Supervisors: Dr Colin Murdoch, School of Medicine/Systems Medicine and Dr Colin Henderson, School of Medicine/Systems Medicine.
Supervisors: Prof Emanuele Trucco, School of Science and Engineering, Dr Alex Doney, School of Medicine / Clinical and Molecular Medicine.
Aims and objectives. The project will use deep learning (DL) techniques to discover combinations of phenotypic and genotypic features working as predictive risk scores for high-incidence conditions (e.g. cardiovascular, diabetic complications).
Aims and objectives. The project aims to stratify diabetic patients by their response to drugs using artificial intelligence (DL) techniques, in line with the increasing interest for Big Data and AI of the School of Medicine.
Small areas of bleeding in the brain, known as cerebral microbleeds (CMB), are emerging as important features of an aging brain. Not only are they a marker for unhealthy blood vessels associated with development of dementia, but they also indicate an increased risk of major bleeding in the brain. This is particularly a concern in the common situation where doctors need to use medicines that stop clots from forming, and therefore increase risk of bleeding, to prevent heart attacks and ischaemic strokes. Although CMB are common they are not checked for routinely in conventional commonly us
The aim of this PhD proposal is to develop novel machine learning algorithms (e.g., deep learning) to predict the risk of dementia in Type 2 diabetes, and detect early signs of such disease with association of clinical and genomic data in clinical settings. There are strong links between Type 2 Diabetes (T2D) and dementia. With increasing numbers of people developing T2D, detecting early signs of dementia is important to better understand how it can be delayed or prevented.
Supervisors: (Lead): Dr Ian Morrison, Department of Neurology, Ninewells Hospital, Professor Emanuele Trucco, School of Science and Engineering, Professor Stephen McKenna, School of Science and Engineering.
The Findlay lab employs cutting-edge technologies to unravel Embryonic Stem (ES) cell signalling networks (Williams et al, Cell Rep 2016, Fernandez-Alonso et al, EMBO Rep 2017; Bustos et al, Cell Rep 2018), culminating in our recent discovery of the ERK5 pathway as an exciting new regulator of ES cell pluripotency. In order to uncover functions of ERK5 in ES cells, this project will deploy global proteomic and phosphoproteomic profiling. Novel ERK5 substrates and transcriptional networks will be characterised using biochemical and ES cell biology approaches.
Many bacterial pathogens use the Type VI secretion system (T6SS) nanomachine to fire diverse, toxic ‘effector’ proteins directly into target cells. It is becoming increasingly apparent that the T6SS plays a key role in the virulence and competitiveness of diverse Gram-negative bacteria, including important human pathogens. Pathogens can use T6SSs to directly target eukaryotic organisms, as classical virulence factors. Alternatively, many pathogens can use T6SSs to target other bacterial cells, killing or inhibiting rivals.
Our research has focused for more than 20 years on developing effective computational methods to predict the function, structure and specificity of proteins from the amino acid sequence. This has included work to characterise and predict protein-protein interactions from 3D structural information as well as from sequences and related data. Much of this experience is encapsulated in widely used software tools that include the Jalview (www.jalview.org) sequence analysis workbench which has over 70,000 regular users world-wide and JPred (
Our research has focused for more than 20 years on developing effective computational methods to predict the function, structure and specificity of proteins from the amino acid sequence. This experience is encapsulated in widely used software tools which include the Jalview (www.jalview.org) sequence analysis workbench that has over 70,000 regular users world-wide and JPred (www.compbio.dundee.ac.uk/jpred) which performs up to 500,000 predictions of secondary structure and other features from the