Queen’s Expertise

Companies working with academics from Queen’s University Belfast can engage in research across a wide range of health data related disciplines.

Research and technology areas include:

  • AI/Machine learning
  • Biobanking
  • Bioinformatics
  • Cell and Gene Therapy
  • Cybersecurity
  • Data Analytics
  • Data flow
  • Digital pathology
  • Global Health
  • Health Economics
  • High Performance Computing
  • Information visualisation
  • Large scale data
  • Linking and Mining Data
  • Nutrition
  • Population Health & Epidemiology
  • Precision Medicine

 

Health Data Science at Queen’s

Queen’s University Belfast (QUB) is committed to the effective and responsible use of data to help preserve and improve human health. Queen’s has a portfolio of world leading capability in health data science across health and life sciences, computer science and engineering. This includes assets such as two centres of excellence (Precision Medicine and Public Health), Centre for Data Science and Scalable Computing and the Centre for Secure Information Technologies; specialised facilities including High Performance Computing and Data Storage, Advanced Informatics Core Technology Unit, and the Northern Ireland Molecular Pathology Laboratory (NI-MPL). Queen’s has recently become a Substantive Site (one of only six in the UK) of Health Data Research UK (HDR-UK), a new type of health and biomedical research institute for the digital world that we now live in.

Queen’s has significant expertise in

  • comprehensive data mining using innovative platforms and algorithms allowing precise characterisation of large clinical, epidemiological and multi-omics datasets
  • the development of innovative translational bioinformatics platforms that can then underpin biomarker discovery, validation and implementation
  • scalable computing and cyber security capabilities that can deliver innovative approaches in developing novel data analytics and data security solutions.

Increasingly, Queen’s are employing a multidisciplinary approach, bringing together diverse expertise in areas such as genomics, informatics and data science, social science, national language processing and health economics, to address significant global challenges which if solved would lead to better health for patients and populations and drive increased innovation and economic benefit.