Studies from University of Maryland Have Provided New Data on Salmonella (A Machine Learning Approach To Identifying Salmonella Stress Response Genes In Isolates From Poultry Processing).

A study conducted by researchers at the University of Maryland in College Park explored the use of machine learning to identify genes associated with Salmonella stress response during poultry processing. The study used whole genome sequencing data from 177 Salmonella isolates obtained from various chicken sources. Six machine learning algorithms were trained on the data, with the best performing algorithm achieving an AUROC score of 0.904. The study identified several significant genes involved in stress response, including those associated with zinc transport, transferase activity, cold and heat shock responses, lipopolysaccharide biosynthesis, DNA repair and replication, biofilm formation, and cellular metabolism. The research was supported by the U.S. Department of Agriculture and has been peer-reviewed. [Extracted from the article]

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