Genomics and Life Sciences

Queen Mary University of London has extensive expertise in AI/ML and computational modelling across multiple areas of genomics and life sciences. The approaches range from automated scientific discovery to the development of advanced processing methodologies. This involves data acquired across scales from atomic structures to dynamics of living systems, to their organisation in sub-cellular assemblies, cells, tissues, and organs. 

Examples of staff working in these fields: 

• Prof Viji Draviam combines single-cell microscopy with molecular and biochemical approaches to collaboratively develop computational tools to extract single-cell metrics. 

• Prof Conrad Bessant works on automation of scientific discovery in the biomedical domain using machine learning, logic modelling, network science and Bayesian inference. 

• Dr Chris Duffy uses theoretical and computational methods including AI and machine learning in plant biology, with applications ranging from understanding how plants harvest energy efficiently yet safely, to exploring the limits of photosynthesis on stars such as the red dwarf. 

• Dr Matteo Fumagalli has pioneered the use of machine learning algorithms for the inference of past demographic human history from genomic data. He has also established the EvoGenomics.AI website for the dissemination of new findings, including a review in the application of Artificial Intelligence in evolutionary genomics. 

Research Centres:  
Centre for Evolutionary and Functional Genomics; Centre for Molecular Cell Biology.