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Predicting antibiotic resistance de novo

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Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

Category: antimicrobial resistance

antimicrobial resistance

CRyPTIC datasets available through new website

Philip Fowler, 25th June 20257th July 2025

The CRyPTIC project ran from 2016 to 2022 and collected >20,000 clinical samples from patients…

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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: looking at rifampicin-resistant subpopulations in clinical samples

Philip Fowler, 10th April 202510th April 2025

Since clinical samples are usually grown in a MGIT tube for a while before some…

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New grant: Ox4TB

Philip Fowler, 17th March 202517th March 2025

Very pleased to announce that I am a co-investigator on the recently announced Oxford4TB project…

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antimicrobial resistance

Can medical microbiology become a big data science? Lessons from CRyPTIC

Philip Fowler, 11th March 202511th March 2025

The CRyPTIC project ran from 2017 to around 2022 and in that time collected over…

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