Biotechnologies, Image processing and signal processing for the quantitative analysis of biological processes



Steering committee

  • Florence BESSE (IBV) ;
  • Laure BLANC-FERAUD (I3S) ;
  • Eric DEBREUVE (I3S) ;
  • Grégoire MALANDAIN ;
  • Caroline MEDIONI (IBV) ;
  • Sébastien SCHAUB (IBV) ;
  • Gilles AUBERT (LJAD) ;
  • Caroline FONTA ;


The study of biological, physiological or pathophysiological phenomena benefits from the development of constantly evolving technologies (microscopy, tomography, mass spectrometry, electrophysiology etc.) to view and measure cellular and / or intracellular processes with increasing accuracy and at ever broader scales. The mass and complexity of data generated by broad-band type experiments, real or multimodal imaging time, however, make any manual analysis unfeasible.


Alongside the development of these new acquisition techniques, it is necessary to develop automated and quantitative methods of data analysis (analysis and image comparison and complex signals, statistics). Once extracted, this information is used to simulate the processes studied and propose new mathematical models which have the advantage of being calibrated and validated using real data obtained in vitro, ex vivo or even in vivo. The use of these models to understand the behaviour of complex biological processes can in turn generate new hypotheses to be tested experimentally.

Main topics

In this context, this axis aims to promote the development of methods for the quantitative analysis of biological signals and the integration of this data into predictive models. Our goal is to help with the emergences of synergies between the research fields concerned, namely biology, image analysis, computer science and applied mathematics.


By seeking a better understanding of biological phenomena, the research conducted may eventually lead to understanding the effects and causes of different diseases, identifying new therapeutic targets, or aid in the longitudinal diagnosis and monitoring of therapy.