Research at Oxford Lifelong Learning
Researchers at Oxford Lifelong Learning carry out research on a range of topics in the fields of data science, computing and maths. Research is currently focused on the following areas:
- Big data approaches to identifying genes that make microbes more dangerous by increasing the frequency or severity of disease, or by conferring drug resistance;
- Implementing computational tools for analysing thousands of microbial genomes;
- Developing statistical theory for joint Bayesian and classical hypothesis testing.
RESEARCH HIGHLIGHTS
- Discovering antibiotic resistance genes in tuberculosis, in collaboration with the CRyPTIC project
- Finding human genes that make people more susceptible to COVID-19, in collaboration with the COVID-19 Host Genetics Initiative
- Linking microbiological data from the UK Health Security Agency to UK Biobank to facilitate large-scale research into infection, including COVID-19
- Harnessing machine learning to predict which types of contaminated meat led to food poisoning cases using DNA
- Identifying a notorious toxin as the cause of tropical muscle Staphylococcus aureus infections in Cambodian children, in collaboration with the Oxford Tropical Network
- Developing the harmonic mean p-value to improve the detection of signals in big data problems while controlling false positives
