Genomic data representations for horizontal gene transfer detection.

ABSTRACT: Horizontal gene transfer (HGT) accelerates the spread of antimicrobial resistance (AMR) via mobile genetic elements allowing pathogens to acquire resistance genes across species. This process drives the evolution of multidrug-resistant "superbugs" in clinical settings. Detection of HGT is critical to mitigating AMR, but traditional methods based on sequence assembly or comparative genomics lack resolution for complex transfer events. While machine learning (ML) promises improved detection, several studies in other domains have demonstrated that data representations will strongly influence its performance. There is, however, no clear recommendation on the best data representation for HGT detection. Here, we evaluated 44 genomic data representations using five ML models across four data sets

SUBMITTER: Wijaya AJ 

PROVIDER: S-EPMC12693543 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature