Machine Learning IDs Antibiotic-resistance Genes in TB-causing Bacteria

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. The researchers say the approach can be used on other infection-causing pathogens, including staph and bacteria that cause urinary tract infections, pneumonia and meningitis. The work was recently published in Nature Communications.