Research

My research and teaching activities concern the development and application of statistical and computational methods to address problems in life sciences and more particularly in (microbial) ecology involving omics data.

Statistical Methods in Molecular Biology

- Design and analysis of high-throughput gene expression experiments based on next-generation sequencing: mRNA-Seq for transcriptome analysis.

Application in cheese metatranscriptome, sea urchin transcriptome

- Comparative Metagenomics based on next-generation sequencing data.

Statistical Methods in Microbial Ecology

- Design and analysis of amplicon-based metagenomic data

- Biclustering using Latent Block Model

Application to microbial ecology, plant-microbial communities interactions in the rhizosphere or soil microbial communities.

Current funded projects

ANR EcoNet

EcoNet (2019-2023): Advanced statistical modelling of ecological networks (leader: C. Matias)

ANR project NGB

(2018–2022): Next Generation Biomonitoring of change in ecosystems structure and function (leader: D. Bohan)