what we do
Our team develops computational methods to study molecular processes in living cells. We use mathematics 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.
- AI and machine learning for cell factory design.
- Discovery of anti-senescence compounds with machine learning.
Media coverage The Times, Sky News, The Conversation, Deutsche Welle
- Bayesian optimization of biological circuits
- Deep learning models of protein expression
- Graph neural networks for predicting gene essentiality
- Protein deimmunization with large language models
|Oct 19, 2023||Diego will be speaking at PEGS Europe in Lisbon on deep learning for optimization of protein expression systems.|
|Oct 2, 2023||Many congrats to Charlotte for her review paper on AI for pathway engineering, just published in the Biochemical Society Transactions.|
|Sep 5, 2023||A warm welcome to Lucas Guirardel, who joins us from EPFL for his PhD in our lab!|
|Aug 27, 2023||This year we will host 4 undergrad students for their final year project. A warm welcome to Laura, Andreas, Sam and Nicholas!|
|Aug 25, 2023||Ramin’s paper using geometric deep learning for predicting gene essentiality is now available in preprint; congrats! and all the best for the future back in Norway.|
|Jul 11, 2023||Hans’ paper on large language models for protein deimmunization is available as preprint, congrats!|
|Jun 22, 2023||Diego will be speaking at the Protein and Antibody Engineering Summit on our work on deep learning for sequence-to-expression prediction.|
|Jun 19, 2023||Charlotte’s paper on machine learning for gene circuit design has been published in ACS Synthetic Biology, many congrats to Charlotte for her first research paper!|
|Jun 16, 2023||Vanessa’s paper on AI for discovery of senolytics appeared in Nature Communications and has been picked up by the press (Sky News, The Times).|
|May 20, 2023||Aryo, Achille and Michal have put out a new preprint on the Vaxformer, a generative protein language model that can help the design of vaccines.|