ArticleNAR genomics and bioinformatics2025
Genomic data representations for horizontal gene transfer detection.
Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Evaluating ensemble learning approaches for horizontal gene transfer detection.Scientific reports · 2026Article
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4 authors.
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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. We demonstrate that ML performance is highly dependent on the genomic data representation. The RCKmer-based representation (
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