2009 intake

   
Sophie Atkinson Roles of non-coding RNAs in cellular lifespan of fission yeast
Joe Bailey Multimarker Nanosensors for monitoring the progression of HIV
Maria Botcharova Scale-free behaviour in resting state human neurological signals: analysis of experimental data and modelling of putative mechanisms.
Hywel Carver Improving simulation of blood flow in the neurovasculature to assist surgeons
Zena Hadjivasiliou Evolution of the eukaryotic cell and somatic complexity
Charlie Harrison Rare codons in optimal gene design
Nicolas Jaccard Controlled embryonic stem cells expansion and directed differentiation in perfusion-based microfluidic bioreactors
Mirna Kovacevic Integrating Archaeological Material Culture and Genetic Data Using Demographic Simulation
Donal O'Donoghue Quantitative Modelling of Ion and Water Transport in Bronchial Epithelia
Abbygail Shaw Modelling fibroblast dependent wound healing and scarring in the injured heart
David Sheehan Examining the membrane dynamics of GABAA receptors in brain slices using quantum dots
Niclas Thomas Migration, Recirculation & Search: Modeling T Lymphocyte Recirculation in the Immune System
Gordon Walsh New dynamic models of cell signalling through phosphoinositide metabolism
James West Network Physics and Cancer Systems Biology
   
   
Sophie Atkinson

Roles of non-coding RNAs in cellular lifespan of fission yeast


Supervisors: Professor Jürg Bähler; Dr. Elia Stupka; Dr. Robin Ketteler

Recent data indicate that transcriptomes contain hundreds of non-coding RNAs (ncRNAs) of largely unknown functions.  In my project I am using fission yeast cells, undergoing the transition from rapid proliferation to quiescence, as a simple model system for understanding the basic mechanisms of aging and cancer.  Using a combination of RNA-sequencing, genetic and cell biological approaches I am examining the roles of ncRNAs during cellular ageing.

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Joe Bailey

Multimarker Nanosensors for monitoring the progression of HIV

Supervisors: Rachel McKendry, Joseph Ndieyira and Gabriel Aeppli

Cantilever based biosensors have great potential for detecting bio-molecules at extremely low concentrations with minimal disruption to the sample (in liquid and free from tags). They are cheap to manufacture making use of technologies well established in silicon valley and potentially highly parallelisable, fitting well with other lab-on-a-chip technologies. 

Monitoring the progression of HIV in patients is extremely important to the effective use of highly active antiretroviral therapy (HAART). With the role out of such therapies to the developing world the challenges involved in this process are increasingly becoming a bottleneck in global efforts to minimize the suffering caused by HIV.

The work being carried out aims to aid in the development of the aforementioned technologies particularly with the intention of developing a practical and readily implementable solution to the  problem of monitoring disease progression in HIV positive patients.

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Maria Botcharova

Scale-free behaviour in resting state human neurological signals: analysis of experimental data and modelling of putative mechanisms



Recent research using human EEG, MEG and FMRi signals reveals spontaneous fluctuations in background activity during resting states. These signals exhibit reproducible patterns of neuronal activity which are then modulated by task. Research to date has shown that resting state spontaneous activity exhibits correlations at multiple spatial and temporal scales suggesting the presence of underlying scale free processes. There is preliminary evidence for scale free behavior in the EEG of young children and preterm neonates, and it has been suggested that these behaviours may follow a developmental trajectory. I am currently focusing on identifying scale free behaviours in resting state data from healthy adults. I will proceed to use bio-constrained modelling of key thalamo-cortical pathways to generate hypotheses about the developmental mechanisms underlying (a) the genesis of this background activity and (b) the transition from infant to adult, in particular, in relation to the putative homeostatic role of long-range temporal correlations.
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Hywel Carver

Improving simulation of blood flow in the neurovasculature to assist surgeons


Supervisors: Prof. Peter Coveney and Dr. Stefan Brew.

Patient-specific medicine gives us the opportunity to improve the success of medical intervention by customising treatment to the patient under consideration. This project will extend and improve HemeLB, a Lattice-Boltzmann-based simulator of neurovascular haemodynamics. The ultimate aim is to produce software to assist a surgeon's decision-making, in real-time
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Zena Hadjivasiliou

Evolution of the eukaryotic cell and somatic complexity


Supervisors: Andrew Pomiankowski (GEE); Nick Lane (GEE); Rob Seymour (Maths).

