Data-driven modeling of cell metabolic response to oxidative stress
Context and challenges
- Team’s long-standing interest in studying stress-response, metabolic and regulatory processes
- Metabolic regulation plays a central role in cancer cell adaptation to oxidative stress
- Requirement for elaborate and original modeling approaches to gain insights into complex biological processes
- Methodological challenges at the crossroad of biochemical network dynamics and data science.
1) An international reference in topological photonics
2) Ultrafast observation and control of particle accelerators
3) Soliton gases in Optics and in Hydrodynamics (SOGOOD ANR Project)
4) From anatomy of chaos to machine learning-assisted extreme event forecasting
5) New states of light : from quantum to nonlinear regime
7) Novel opto-fluidic drug delivery system for efficient cellular transfection