Computational Medicine

Computational approaches have had a growing impact on scientific research. With the emergence of increasing computing power, new computer algorithms and rising levels of clinical data we are now able to predict increasingly complex outcomes for patients. In our Division we have several complementary aims. One of these is to develop statistical tools to identify genetic associations of different diseases and then robustly link each one with a specific gene, cell type, stimulatory condition and ultimately to a biological pathway. Using similar techniques, we also probe the correlations relating to autoimmune diseases with the aim of understanding its causes. Such research identifies the links between different diseases, and provides opportunities to identify pharmaceutical targets. This can be used as evidence for establishing new drug development programmes and for the pharmaceutical re-purposing of existing therapies.

By incorporating health informatics, bench science, mathematics, statistics, and social sciences into classical and molecular epidemiology our division is better able to understanding disease transmission at all levels. This extends from individuals to the environment in which we live, providing us with opportunities to profile health-related settings, predict healthcare risks, and establish innovative and effective health solutions. This even includes policy support and public health intervention. As such, some of our work is conducted in partnership with Public Health England, the Cambridge University Hospitals Foundation Trust and other NHS trusts where we have applied our methods to diseases such as HIV, hepatitis C, tuberculosis, hepatitis A, influenza and norovirus. Some is also used in low and middle income countries (particularly those in Africa and South-East Asia), where we have provided insights into population genome diversity and chronic disease with the help of indigenous populations and ancient DNA. This has also allowed us to provide computational resources to African institutions.

Members of the MRC Biostatistics Unit also sit within the Division when they use allocated space in the Department of Medicine, bringing a broader wealth of expertise to the application of biostatistics to human health.

Selected Publications