Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.

family, we elucidated the evolutionary emergence and development of AR mechanisms. Leveraging population-wide machine learning (ML)-based genomic analysis, we transformed substantial non-random allelic variations into discernible clusters of elements, enabling precise prediction of MLS phenotypes from non-coding regions. These findings offer deeper insight into AR evolution and demonstrate the potential of harnessing non-coding genomic allele data for accurately predicting AR phenotypes.