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article · JAC-Antimicrobial Resistance

Prediction of pyrazinamide resistance in <i>Mycobacterium tuberculosis</i> using structure-based machine-learning approaches

202420 citationsOpen accessStellenbosch University

Abstract

This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.

Research topics

  • Tuberculosis Research and Epidemiology
  • vaccines and immunoinformatics approaches
  • Computational Drug Discovery Methods

Sustainable Development Goals

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DOI: 10.1093/jacamr/dlae037

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