Combination of whole genome sequencing and Supervised Machine Learning provides unambiguous identification of enterohemorrhagic Escherichia coli in raw milk

The objective of this study was to identify, using a genome-wide approach, an unambiguous scheme to predict the presence of highly pathogenic STEC in E. coli reads assemblies derived from complex samples containing potentially multiple E. coli strains.