Dr Nicole Wheeler from the University of Canterbury in collaboration with Associate Professor Paul Gardner from the Helmholtz Institute has developed a smart software to predict how dangerous a particular strain of Salmonella will be.
The software that uses machine learning algorithms could be useful to flag dangerous bacteria before they cause an outbreak, from individual hospital wards up to a global scale. Scientists believe that their work will highly affect the reconnaissance of hazardous microorganisms in a way we haven’t possessed the capacity to previously, in healing center wards, as well as at a worldwide scale.
Paper authors Dr. Nicole Wheeler and Associate Professor Paul Gardner worked on the research, which formed Dr. Wheeler’s 2017 Ph.D. thesis, at UC’s Biomolecular Interaction Centre (BIC), which also funded the research and UC’s School of Biological Sciences. Dr. Wheeler continued her research as a BIC postdoctoral fellow in 2017.
Some Salmonella strains can be frightful microbes that reason sickness, loose bowels, regurgitating, and other sustenance harming side effects, while others can be moderately innocuous.
Dr. Wheeler said, “We have designed a new machine learning model that can identify which emerging strains of bacteria could be a public health concern. Using this tool, we can tackle massive data sets and get results in seconds.”
Their results are published in the journal PLOS Genetics.