We follow two main lines of research, namely the study of
- (Re-)programming in discrete concurrent models. Cellular regulatory networks exhibit highly complex concurrent behaviours that is influenced by a high number of perturbations such as mutations. We are in particular investigating discrete models, both in the form of boolean networks and of Petri nets, to harness this complexity, and to obtain viable methods for two interconnected and central challenges:
- find attractors, i.e. long-run stable states or sets of states, that indicate possible phenotypes of the organism under study, and
- determine reprogramming strategies that apply perturbations in such a way as to steer the cellâs long-run behaviour into some desired phenotype, or away from an undesired one.
- Distributed Algorithms in wild or synthetic biological systems. We also work, on the multi-cell level, with a distributed algorithms' view on microbiological systems, both with the goal to model and analyze existing microbiological systems as distributed systems, and to design and implement distributed algorithms in synthesized microbiological systems. Major long-term goals are drug production and medical treatment via synthesized bacterial colonies.
New explorations are also under way in
- Modeling of metabolic pathways
- Causal analysis of Ecosystems
