Our four main research themes range from basic science to population health
Statistical Omics (SOMX) is centred on developing and implementing new analytical strategies for integrative and translational genomics as well as epidemiological studies enriched with genetics data, opening up to statistical issues arising from newomics technologies. Issues of efficient inference and scalability of computations for big data are a particular focus.
Precision Medicine and Inference for Complex Outcomes (PREM) focuses on the methodological issues arising from the development of precision medicine, the need to stratify complex disease phenotypes and to perform integrative clustering based on multiple data types, to tailor risk prediction and to analyse complex longitudinal data.
Design and Analysis of Randomised Trials (DART) develops adaptive and novel trial designs that are ever more efficient at flexibly answering the key clinical questions of interest. It targets the translation of methods into practice with software production and dissemination activities.
Statistical methods Using data Resources to improve Population Health (SURPH) is directed to tackle the statistical challenges in addressing causality (disease aetiology), estimating and predicting disease burden and evaluating public health policies using data from publicly-available sources which are of different types, potentially subject to selection biases and likely of large dimension.