Tom Pugsley

Profile

Project Title: A machine learning approach to optimise cyanobacteria for use in biotechnology

Summary: Developing accurate models of complex biological systems is essential to understanding how best to manipulate them for exploitation in biotechnology. One such example are cyanobacteria, which are increasingly being used as biofactories, but are in the early stages of domestication. Typically, building bottom-up systems-level models requires a deep theoretical understanding of the system. As the relationship between a mutation and its functional consequences is so non-linear, most traditional kinetic models are rendered useless. Machine learning has the potential to overcome these issues and allow computational modelling to inform cyanobacterial optimisation strategies for use in biotechnology.

Supervisor:

• Dr Guy Hanke

Research