Our research interest is Quantitative Microbiology. An approach of microbiological problems using an interdiciplinary approach, combining modelling, statistics,informatics we try to look at the microbial world from a new perspective. We develop new tools and apply them to our domains of interest in medical and industrial microbiology : microbial ecology, optimization of diagnostics strategies, and anti-bacterial agents.
Bioinformatics and bacterial identification
BIBI is a webtool dedicated to the identification of bacteria based on a phylogenetic approach. It consists both of a "clean" database BIBIDB and of the bioinformatics tools for the automatisation of the identification process. BIBI privilegiates phylogenetic relationships, today basis of taxonomy of bacteria, to the use of similarities in the indenfication process. Adaptation of general sequences databases to identification purposes is a related topic. Aside this, our team is involved in the development of multilocus sequences databases devoted to identification of Actinomycetales, especially Corynebacterineae (including Mycobacteriaceae and Nocardiaceae) and in the improvement of phylogeny and taxonomy using a multilocus approach.
Probabilities in microbiology
optimisation of sampling strategies for diagnostics, predictive values of microbial analyses
Detection of bacterial population fluctuations, of anormal and epidemic events
theme the more strongly linked to our medical activities. We are interested in stochastic models of epidemics and detection of rare unexpected related events or outbreaks (for instance unexpected antibiotics resistance) in a continuous flow of information generated by laboratories. We have also developped a webtool improving identification of subtypes of Mycobacterium tuberculosis for epidemiologists
Modelling of the dynamics of bacterial populations, essentially using differential equation systems
Our aim is to describe growth and death processes in bacterial populations, interactions with the environment and impact of anti-bacterial compounds using modelling. We have developped Dynatica for the biologists simulations tasks. Now a net tool is online and somewhat similar : DynW RFIT is a webtool that provide an easy way to estimate the parameters of population dynamics models.More on the team webpage (in French) ...