Patrick Munk

PanRes is a curated database of antimicrobial resistance genes that uses structural clustering and HMMs to improve detection of resistance determinants in metagenomes.

The paper uses single-cell metagenomics to link plasmid-derived antimicrobial resistance to host bacteria in pigs, identifying resistance-associated features in longitudinal gut microbiome data.

This paper introduces MGCalibrator, a tool for spike-in free absolute abundance estimation in metagenomics, validated against qPCR and applied to track antibiotic resistance genes in wastewater.

This study uses sewage metagenomics to distinguish seasonal, human-derived, and environmental microbial communities, offering potential for improved AMR surveillance.

The paper identifies co-occurring antimicrobial resistance genes (ARGs) in metagenomic datasets to highlight potential co-selection in resistomes across different environments.

The paper curates a large metagenomic dataset to study the global distribution and dynamics of antimicrobial resistance genes.

This paper develops a random forest model to predict plasmid hosts, achieving 0.662 and 0.867 Matthews correlation coefficients at species and order levels, respectively.