Coordinator: Gilles Charvin (BDCS)
Managing Committee: Annick Dejaegere (BSI), Nacho Molina (GFC), Juliette Godin (MTN)
13 Participating teams:
- BSI: Dejaegere, Kieffer, Weixelbaumer
- GFC: Li, Molina, Sexton
- BDCS: Riveline, Vermot, Charvin, Soutoglou, Dollé
- MTN: Godin, Laporte
- Technological platforms involved: IT, Bioinformatics, Imaging, Sequencing, Mass spec, High-throughput screening
Biology is progressively turning into a quantitative discipline. At all scales, from the atom to the whole organism, the analysis of biologcal processes and functions requires more and more complex experimental setups and analysis tools. These emerging methodologies increasingly rely on the input from other disciplines, such as computer sciences, physics, chemistry and mathematics.
The IGBMC teams have diverse research interests, yet they share a lot of common methodology in quantitative biology. In this context, we would like to launch a new transversal program with a methodological perspective to federate the teams around emerging trends in quantitative Biology. This strategic axis – which is one of the thematic directions of the Labex - has already been defined as a priority in leading research institutes in Biology (e.g. Quantitative Biology department at the FMI, Basel).
The goal of this program is three-fold, as described in detail in the next section. First, it will allow us to make an audit of existing expertise in these fields at the IGBMC, and attempt to strengthen the links between teams that share common methodology. Second, it will work to expand the expertise in specific quantitative methods by inviting recognized external experts to give lectures, by organizing small workshops and by training students, postdocs and researchers. Last, it will attempt to make the IGBMC an important node in quantitative biology and project it towards the local, regional and European scientific landscape.
The program welcomes all teams that either already have an expertise or wish to acquire one in the following fields:
1) Experimental methods
Single cell analyses, OMICS, mass-spectrometry, structural methods, quantitative imaging, microfabrication and other biophysical methods
2) Computational methods and numerical simulations
Cellular and tissue dynamics, molecular dynamics, stochastic simulations, gene networks modelling
3) Statistics and mathematical models
Statistical physics, stochastic processes, theory of dynamical systems, statistical analyses, network theory
4) Information processing
NMR data analysis, mass spectrometry data analysis, image processing techniques, DNA sequence analysis, management of big data