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: looking at rifampicin-resistant subpopulations in clinical samples10th April 2025 New grant: Ox4TB17th March 2025 Can medical microbiology become a big data science? Lessons from CRyPTIC11th March 2025 New preprint: a deep learning model that can read 96-well broth micro dilution plates23rd February 2025 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 Tweets by _fowlerlab_ Share this:TwitterBlueskyEmailLinkedInMastodon