My team is at the interface between statistical physics and systems biology, and focuses on interaction networks (catalytic or regulatory). A major challenge in this field is to go beyond a mere description of connectivity, and understand the relations between structure and function.
For this we use tools from biochemistry and genetics, to design artificial networks or perturb existing ones. Microfluidic technology plays a central role in our activity, as it allows us to control conditions and analyze the response of the system at a high-throughput. We also put a strong emphasis on quantitative analysis of the resulting data, in relation with theoretical models.
We approach the problem of network organization from several complementary angles:
In which conditions can in vitro molecular systems build up complexity? We study artificial networks made of nucleic acids, and develop tools to measure their compositional trajectories. We ask questions about the flow of information and the feedback between structure and function.
How to control the state of cells? We develop strategies to impose multiple genetic or drug perturbations, and measure the resulting phenotype, for example by RNA-seq. Our aim is to understand multi-factorial interactions in terms of network wiring.
How do networks evolve? We ask this question from the perspective of the biological function performed by the networks.