Fernando Meyer

This study benchmarks ML and rule-based methods for predicting antimicrobial resistance from microbial genomes, finding significant variation in performance across species and antibiotics.

The paper evaluates metagenomic software tools using realistic datasets, highlighting improvements in assembly and taxon profiling while identifying remaining challenges in virus/archaea detection and reproducibility.

This tutorial explains how to use the CAMI benchmarking toolkit to evaluate metagenomics software performance using standardized datasets and metrics.

OPAL is a software package for benchmarking taxonomic metagenome profilers using performance metrics and visualizations, demonstrating its application on CAMI challenge datasets.

AMBER evaluates genome binning tools using benchmark datasets and provides performance metrics and visualizations.

The paper benchmarks computational metagenomics software using complex datasets, showing strengths and limitations in assembly, binning, and taxonomic profiling.