New publication: Predicting resistance is (not) futile Philip Fowler, 21st August 201921st August 2019 Our “First Reactions” article has been published in ACS Central Science. We discuss the paper, Predicting Kinase Inhibitor Resistance: Physics-Based and Data-Driven Approaches, by Matteo Aldeghi, Vytautas Gapsys and Bert de Groot, which is in the same issue of the journal. Aldeghi et al. apply a series of methods to try and predict the effect of individual mutations on how well tyrosine kinase inhibitors bind to the Abl kinase. These methods include not only alchemical free energy methods but also machine learning. You can read it 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 molecular dynamics publication
antimicrobial resistance New preprint: Deciphering bedaquiline and clofazimine resistance in tuberculosis 22nd March 202122nd March 2021 In this preprint we examine 14,151 clinical isolates drawn from the CRyPTIC dataset. Each isolate… 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: Predicting pyrazinamide resistance by machine learning 29th April 201929th April 2019 Usually, the protein that an antibiotic binds is essential for bacterial survival, which is how… 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 AMyGDA now available from GitHub 27th January 202027th January 2020 AMyGDA is a python module that analyses photographs of 96-well plates and, by examining each… 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