Biomolecular control group

what we do

Our team develops methods to study molecular processes in living cells. We use mathematics and computation to understand natural networks and to design novel systems for biotechnology and biomedicine. We employ a wide range of methods, such as machine learning, control theory, stochastic analysis and network theory. Large parts of our work are in collaboration with Systems and Synthetic Biology labs in the UK and abroad.

who we are

The group lead is Diego Oyarzún and includes research students and postdocs. Together we gather expertise in many disciplines like machine learning, mathematics, biochemistry and bioinformatics.

where we work

We are very lucky to be located at the School of Informatics and the School of Biological Sciences of the University of Edinburgh, in one of the most vibrant European capitals. We are members of the Edinburgh Centre for Engineering Biology.

our recent science

• Representation learning of single cell time-series data
• Deep mutational learning for improved enzyme function
• Machine learning and genome-scale metabolic models for gene deletion phenotypes
• Active learning for DNA sequence optimization
• Integration of kinetic and genome-scale metabolic models
• Discovery of drug candidates against brain cancer
• Using mechanistic knowledge in sequence-to-expression models
• Risk-averse design of synthetic gene circuits