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

• New preprint: automatically building a better bedaquiline catalogue31st January 2025
• SARS-CoV-2 pipeline live on EIT Pathogena28th January 2025
• Updated preprint: A validated cloud-based genomic platform for co-ordinated, expedient global analysis of SARS-CoV-2 genomic epidemiology23rd January 2025
• Dylan Adlard is an SSI Fellow!15th January 2025
• New preprint: comparing different genetics analysis pipelines for tuberculosis13th January 2025
• New preprint: validating antibiotic resistance prediction in our Myco pipeline9th November 2024
• New paper: Infection Inspection10th September 2024
• New preprint: predicting rifampicin resistance16th August 2024
• New paper: Quantitative drug susceptibility testing for M. tuberculosis using unassembled sequencing data and machine learning14th August 2024
• Updating the Grammar for Antimicrobial Resistance Catalogues18th July 2024
• Dx4LMICs conference3rd July 2024
• FowlerLab at ESM 20241st July 2024
• Kafka and tuberculosis21st June 2024
• New preprint: processing 3.9 million SARS-CoV-2 samples to make a consistent phylogenetic tree7th May 2024
• New paper: predicting pyrazinamide resistance20th March 2024

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