what we do
Our team develops computational methods to study molecular networks 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 mathematical 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.
You can read more about our work in this piece.
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 co-located at the School of Informatics and the School of Biological Sciences of the University of Edinburgh, in one of the most vibrant and stimulating European capitals. We are members of SynthSys, the Edinburgh Centre for Synthetic and Systems Biology.
- Opportunities at the interface of network science and metabolic modelling, 2021.
- Prediction of cellular burden with host-circuit models, 2021
- Genotype-phenotype map of an RNA-ligand complex, 2020
- Computation of single-cell metabolite distributions using mixture models, 2020
- Stochastic model of gene expression with polymerase recruitment and pause release, 2020
|12 Jan 2021||Preprint on machine learning for genotype-mapping of RNA broccoli. Great collaboration with the Kudla lab!|
|5 Jan 2021||Three new papers just published in a variety of topics, links here, here and here|
|1 Oct 2020||Welcome! Two Honours students have joined our team, a warm welcome to Lilli and Simiao.|
|15 Sep 2020||Welcome! Three PhD students have joined our team, a warm welcome to Zuzanna, Ricardo and Michael.|
|1 Aug 2020||Diego has been promoted to Reader in Computational Biology.|