Overview of our Research

Mitochondria in context of the cellular host. We are fascinated by mitochondria and their metabolism and want to understand how they are able to adapt to their cellular host environment. We study mitochondrial diversity using several computational methods, such as data integration, visual data mining, network biology, metabolic modelling and deep learning. 

We are especially interested in mitochondria and how these essential organelles, the powerhouses of our cells, are able to adapt to their cellular host environment. In order to address this question, we develop computational tools to analyse (multi-)omics data from a mitochondrial perspective, such as mitoXplorer. 

To look more closely at the metabolic changes that go hand-in-hand with mitochondrial maturation or adaptation, we use metabolic modelling, and our recently published mitoMammal metabolic model. 

What defines a replication origin in eukaryotes? We want to understand how eukaryotic cells choose their origin of replication to duplicate their genomes. In most eukaryotic cells, there is no consensus sequence that defines the origin of replication. Instead, there are spatial, structural and molecular cues that must initiate replication along the chromosome. We use several approaches to study this question, ranging from data modelling, deep learning to molecular dynamics simulations.

Biological networks and knowledge graphs. We are intrigued by the power of complex biological networks to learn about biological systems and to interpret complex biological data. We use complex networks and knowledge graphs to integrate data from a multitude of sources and applied to mitochondrial biology and rare diseases.

Evolution of organisms, tissues and molecules. We are interested in evolution and how proteins and organisms adapt to their environment, for instance by evolving novel traits or by readjusting their metabolism. We study this phenomenon in close collaboration with experimental teams and apply methods such as classical sequence analysis and phylogenetics, single-cell based data analysis, to comparative metabolic modelling.