The evolution of the eukaryotic cell presents a number of challenges to understanding. In the course of my PhD I will attempt to address several of them. I am particularly interested in the evolution of somatic complexity in multicellular organisms and will consider a number of different elements such as the evolution of sexual reproduction, mitochondrial and nuclear gene interactions and somatic versus germline mutations.
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Charlie Harrison

Rare codons in optimal gene design


Supervisors: Prof. John Ward (Molecular Biology) and Prof. David Jones (Computer Science)

The universal genetic code is a mapping from 64 codons and 20 amino acids.  This redundancy means that there are multiple ways of encoding a given protein.  Where an amino acid has several codons that specify it, some codons are used more frequently than others.  Although the mapping itself is shared across all known life, the preference for one synonymous codon over another varies between species.  The significance of synonymous codon usage is not well understood, but present wisdom in synthetic biology dictates that when designing a gene, the favoured codons of the intended host species should be used wherever possible.  In this project we will be examining cases where rare codons appear to be used preferentially, and how this might be important for effective expression of proteins.
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Nicolas Jaccard

Controlled embryonic stem cells expansion and directed differentiation in perfusion-based microfluidic bioreactors


Supervisors: Nicolas Szita (Microfluidics, Biochemical Engineering), Farlan Veraitch (Regenerative Medicine, Biochemical Engineering)

Embryonic stem cells are self-renewable, meaning they can undergo an infinite number of divisions. They are also pluripotent and can give rise to most adult cell types through differentiation. These properties make them a potentially unlimited source of material for developmental biology, drug discovery and regenerative medicine. However, the mechanisms involved in stem cells fate determination remain poorly understood.

The goal of the project is to develop an automated microfluidics-based platform for stem cells bioprocessing. Both expansion and directed differentiation of mouse embryonic stem cells under strictly controlled conditions will be studied and interpreted using machine vision techniques based on live cell imaging and fluorescence microscopy. The resulting data will be used to devise a model of the cells’ response to perturbations in their microenvironment and could potentially lead to more efficient stem cells bioprocesses.

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Mirna Kovacevic

Integrating Archaeological Material Culture and Genetic Data Using Demographic Simulation


Supervisors: Mark Thomas (GEE), Kevin Bryson (Computer Science) and Stephen Shennan (Archaeology)

 It has recently been shown that demographic processes are a major determinant of patterns of genetic variation, including gene-culture co-evolution and spread of selectively advantageous variants, as well as of the accumulation, or loss, and spatial distribution of culturally transmitted skills, behaviours and material culture. There is also increasing evidence that demographic processes are behind many of the major changes observable in the archaeological record.


This project aims to apply spatially explicit simulation modelling and Approximate Bayesian Computation to explore how human demographic history and cultural transmission processes have shaped geographic patterns of material culture, as evidenced in the archaeological record. Simulations will model how factors such as migratory activity and population growth and decline influence the appearance and demise of prehistoric cultures, as well as the effects of climatic and environmental factors affecting the demography. A wide range of parameter values will be explored within an environmental framework and simulations will be conditioned on patterns of genetic data and distribution of material culture variation. By simultaneously conditioning on both genetic and cultural data, it is possible to integrate these different data sources in a robust statistical framework.

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Donal O'Donoghue

Quantitative Modelling of Ion and Water Transport in Bronchial Epithelia


Supervisors: Dr Paola Vergani (UCL Department of Neuroscience, Physiology and Pharmacology), Dr Vivek Dua (UCL Department of Chemical Engineering) and Dr Guy Moss (UCL Department of Neuroscience, Physiology and Pharmacology)

Cystic Fibrosis (CF) is a common monogenetic disease which impairs quality of life and reduces life expectancy. CF is caused by loss-of-function mutations in CFTR, a Cl- channel, however how CFTR mutations produce the symptoms of CF remains unclear.
In my research I try to understand how the symptoms of CF that present in the airway epithelia of patients arise from the underlying genetic cause. Particular aspects that I am interested in explaining are how the trans-epithelial potential difference (PD) is generated and maintained by different transport proteins (such as CFTR & ENaC, epithelial sodium channel), and how the airway surface liquid (ASL) depth is functionally related to the trans-epithelial PD and maintained by the activity of these proteins.

The kinetics of ion and water transport in an epithelial cell are determined by complex interactions between the electrical, chemical and osmotic gradients that are present across the polarised epithelial layer. Hence the epithelium can be considered as a dynamical system, and a model description of epithelial transport in terms of driving forces and fluxes can be created. Challenges arise in implementing numerical simulations of these model systems, due to a lack of homogeneous experimental data with which to fully characterise the functioning of the epithelium. In my project I use different optimisation and parameter estimation techniques to minimise deviations between expected physiological behaviours and observed model behaviour, in a range of different experiments. I am also interested in the use of global sensitivity analysis techniques as a means of fully exploring the non-linear relationships between input and outputs in complex model systems (for example, exploring the non-linear relationship between CFTR activity and trans-epithelial PD).

