New paper: predicting pyrazinamide using a graph convolutional network Philip Fowler, 3rd March 202612th March 2026 This paper is the start of us, as a group, using deep learning methods to predict antimicrobial resistance whilst taking into structural and chemical features. You can read a more detailed description in an earlier post and notably it is our first paper in a special issue for a while. Dylan Dissanayake did the research and was helped by Viki Brunner and Dylan Adlard, along with Joe Morrone from IBM Research. Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Related Uncategorised
Uncategorised Congratulations Dr Brunner! 10th December 202522nd January 2026 Viki successfully defended her DPhil thesis on Tuesday 9 December 2025 – well done! I… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More
New preprint: Rapid decontamination of SARS-CoV-2 genetic reads 24th January 202224th January 2022 This preprint describes some software, ReadItAndKeep, that rapidly removes host (i.e. human) genetic information from… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More
Uncategorised Fitness compensation in M. tuberculosis: A game of genetic chess 11th March 202411th March 2024 It was a pleasure to write this short blog post for the Microbiology Society, talking… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More