Dr Schofield is Reader in Biomedical Informatics at the University of Cambridge. He gained his first degree in Biochemistry in 1981 at the University of Oxford and then went on to complete a DPhil on the integration of chromatin assembly and histone gene expression in 1984. He moved to his post in Cambridge at the then Department of Anatomy – now Physiology Development and Neuroscience – in 1990 and is a fellow of Robinson College. He holds an adjunct Professorship at the Jackson Laboratory in the USA.
Dr Schofield's research interests centre on formal descriptions of human and model organism disease, with a particular interest in using phenotype and disease ontologies for the discovery of human disease genes and their causative variants. He has ongoing interests in ontology axiomatisation, biomedical data integration and applications in machine learning and neural networks for personalised medicine.
The research he is conducting at the Turing involves extraction of patients' genome sequence and clinical data from electronic health records, and its integration with the huge volume of human genotype/phenotype information and data from fundamental experimental sciences, scattered internationally across multiple public databases. The data will be linked into a very large network, or knowledge graph, which may then be exploited using machine learning approaches to discover, for example, links between patient groups not previously suspected (patient stratification), insights into genetic overlaps between seemingly unrelated diseases and traits, and new predictors of prognosis, clinical events and responsiveness to therapy.