LECOMTE, Maxime; LABARTHE, Simon; SHERMAN, David James; FALENTIN, Hélène; FRIOUX, Clémence

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Licence d’utilisation du document

LECOMTE, Maxime
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
Science et Technologie du Lait et de l'Oeuf [STLO]

LABARTHE, Simon
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
Biodiversité, Gènes & Communautés [BioGeCo]

SHERMAN, David James
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]

Langue

Communication dans un congrès

Ce document a été publié dans

Workshop SymBioDiversity, 2022-05-16, Santiago.

Résumé en anglais

The massive development and use of multi omics data permits a better understanding of complex microbial ecosystems at the metabolic level. However, this data and their integration varies depending on the size and characteristics of the considered ecosystems. In this talk, I will discuss of two different approaches applied respectively to a controlled microbial community and natural communities in order to reveal putative bacterium-bacterium interactions. I will first describe how numerical optimisation of metabolic models constrained by genomics and metatranscriptomics data can accurately describe a cheese starter community. I will then detail a discrete method based on only genomic data aiming to characterize the competition and cooperation potentials in natural communities.< Réduire

Origine

Importé de hal

Unités de recherche

BioGeCo (Biodiversité Gènes & Communautés) - UMR 1202