New paper: predicting pyrazinamide resistance Philip Fowler, 20th March 202420th March 2024 This paper has finally been published and you can find it here. It had a slightly tortuous journey from original preprint to updated preprint and now publication. In brief, we use a range of structural, chemical and evolutional features to learn which missense mutations in PncA (encoded by pncA) are associated with resistance to pyrazinamide, one of the four first-line antibiotics used to treat tuberculosis. This research output is designed to be reproducible; you can retrain all machine learning models and replot (nearly) all the figures in the paper using this GitHub repository. Share this:TwitterBlueskyEmailLinkedInMastodon Related antimicrobial resistance clinical microbiology publication research tuberculosis
antimicrobial resistance New paper: Quantitative drug susceptibility testing for M. tuberculosis using unassembled sequencing data and machine learning 14th August 202414th August 2024 This is the last paper from the initial set of CRyPTIC publications following the project’s… Share this:TwitterBlueskyEmailLinkedInMastodon Read More
antimicrobial resistance GPAS 17th May 202113th October 2021 I’ve been working on this for the last few months and very happy that we… Share this:TwitterBlueskyEmailLinkedInMastodon Read More
New preprint: Including minor alleles improves fluoroquinolone resistance prediction 10th November 202217th November 2022 Fluoroquinolones are used to treat both normal and drug resistant tuberculosis and therefore being able… Share this:TwitterBlueskyEmailLinkedInMastodon Read More