Translational data science

Drawing on Bristol’s expertise in big data, this theme brings together large, complex datasets. This enables us to develop and evaluate health interventions and predict how disease will develop.

Our work focuses on both analytical expertise and data infrastructure. Infrastructure includes data management software, platforms and integrating different organisations’ datasets. Our approach enables routine and research datasets to be combined and analysed using state-of-the-art methods.

This theme combines our:

• Innovative methods and software for large-scale genetic and molecular data analysis
• Electronic health record data infrastructure and analytical expertise

Using these, we aim to:

• Prioritise targets for intervention to prevent and treat disease
• Identify new biomarkers (biological molecules found in the blood or elsewhere in the body) that predict disease

We are building on cutting-edge research by the MRC Integrative Epidemiology Unit. We will also draw on data from large population-based studies with rich genetic, molecular and phenotypic (characteristics we can see, such as red hair) data. These include UK Biobank, Global Biobank Meta-analysis Initiative, Children of the 90s and the multi-ethnic Born-in-Bradford.

To address the needs of under-represented groups, we are developing new data analysis methods. We will apply these to a range of population health datasets from the UK and around the world.

Platforms such as OpenSAFELY and the UK Longitudinal Linkage Collaboration will allow us to analyse whole population linked administrative data. Administrative data includes information collected by public services and institutions such as the NHS and local authorities.
Our expert analysts will work with other Bristol BRC themes and external partners, to ensure everyone can benefit from our innovative approaches.