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Fowler Lab

Predicting antibiotic resistance de novo

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Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

Welcome

The main aim of our research is to develop methods that can de novo predict the effect of protein mutations on the action of antibiotics.

Latest News

  • Congratulations Dr Adlard!7th March 2026
  • New paper: predicting pyrazinamide using a graph convolutional network3rd March 2026
  • New paper: Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny9th February 2026
  • New preprint: comparing long- and short-read sequencing of Mycobacteria7th February 2026
  • Gr-ADI consortium announced22nd January 2026
  • New paper: how well can we predict AMR in tuberculosis samples?16th December 2025
  • Congratulations Dr Brunner!10th December 2025
  • New preprint: Predicting pyrazinamide resistance in M. tuberculosis using a graph convolutional network29th October 2025
  • New paper: Evaluating 12 WGS analysis pipelines for MBTC21st October 2025
  • Dylan’s bedaquline paper one of the most read in Microbial Genomics in September!20th October 2025
  • New paper: What can subpopulations tell us about rifampicin resistance?14th October 2025
  • New preprint: rapidly and reproducibly building resistant catalogues for M. tuberculosis3rd October 2025
  • New paper: predicting rifampicin resistance via free energy simulation23rd September 2025
  • Third Dx4LMICs conference3rd July 2025
  • I’m hiring!26th June 2025
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