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Predicting antimicrobial resistance

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Fowler Lab
Fowler Lab

Predicting antimicrobial resistance

Category: research

antimicrobial resistance

New paper: Validation of an optimized Oxford Nanopore sequencing workflow versus Illumina for mycobacteria from primary MGIT culture

Philip Fowler, 24th August 202624th August 2026

Most genetic sequencing of Mycobacteria, including Mycobacterium tuberculosis, has for historical reasons used short-read technology,…

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antimicrobial resistance

New preprint: using genetics to analyse ESBL infections in a neonatal ICU ward

Philip Fowler, 7th July 20267th July 2026

In this preprint, Melody Parker as part of her DPhil, has analysed a series of…

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New preprint: evaluating a laboratory workflow for sequencing Mycobacteria using long-read sequencing

Philip Fowler, 7th February 20269th April 2026

In this preprint, we describe and evaluate a laboratory workflow for sequencing Mycobacterial samples using…

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antimicrobial resistance

New paper: how well can we predict AMR in tuberculosis samples?

Philip Fowler, 16th December 202516th December 2025

This paper just published in Microbial Genomics examines how well our software tool, gnomonicus, predicts…

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antimicrobial resistance

New preprint: Predicting pyrazinamide resistance in M. tuberculosis using a graph convolutional network

Philip Fowler, 29th October 202530th October 2025

In previous work we’ve used “traditional” machine-learning approaches, like XGBoost, to learn and therefore predict…

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New paper: Evaluating 12 WGS analysis pipelines for MBTC

Philip Fowler, 21st October 202529th October 2025

Ruan Spies did a careful systematic analysis of the publicly-available pipelines that claimed to process…

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