Samuel Chaffron

The paper shows that codon usage bias in metabolism-related genes reflects microbial adaptation to temperature and nutrient regimes in ocean communities.

The paper identifies global hotspots of plankton-based ecosystem services by integrating satellite data with metagenomic functions and machine learning.

The paper examines how marine reserves affect seawater microbial communities in the Great Barrier Reef, finding distinct microbiomes between protected and fished areas.

This study investigates how nutrient stress shapes interactions in a synthetic microbial community with Prymnesium parvum, showing B12 limitation drives mutualism and metabolic reprogramming.

This study compares microbial community dynamics in equatorial and temperate marine time-series, finding distinct ecological processes shaping their assembly and stability.

The paper investigates the relationship between co-occurrence and horizontal gene transfer (HGT) in marine bacteria, finding a significant association independent of phylogeny.

MIMEco predicts pairwise microbial interactions using multi-objective metabolic modeling without requiring abundance data, validated by replicating experimental results with Escherichia coli.

This study generates absolute estimates of plankton cell concentrations and carbon biomass using environmental genomic data, revealing ecological associations and quantitative biogeographies of photosynthetic lineages.

The paper introduces MicrobioRel, two datasets for microbiome relation extraction, and evaluates models for this task, finding PubMedBERT to be effective.

This study analyzes diatom diversity and abundance in the global ocean using Tara Oceans data, identifying key environmental drivers and community patterns.

This paper models host-microbiota interactions using in silico metabolic models and multi-objective optimization to predict microbial interaction types and quantify their effects on epithelial cell maintenance.

MAGNETO automates MAGs reconstruction by integrating co-assembly and binning strategies, improving genome recovery from metagenomic data.

MiBiOmics provides a web-based tool for multi-omics data integration and analysis, enabling visualization, ordination, and network inference to identify biomarkers.