School of Life Sciences

University of Dundee

Computational Biology

MRC DTP 3.5 Year iCASE Project: Machine learning to predict drug penetration into Gram-negative bacteria

An alarming rise in pathogens that show antibiotic resistance has been observed over recent years. In the case of Gram-negative bacterial pathogens, the resistance crisis has started to go out of control. Due to the lower permeability of the Gram-negative cell envelope for antibiotics, these pathogens are inherently more difficult to treat. The lower cell penetration of new drug candidates is also reflected in the failure of medicinal chemistry to advance novel classes of compounds with Gram-negative activity.

MRC DTP 4 Year PhD Programme: Dealing with proteotoxic stress: How do cells tidy up when trash piles up?

Degrading proteins in a timely manner to dispose of misfolded and damaged proteins is essential for a healthy cell. In ageing cells and organisms, there is a deterioration in the ability of cells to clear proteins resulting in the accumulation of misfolded proteins. Deposition of misfolded protein aggregates is a hallmark of many neurodegenerative diseases. It is not understood why quality control systems and the degradation capacity of a cell decline with age.

MRC DTP 4 Year PhD Programme: Dissecting the epigenetic regulation of enhancer function in hematopoiesis

The epigenetic mark of DNA methylation is established by DNMT (DNA methyltransferase) enzymes and has been shown to correlate with transcriptional states and influence cell identity and tumorigenesis in mammalian cells. The recent discovery that TET (Ten-Eleven-Translocation) enzymes produce 5-hydromethylcytosine (5hmC), 5-formylcytosine (5fC), 5-carboxycytosine (5caC) and mediate active DNA demethylation in the genome has opened a new avenue to understand how DNA methylation dynamics affect transcriptional programs1.

BBSRC EASTBIO PhD Programme: Tackling the problem of ‘Big Data’ in Molecular Biology and Genomics: Advanced sequence alignment visualisation and analysis for molecular function prediction

This project should appeal to a student who will most likely have a background in computer science or other subject with strong experience in algorithm development. They will extend their skills to the challenging problem of visualising ‘big data’ in biology. They will also gain experience of communicating their achievements to a wide biological research audience through distribution of their software to a large user-base as well as conventional seminars and meetings.