Our group is interested in how biological systems, such as organisms, tissues, organelles cells or molecular systems, adapt to changing environments, and during development.

Biological systems, such as organisms, organs, cells, organelles or molecular systems, are highly dynamic and change for instance over time during development, during ageing, as well as to cues coming from their environment.

To give one example, mitochondria, which are important bioenergetic and metabolic organelles in eukaryotic cells, mature during development, changing their structure, their content and their metabolism. They also adapt to the cell type they are hosted in and change in disease, adapting their structure, content and metabolic function to the cellular needs in response to multiple molecular, chemical, metabolic, bioenergetic and mechanical cues. What are the underlying mechanisms and signals that drive mitochondrial adaptation?

Such metabolic adaptations to the environment can also be seen in bacteria. In these simpler organisms, we can even study in real time the evolutionary cues that lead to the adaptation to their environment, and to other interacting species, for instance in symbiotic, competitive or predatory relationships.

To ensure integrity of the genome during DNA replication, cells use a complex mechanism of origin of replication selection in eukaryotes, which involves a set of highly complex protein machines together with contextual structural cues of the DNA. The selection of replication origin, while not guided by sequence-specificity in most opisthokonta, is not random. The properties of replication origins can change during cell differentiation and also during disease. What are the underlying mechanisms of replication origin selection?

We address these questions using a set of computational, mathematical, and biophysical methods, which include visual data mining, metabolic modelling, network biology with complex networks and knowledge graphs, evolutionary analysis, as well as cellular automata and biophysical modelling.