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Predicting antibiotic resistance de novo

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Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

Category: computing

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…

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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…

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antimicrobial resistance

New preprint: predicting rifampicin resistance

Philip Fowler, 16th August 202416th August 2024

In this preprint we train a series of machine learning models on protein mutations found…

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antimicrobial resistance

Updating the Grammar for Antimicrobial Resistance Catalogues

Philip Fowler, 18th July 202418th July 2024

This blog updates an old (and now out of date) post describing the grammar we’ve…

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clinical microbiology

New preprint: processing SARS-CoV-2 genetics in the cloud

Philip Fowler, 31st January 202431st January 2024

In this preprint, we describe how in July 2022 for two weeks seven sites in…

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New publication: Predicting antibiotic resistance in complex protein targets using alchemical free energy methods

Philip Fowler, 26th August 202224th October 2022

In this paper, Alice Brankin calculates how different mutations in the DNA gyrase affect the…

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