Peter Belmann

The paper introduces a cloud-based metagenomics workflow with machine learning for resource allocation, demonstrating its efficiency on sewage samples.

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

CAMISIM simulates microbial communities and metagenomes with truth standards, enabling benchmarking of metagenomic analysis tools.

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.