AMyGDA now available from GitHub Philip Fowler, 27th January 202027th January 2020 AMyGDA is a python module that analyses photographs of 96-well plates and, by examining each well for bacterial growth, is able to read a series of minimum inhibitory concentrations for the antibiotics present on a plate. Previously it was only available to download from this website (due to licensing) if you gave your email address which was inconvenient and also meant the public version often lagged the current stable release. Now it is available directly from GitHub! Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Related antimicrobial resistance clinical microbiology computing tuberculosis
computing GROMACS2018 on NVIDIA DGX-1s 27th September 201929th October 2019 HECBioSim advertised for proposals to use JADE, the new Tier-2 UK GPU high performance computer… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More
antimicrobial resistance New paper: What can subpopulations tell us about rifampicin resistance? 14th October 202514th October 2025 Last Thursday this work which we’d previously preprinted looking at looking at rifampicin-resistant subpopulations in… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More
antimicrobial resistance New preprint: compensatory mutations are associated with increased growth in resistant samples of M. tuberculosis. 22nd June 20238th December 2023 In this preprint, Viki Brunner shows how, using the large CRyPTIC dataset, she can recapitulate… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More