Our research leverages big data in genetics and genomics for medically important human traits. We aim to translate insights from genomics into mechanisms of disease development and progression, shortening the path to translation and empowering precision medicine.

Our overarching aims are to:

  • Characterise the genetic architecture of common complex diseases of high public health burden;
  • Generate insights into the biological mechanisms underpinning chronic disease development and progression;
  • Develop robust methods for integrating big data to address key biomedical challenges;
  • Catalyse pathways to translation for disease prognosis, management and treatment.

We integrate information gleaned from deep molecular, genomics and epidemiological approaches to address important biomedical research challenges. The field of complex trait genetics has witnessed a revolution in technological advances, and genome-wide interrogation of sequence variation has led to the discovery of thousands of risk loci. Methodological advances have also enabled deep molecular characterisation of disease-relevant primary tissues collected from patients, or studied in cellular and organismal models of disease. The next steps require powerful consolidation of these approaches across a range of populations, to enhance our understanding of the genetic and genomic aetiology of disease development and progression, and to move from discovery to functional interpretation and ultimately to clinical application. Our approach is underpinned by data generation at scale and by the development of computational genomics toolkits to analyse the wealth of information.

Research strands
The Institute of Translational Genomics brings together research strands in:

  • Next generation genomics studies of diverse populations with deep phenotype data;
  • Large-scale genetics and genomics studies leveraging national and international epidemiological cohorts, coupled to disease registries and electronic health records, including imaging;
  • Integrated multi-omics and systems genomics.

The research environment is underpinned by a strong focus on open and wide collaborative interactions, career development, and diversity and inclusion. Team science is a key overarching feature, fostering links across interdisciplinary teams and bringing together talent across the computational biology, molecular genomics, statistics and clinical fields internationally.

We use cookies to improve your experience on our Website. We need cookies to continually improve our services, enable certain features, and when we embed third-party services or content, such as the Vimeo video player or Twitter feeds. In such cases, information may also be transferred to third parties. By using our website, you agree to the use of cookies. We use different types of cookies. You can personalize your cookie settings here:

Show detail settings
Please find more information in our privacy statement.

There you may also change your settings later.