Data analysis, bioinformatics and mathematical modeling
The surge of omics data in microbiology constitutes a huge challenge while opening up tremendous opportunities to study microbial physiology and microbial communities in unprecedented detail.
In our group, we use state-of-the art bioinformatics tools to process and analyse different types of omics data, including whole-genome sequencing, metagenomics, metatranscriptomics, and metabolomics. We also develop new tools, for example for strain-level analysis in metagenomics data to study the spread of antimicrobial resistance genes. Ultimately, we use mathematical modeling, such as genome-scale metabolic modeling, as well as data analysis methods, such as machine learning, to leverage these data toward our research goals. Our aims are to develop new metabolically engineered microorganisms and study the evolution of bacteria and their interactions in simple and complex microbial communities.
Keywords: Systems biology, Genome-scale metabolic modeling, Metagenomics .
Affiliated researchers
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Contact
Ghjuvan Grimaud, Associate Senior Lecturer