A pan-genome-based machine learning approach for predicting antimicrobial resistance activities of the Escherichia coli strains.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Antimicrobial resistance (AMR) is becoming a huge problem in both developed and developing countries, and identifying strains resistant or susceptible to certain antibiotics is essential in fighting against antibiotic-resistant pathogens. Whole-genome sequences have been collected for different microbial strains in order to identify crucial characteristics that allow certain strains to become resistant to antibiotics; however, a global inspection of the gene content responsible for AMR activities remains to be done.

Authors

  • Hsuan-Lin Her
    School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
  • Yu-Wei Wu
    Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.