The project utilises techniques from applied and engineering mathematics, and integrates data from a range of electrophysiological and clinical studies. The use of mathematical modelling in the study of CF will allow different hypotheses about the pathogenesis of the disease to be investigated in a quantitative manner, and it also allows us to conceptually address the question of what therapeutic interventions can be made to reverse the symptoms due to CFTR mutations.
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Abbygail Shaw

Modelling fibroblast dependent wound healing and scarring in the injured heart


Supervisors:
Prof. Paul Riley and Prof. Peter Hammond

Myocardial infarction(MI) results from an occlusion in the vasculature supplying the heart tissue which cuts off the supply of oxygen to the cells within the region downstream of the blockage. This area of ischemia then results in a reduction in energy metabolism and death of cardiac tissue. The biological response to this is inflammation and initiates the formation of a fibrotic scar as a substitute for the loss of cardiac tissue. A common outcome for post MI patients is a loss of cardiac function, which is a major risk factor in cases of heart failure. This loss in function is suggested to be related to the level of scarring that occurs post MI. This research aims to develop a biologically realistic and predictive mathematical model of wound healing and the subsequent scarring process in the heart following MI. This work will involve input from both experimental and mathematical methods.

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David Sheehan

Examining the membrane dynamics of GABAA receptors in brain slices using quantum dots


Supervisors: Dr. Josef Kittler (Neuroscience) & Dr. Lewis Griffin (Computer Science)

GABAA receptors are the primary source of fast inhibition in the mamallian brain. As such, they play a pivotal role in fundamental neurological processes. Quantum dots (QDs) have been employed to observe the dynamic behaviour of these receptors in real time. QDs are brightly fluorescent semi-conductor nano-crystals that, owing to their strong photostability and favourable fluorescence characteristics, enjoy substantial advantages over alternative single particle tracking techniques, such as GFP and organic dyes.

Previous studies using QDs have focused on neurotransmitter receptors in cultured neurons. My PhD project aims to accurately identify and track QD bound GABAA receptors in brain slices, where the detection environment presents considerable complications. This will involve live cell imaging and the application of machine learning techniques to efficiently determine QD bound receptors from the experimental data.

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Niclas Thomas

Migration, Recirculation & Search: Modeling T Lymphocyte Recirculation in the Immune System


Supervisors: Prof. Benny Chain and Prof. John Shawe-Taylor

Adaptive immunity is initiated when foreign antigen, displayed on the surface of dendritic cells (DCs), is recognised by a relevant T cell. With only 1 in 105 – 106 T cells actually able to recognise a given antigen, a T cell’s journey through the body can be likened to finding a “needle in a haystack”, as it searches the lymph node for a relevant DC presenting cognate antigen. The problems a T cell faces in finding a relevant DC are aided by its recirculation through the body, a characteristic feature of every vertebrate, and particularly mammalian, adaptive immune systems. The process of recirculation enables T cells to constantly search the host for DCs presenting cognate antigen. We are interested in determining the characteristic features of this recirculation process, such as the distribution of times that a T cell typically spends in a lymph node and the distribution of times that 1, 2 or n T cells would be expected to spend to locate a cognate DC.
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Gordon Walsh

New dynamic models of cell signalling through phosphoinositide metabolism


Supervisors: Geraint Thomas (Cell & Developmental Biology) and Kevin Bryson (Computer Science)

Cellular signalling is the process in which cells process and transmit information both internally and externally. The aim of my research is to develop new dynamic modelling techniques of signalling pathways through ODE, PDE and stochastic differential equation based models. In particular I am investigating the dynamic properties of the phosphoinositde cycle which is ubiquitous in eukayotic organisms and is highly important in calcium signalling, cell growth and many other areas.

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James West

Network Physics and Cancer Systems Biology


Supervisors: Dr. Andrew Teschendorff (Medical Genomics, UCL Cancer Institute) and Dr. Simone Severini (Honorary Research Fellow, Department of Physics and Astronomy).

The last few years have seen a massive increase in cancer genomic data, including molecular profiles encompassing mRNA expression, single nucleotide polymorphism (SNP), genomic copy number and epigenomic data. We are now faced with the challenge of integrating these different data modalities together in order to realise their full potential and to lead to tangible improvements in clinical management. Recent statistical approaches have combined structural network models of signal transduction pathways with gene expression but much less has been done in integrating these network pathway models with cancer genomic profiles. A network-based perspective to integrating such diverse data types offers the potential of (i) obtaining fundamental systems-level insights into cancer biology, (ii) identifying novel genes and pathways driving the oncogenic process and (iii) proposing novel molecular and clinically relevant classifications of cancer.
This project will investigate the application of ideas from network physics, combinatorics, and information theory in the context of cancer genomics. In particular, novel information theoretic quantities and notions with their origins in the physical sciences will be applied for the first time in biology and this opportunity would constitute a fertile ground for their further analysis. For example, there are many suitable notions of entropy relevant to the cancer cell and studying the particular genes, pathways and even the entire signalling hierarchy offers systems level insight.

Challenges in the physical sciences that could be addressed in the project include models for the growth of the various biological networks arising from the data. Their topological structure exhibits many recently discovered phenomena that are inconsistent with the existing models of network growth. Such models can subsequently be studied by considering their limit graphs and spectra.
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