date:Feb 11, 2019
A team of scientists led by researchers at the University of Georgia Center for Food Safety in Griffin, Georgia, has developed a machine-learning approach that could lead to quicker identification of the animal source of certain Salmonella outbreaks.
In the research, published in the January 2019 issue of Emerging Infectious Diseases, Xiangyu Deng and his colleagues used more than a thousand genomes to predict the animal sources, especially livestock, of Salmonella Typhimurium.
Deng, an assist