Mohammadali Serajian

This paper reviews computational methods for predicting antimicrobial resistance in Mycobacterium tuberculosis using genomic data, comparing catalog-based and machine learning approaches.

AURA is a scalable machine learning framework for predicting antibiotic resistance in Mycobacterium tuberculosis, identifying novel resistance-associated loci.

This paper develops a machine learning classifier to predict antibiotic resistance in Mycobacterium tuberculosis using genomic data and achieves high accuracy for first-line antibiotics.