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Washington State University researchers have developed a novel way to identify previously unrecognized antibiotic-resistance genes in bacteria.
By employing machine learning and game theory, the researchers were able to determine with 93 to 99 percent accuracy the presence of antibiotic-resistant genes in three different types of bacteria.
Researchers - Graduate - Student - Abu - Sayed
The researchers, including graduate student Abu Sayed Chowdhury and Professor Shira Broschat in the School of Electrical Engineering and Computer Science, and Douglas Call in the Paul Allen School of Global Animal Health, report on their work in the high-profile journal, Scientific Reports.
The increasing prevalence of antibiotic-resistant bacteria is a growing problem around the world. Every year, millions of people in the U.S. are infected with drug-resistant pathogens, and thousands of people die from pneumonia or bloodstream infections that become impossible to treat.
Years - Researchers - Use - Genome - Genes
In recent years, researchers have been working to make use of genome sequencing to identify antibiotic-resistant genes, looking for similar sequences of genes in public databases. This works for identifying well-known antibiotic-resistant genes, but doesn't hold up with new or unusual genes.
"There appears to be a vast reservoir of antibiotic resistance genes in the natural world," said Call. "This tool allows us to identify presumed resistance genes that would...
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