antimicrobial resistance New preprint: Predicting pyrazinamide resistance in M. tuberculosis using a graph convolutional network Philip Fowler, 29th October 202529th October 2025 In previous work we’ve used “traditional” machine-learning approaches, like XGBoost, to learn and therefore predict… Continue Reading
New paper: Evaluating 12 WGS analysis pipelines for MBTC Philip Fowler, 21st October 202529th October 2025 Ruan Spies did a careful systematic analysis of the publicly-available pipelines that claimed to process… Continue Reading
antimicrobial resistance New preprint: rapidly and reproducibly building resistant catalogues for M. tuberculosis Philip Fowler, 3rd October 20253rd October 2025 The CRyPTIC project carried out many exciting research projects but it never quite got around… Continue Reading
antimicrobial resistance New paper: predicting rifampicin resistance via free energy simulation Philip Fowler, 23rd September 20253rd October 2025 This work was carried out by Xibei Zhang, who is doing her PhD with Peter… Continue Reading
antimicrobial resistance New paper: automatically and reproducibly building a catalogue bedaquline resistance-associated variants Philip Fowler, 18th June 20251st July 2025 Dylan Adlard‘s paper describing how we can rapidly automatically build catalogues of bedaquiline resistance-associated variants… Continue Reading
antimicrobial resistance New paper: a deep learning model that reads MICs from images of 96 well plates Philip Fowler, 26th May 20251st July 2025 Our paper describing how a convolutional neural network model can determine the minimum inhibitory concentrations… Continue Reading