(University of California - San Diego) Researchers have trained a machine learning algorithm 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. The approach could be used to predict resistance in other infection-causing pathogens.