Arnaud Belcour

This study characterizes the bacterial, archaeal, and fungal communities of Ascophyllum nodosum across multiple environmental factors, revealing dynamic bacterial interactions and stable fungal associations.

The paper develops a pipeline called Tabigecy to predict metabolic functions from metabarcoding data and integrate them into biogeochemical cycle representations.

The paper develops a computational pipeline to classify gut microbiome states using functional annotations, showing comparable performance to microbial profiles and identifying reliable discriminant variables.

This study analyzes 60 brown algal genomes to identify genomic innovations and evolutionary patterns that enabled their adaptation to coastal ecosystems.

AuCoMe reduces technical biases in metabolic network comparisons across diverse genomes and identifies shared and divergent metabolic traits.

EsMeCaTa estimates consensus proteomes and metabolic functions from taxonomic data, validated on environmental datasets and applied to a methanogenic reactor study.

Metage2Metabo identifies keystone species in large microbiotas by analyzing metabolic networks and complementarity.

The paper infers new biochemical reactions and metabolite structures in Chondrus crispus, revealing metabolic pathway drift despite conserved phenotypes.

The paper describes the genome of a new Plasmodiophora brassicae isolate, identifies its mitochondrial sequence, and designs a pathway genome database for metabolic pathway analysis.