Artificial intelligence

We are using artificial intelligence (AI) to advance our understanding and treatment of cancer.

Modern experiments generate vast amounts of complex data that can be hard analyse. AI and machine learning help us to process this data more effectively, uncovering new patterns and insights. 

The Brenton and Markowetz Groups have used AI to identify patterns of chromosomal instability, the frequent changes in the number or structure of chromosomes within cancer cells. These patterns help us understand the mechanisms that drive cancer development and enable us to predict vulnerabilities in cancer cells.  

The Markowetz Group has also used AI to classify imaging data from radiological images and cell samples, including those collected with the Cytosponge method for monitoring Barrett’s oesophagus to save pathologists time by automating the analysis process. The Ali Group and IMAXT Lab use machine learning to analyse spatial profiling data, helping to identify cellular signals and variations in tissue organisation.  

We aim to expand our use of AI to generate new research hypotheses and explore further areas of cancer biology. By developing AI models trained on extensive datasets, we aim to place computational biology at the core of our discovery process. This approach will enable us to uncover new insights and improve patient outcomes, ultimately transforming cancer research and treatment.