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Using Machine Learning and Artificial Intelligence to Identify Novel Antibiotics in Predatory Bacteria

   Department of Computer Science

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  Dr Wayne Aubrey , Dr A Clare  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Project Description:

The discovery of antibiotics has transformed medical practice. They have saved countless lives through the treatment of infectious diseases that were the leading cause of mortality for the majority of human existence. Misuse of antibiotics over the last 50 years has contributed to an antimicrobial resistance (AMR) crisis which kills an estimated 700,000 people annually at a societal cost of billions. AMR is predicted to be the major cause of death (10M annually) by 2050 (O’Neill Report on AMR, 2016).

Myxobacteria kill and eat other bacteria and their genomes have been likened to natural pharmaceutical factories rich in novel antibiotics. IBERS probably contains the largest collection of myxobacteria isolates and sequenced genomes, worldwide. This project aims to identify these antibiotics and demonstrate their potential value to healthcare?

IBERS currently has over 100 sequenced Myxobacteria genomes many supported with phenotypic data. We will develop and use machine learning and data mining to predict and elucidate the antibiotic mechanisms that these genomes contain. The data is diverse and

structured (DNA and protein sequences, reaction graphs, structured phenotypes, phylogenetic/hierarchical background information, and assay results). The analysis will include the use of cutting-edge data analysis including network analysis, deep learning, vector space analysis, and graph-based databases. We will aim to build models that allow us to extract understanding of antibiotic action that can be tested in the laboratory, using the extensive Myxobacteria collection here at AU.

Members of the Bioinformatics and Computational Biology research group cover the full breadth of these timely and important developments and offer a diverse set of possible PhD projects in these areas. See for more information.

Funding Notes

-       Excellent candidates can be recommended to AberDoc scholarship(, deadline: 14. Jan, 2022), which will cover their tuition fees (up to the UK rate of £4,500 per annum*) and a maintenance allowance of approximately £15,609 per annum* and access to a travel and conference fund (max. £500 per annum*) will also be provided. 

-       Outstanding international candidates can also be recommended to the Departmental Scholarship, which will reduce the international tuition fee to a home fee.

How to Apply

Applications through Aberystwyth’s electronic application process (How to apply:Study With Us , Aberystwyth University), include the following attachments in pdf form:

-        CV

-       Degree certificates and transcripts (if you are still an undergraduate, provide a transcript of results known to date)

-       A statement no longer than 1000 words that outlines your research. Academic references - all scholarship applications require two supporting references to be submitted. Please ensure that your chosen referees are aware of the funding deadline (to be determined), as their references form a vital part of the evaluation process. Please include these with your scholarship application.

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