Predicting antimicrobial resistance using conserved genes.

Abstract excerpt

A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features derived from comprehensive sets of AMR genes or whole genome sequences and may not be suitable for use when genomes are incomplete. In this study, we explore the...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Algorithms
• Share to Anti-Bacterial Agents
• Share to Bacteria