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Predicting antimicrobial resistance

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Fowler Lab
Fowler Lab

Predicting antimicrobial resistance

Category: tuberculosis

antimicrobial resistance

Oxford Public & Community Engagement Conference

Philip Fowler, 12th June 202623rd June 2026

As part of the “Enriching Engagement – funding, culture and institutional legacy” session at the…

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antimicrobial resistance

NIHR PPI In Action Webinar on BashTheBug

Philip Fowler, 1st June 20261st June 2026

As part of the NIHR’s “PPI In Action” series, Philip Fowler gave a webinar on…

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New preprint: ONT sequencing is comparable to Illumina sequencing for M. tuberculosis

Philip Fowler, 9th April 20269th April 2026

In this preprint, we compare the differences when Mycobacterial samples are sequenced with either long-…

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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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