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Advanced analysis of rich datasets deepens our understanding

health data, scientist looking at a tablet, BDI building

Combining and analysing data from different sources gives us powerful ways to find markers of disease, target the development of new treatments, and test the efficacy of potential interventions. From specialist teams developing new computational tools to individual researchers analysing a bespoke experiment, data underpins all our research.

The Big Data Institute brings together researchers from medicine and population health for the analysis of large and complex datasets for research into the causes and consequences, prevention and treatment of disease. The approaches they develop are invaluable in identifying the associations between lifestyle exposures, genetic variants, infections and health outcomes around the globe.

Many of our researchers contribute to the broadening approach of characterising the complex sets of molecules that make up each individual person, with a wide range of techniques that together are colloquially known as ‘omics’. From DNA (genomics) to microbes (microbiomics), studying the full complexity of the human body allows us to understand better the progression of disease and success of treatments. Images at many scales – from tissue sample to the whole body - are crucial source of information and increasingly are analysed as data, leading to ‘intelligent' medical imaging and in turn better diagnoses.

Electronic health records collected as part of standard clinical care, national biobanks and targeted cohorts contain detailed information about a patient’s clinical history. Analysis of these on a large-scale enables us to identify the individuals with the highest risk of disease, or those likely to respond positively to specific treatments.

Examples of the unique resources that Oxford researchers both support and benefit from include very large cohort datasets (e.g. The Million Women Study, Our Future Health), major biobanks (e.g. UK Biobank and China Kadoorie), and new collections of electronic health data including  QResearch and OpenSAFELY, both set up to help tackle COVID-19. The Million Women Study has provided reliable findings on the role of lifestyle factors in risks of cancer, as just one example. The Bennett Institute for Applied Data Science is pioneering the better use of data, evidence and digital tools in healthcare and policy.

Our Clinical Trials Units support rigorous and secure data collections and analysis in our numerous trials and studies. Many of our research groups benefit from dedicated statisticians and bioinformaticians who provide crucial expertise in designing studies and assembling and analysing biomedical datasets.

A number of our research groups use computational methods to model the outcomes of different approaches, for example to control the spread of tropical diseases and COVID-19, which have led to changes in government policy and lives saved around the world.