Researchers at the University of California San Diego have developed an approach that uses machine learning to identify and predict which genes make infectious bacteria resistant to antibiotics. The approach was tested on strains of Mycobacterium tuberculosis—the bacteria that cause tuberculosis (TB) in humans. It identified 33 known and 24 new antibiotic resistance genes in these bacteria.