Next generation sequencing technology allows studying microbial communities "in action": more and more data sets are being published that monitor the dynamics of hundreds of species over long time periods. We plan to take advantage of these novel data sets in order to model microbial communities. Currently, interactions networks are inferred from these data, but these do not describe the dynamics of microbial communities. The goal of our project is therefore to develop, parameterize and benchmark a dynamic microbial community model and then to apply this model to perturb microbial communities in silico. This framework will allow to study the consequences of different types of perturbations in a simulated community. Such simulation studies will increase our understanding of perturbed communities and thus may prove relevant in a clinical context, where perturbed microbial communities are known to play a major role in several diseases.
Promoters:Didier Gonze and Jan Danckaert