Article

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes

2024-02-01

Abstract excerpt

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno, and Aytan-Aktug), an ML b...

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Literature Corpus work: ce6ad742-8e20-5a70-a418-95367330ed7d
DOI: 10.1101/2024.01.31.578169

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