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Search results (7)

« Back to Publications

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network

Dissanayake D. et al, (2026), BMC Microbiology

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network

Dissanayake D. et al, (2025)

Rapidly and reproducibly building a comprehensive catalogue of resistance-associated variants for M. tuberculosis

Adlard D. et al, (2025)

An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance in Mycobacterium tuberculosis using a reproducible algorithmic approach

Adlard D. et al, (2025), Microbial Genomics, 11

Predicting rifampicin resistance in Mycobacterium tuberculosis using machine learning informed by protein structural and chemical features

Lynch CI. et al, (2025), ERJ Open Research, 11, 00952 - 2024

An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance in M. tuberculosis using a reproducible algorithmic approach

Adlard D. et al, (2025)

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine-learning approaches

Carter JJ. et al, (2024), JAC-Antimicrobial Resistance, 6