Machine learning unlocks secrets of antimicrobial resistance, identifying over 900 key genes

Researchers employed advanced techniques like gene annotation, pangenomics, and machine learning to identify over 900 genes responsible for antimicrobial resistance in 12 bacterial species, outperforming traditional identification methods. This breakthrough approach offers new insights into the genetic basis of resistance, potentially guiding the development of more effective antibiotics