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Found 2 matching student topics

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Representation learning for anti-microbial resistance

This project is about using neural network models help us understand Anti-Microbial Resistance (AMR), a phenomenon in which bacteria adapt to reduce the effectiveness of antibiotics, usually through a process known as Lateral or Horizontal Gene Transfer - where genes are included in the organism from other sources.Our focus will be on learning compact vector representations of biological sequences known to be associated with AMR genes. By encoding DNA sequences in this way we can more rapidly identify AMR genes …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Understanding capsular polysaccharide diversity is key to next generation therapies for multi-drug resistant Acinetobacter baumannii infections

Bacteriophage therapy is an attractive innovative treatment for infections caused by extensively drug resistant Acinetobacter baumannii, for which there are few effective antibiotic treatments remaining.Capsular polysaccharide (CPS) is a primary receptor for lytic bacteriophage, thus knowledge of the chemical structures of CPS produced by the species underpins the identification of suitable phage for therapeutic cocktails.As many phage depolymerases cleave a specific CPS linkage formed by either a glycosyltransferase or polymerase enzyme, characterisation of these proteins are essential.However, these remain largely …

Study level
PhD
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)

Centre for Immunology and Infection Control

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