events at the tip of a microtubule. Using a mean-field theory, we find a transition between regimes where the microtubule grows on average, and where the length remains finite. For low rates of polymerisation and depolymerisation, the transition is in good agreement with Monte Carlo simulation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Identification of seven new prostate cancer susceptibility loci through a genome-wide association study
Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we have previously conducted a genome-wide association study in which 541, 129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and 1,894 controls. We have now evaluated promising associations in a second stage, in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls, and a third stage, involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to previously identified loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11, and 22 (P=1.6×10−8 to P=2.7×10−33)