UR1404 Applied Mathematics and Informatics from Genome to the Environment (MaIAGE)

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The MaIAGE laboratory gathers mathematicians, computer scientists, bioinformaticians and biologists to tackle problems from biology, agronomy and ecology. Our research concerns processes at various levels, ranging from molecular, cellular or multicellular levels to organisms, populations, and entire ecosystems.

MaIAGE develops new methods in mathematics, statistics, and computer science, which may be generic or driven by specific biological problems. A particular focus is on developing software, databases, ontologies and web services to be used by biologists in analyzing data or mining the scientific literature.

A main expertise of the laboratory is in statistical inference and dynamic modelling, along with bioinformatics, automatic control and algorithmics. Research and engineering activities are based on strong involvement in the target disciplines: ecology, environment, molecular biology and systems biology.

Highlights of the MaIAGE unit

Modélisation de dynamiques démographiques et épidémiologiques sur un graphe de grande taille avec une application sur les transmissions de maladies infectieuses chez les bovins.
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BiPON: une preuve de concept sur la manière de combiner formellement la biologie systémique et les bio-ontologies.
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10 ans d’études de la diversité génétique de la bactérie pathogène des poissons Flavobacterium psychrophilum : une collaboration de longue durée entre mathématiciens et biologistes.
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Florilège: un service d'agrégation de connaissance en microbiologie des aliments.
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Latest publications

Laurent Naudon, Adrien François, Mahendra Mariadassou, Magali Monnoye, Catherine Philippe, Aurélia Bruneau, Marie Dussauze, Olivier Rué, Sylvie Rabot, Nicolas Meunier (2020) First step of odorant detection in the olfactory epithelium and olfactory preferences differ according to the microbiota profile in mice. Behavioural Brain Research, , DOI

de Lira, A. D.; Kothe, C. I.; Rue, O.; Midoux, C.; Mann, M. B.; et al. (2020) Assessing the quality of fresh Whitemouth croaker (Micropogonias furnieri) meat based on micro-organism and histamine analysis using NGS, qPCR and HPLC-DAD.. Journal of Applied Microbiology, , DOI

Gibrat, J.-F. (2019) On the use of algebraic topology concepts to check the consistency of genome assembly. Biophysics and Physicobiology, Volume : 16, DOI

Lubitz, T.; Liebermeister, W. (2019) Parameter balancing: consistent parameter sets for kinetic metabolic models. BIOINFORMATICS, , DOI

Vila Nova, M., Durimel, K., La, K., Felten, A., Bessières, P., Mistou, M.-Y., Mariadassou, M., Radomski, N. (2019) Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale. BMC GENOMICS, , DOI