Unlocking antimicrobial resistance with multiomics and machine learning.

Journal: Trends in microbiology
Published Date: May 26, 2025

Abstract

The global antimicrobial resistance (AMR) emergency is driven by complex and evolving molecular mechanisms. Cutting-edge machine learning methods and multiomics technologies can help to combat this crisis by predicting novel AMR biomarkers and outcomes with unprecedented precision and speed, offering critical insights into the molecular underpinnings of AMR.

Authors

  • Abhirupa Ghosh
    Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Charmie K Vang
    Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Evan P Brenner
    Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Janani Ravi
    Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA. Electronic address: janani.ravi@cuanschutz.edu.

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