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 (MICs) from a photograph of the 96-well plate after two weeks incubation has been published in the Computational and Structural Biology Journal. You can get the model, which is called TMAS, on GitHub here and there is a longer description here. 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 computing tuberculosis
computing How to setup a Gramble 14th April 2016 This is a Gramble, which of course is short for a GROMACS Bramble, or, 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 Postdoctoral position advertised 17th May 202117th May 2021 Through the CompBioMed2 EU Centre of Excellence project I have funding to appoint a postdoctoral… 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
New publication: fast human read decontamination for SARS-CoV-2 16th May 202216th May 2022 ReadItAndKeep is a new human-read decontamination algorithm that works by mapping the reads in a… 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