Andrew G. McArthur

The paper develops a rules-based classifier to predict ciprofloxacin resistance in Klebsiella pneumoniae from genotype data and demonstrates its global distribution association with quinolone consumption.

The paper uses BioBERT to extract and analyze antimicrobial resistance gene transmission patterns from 204,094 publications, visualizing ARG spread across environments, hosts, and agriculture.

The paper shows how phage tail fibre structure determines their ability to recognize diverse type IV pils despite receptor variation.

The paper analyzes antimicrobial resistance gene mobility across 8000 bacterial species, finding that certain resistance mechanisms are more associated with mobile elements than others.

CARD k-mers classifies antimicrobial resistance genes in metagenomic data by predicting taxonomy and genomic context, outperforming existing tools in accuracy and speed.

CARPDM enables cost-effective antibiotic resistome profiling in metagenomic samples through targeted enrichment and in-house probe synthesis.

This paper reclassifies SHV β-lactamase alleles in K. pneumoniae genomes based on mutations, improving genotype-phenotype understanding and updating the Kleborate tool.

The paper develops an open-source, cloud-based tool for detecting pathogens and antimicrobial resistance genes in metagenomic and whole-genome sequencing data, demonstrating its application across clinical and environmental studies.

hAMRonization standardizes AMR gene detection outputs from multiple tools into a unified format for easier analysis and integration.

This study profiles resistance determinants, virulence factors, and mobile genetic elements in 1273 Enterococcus faecium genomes from UK and Canada, showing habitat-associated gene and MGE patterns and a workflow for AMR surveillance.

This study evaluates the performance of short-read sequencing for detecting antimicrobial resistance genes in genomes and metagenomes, finding that assembly-based methods require 15X coverage for reliable detection.

A decentralized open-source web platform lets public health labs run outbreak sequencing pipelines on local compute, keeping data under their own governance while still exchanging results between instances.