Shaheed Vally Omar

This study compares long-read and short-read sequencing for tuberculosis drug resistance and outbreak analysis, finding they are comparable with minimal differences in key clinical outputs.

This paper evaluates the performance of the gnomonicus tool for predicting antibiotic resistance in Mycobacterium tuberculosis using a diverse testset of 2,663 samples and compares it to TB-Profiler.

This paper develops an automated method to build a comprehensive catalogue of resistance-associated variants for M. tuberculosis, achieving comparable performance to existing catalogues without expert rules.

The paper develops an automated method to predict bedaquiline resistance in M. tuberculosis using a reproducible algorithmic approach, achieving high sensitivity and specificity in variant classification.

This study quantifies antibiotic resistance in tuberculosis using genomic data and MIC measurements to identify genetic determinants of resistance and hypersensitivity across multiple drugs.

GenomegaMap estimates genome-wide dN/dS ratios across 10,209 tuberculosis genomes to identify selection pressures shaping the pathogen's evolution.