Theoretical physics of active and biological materials
We investigate the physical principles that organize living matter—from the interior of cells to the three-dimensional architecture of the genome—to understand how biological functions emerge.
Our team focuses on the physics of active and biological matter and genome physics. We aim to uncover how physical laws—such as phase transitions, non-equilibrium dynamics, and collective interactions—shape the spatial and temporal organization of living systems.
Our work addresses:
- Large-scale intracellular organization
- The 3D architecture of the eukaryotic genome and its link to epigenetics (gene repression, activation, and expression)
- Segregation and positioning of the bacterial genome through active, non-equilibrium mechanisms
- Dynamics and distribution of bioenergetic complexes within bacterial membranes
- Modeling immune systems as complex systems described in terms of cell population dynamics
We combine theoretical modeling, numerical simulations, and quantitative analysis of data from cutting-edge experimental techniques (e.g., chromosomal contact mapping and multipoint imaging) to connect structure, dynamics, and function in the systems we study.
Sub-Themes :
- Active Matter & Intracellular Organization: Laws of self-organization and non-equilibrium dynamics in biological matter
- Genome Physics: Statistical physics and polymer-based models linking genome architecture, epigenetics, and gene expression mechanisms
- Bacterial Genome: Active mechanisms of genome segregation and positioning enabling cell division
- Nanobiophysics of Membranes: Distribution and dynamics of protein complexes involved in transmembrane proton-motive force and bacterial bioenergetics
- Immunological Systems: Population and network models to shed light on disease evolution and dynamics (applications to autoimmune diseases such as rheumatoid arthritis)
Methods :
Modeling (stochastic equations, variational methods, systems of differential equations), simulations (Monte Carlo, molecular/Brownian dynamics), and quantitative analysis of experimental data.
