Antimicrobial resistance (AMR) remains one of the most challenging phenomena of modern
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …

Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It
is very important to understand and apply effective strategies to counter the impact of AMR …

The emergence of microbial antibiotic resistance is a global health threat. In clinical settings,
the key to controlling spread of resistant strains is accurate and rapid detection. As …

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for
routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve …

The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-
genome sequences to be generated at an unprecedented pace. This wealth of information …

Anthropogenic environments such as those created by intensive farming of livestock, have
been proposed to provide ideal selection pressure for the emergence of antimicrobial …

Microbial genome-wide association studies (mGWAS) are a new and exciting research field
that is adapting human GWAS methods to understand how variations in microbial genomes …

Sharing of genetic elements among different pathogens and commensals inhabiting same
hosts and environments has significant implications for antimicrobial resistance (AMR) …

Pangenomes are replacing single reference genomes as the definitive representation of
DNA sequence within a species or clade. Pangenome analysis predominantly leverages …

Agricultural productivity is highly influenced by its associated microbial community. With
advancements in omics technology, metagenomics is known to play a vital role in microbial …