Constituents


How Machine Learning Helps Identify Toxicity In Potential Drugs

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The team believe that being able to determine the atomic structure of protein molecules will play a huge role in understanding how they work, and how they may respond to drug therapies. The drugs typically work by binding to a protein molecule, and then changing its shape and thus altering how it works.



Researchers Use Machine Learning to Detect Pathogenic Bacteria in Cattle

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A team of researchers has found a new way to detect dangerous strains of bacteria, potentially preventing outbreaks of food poisoning. The team developed a method that utilizes machine learning and tested it with isolates of Escherichia coli strains. The team utilized machine learning, a form of artificial intelligence that allows computers to learn and analyze patterns. If researchers can quickly identify cattle herds carrying dangerous strains of E.coli, that particular herd can be treated or isolated before an outbreak occurs.


The Roslin Institute (University of Edinburgh) - News

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Machine learning can predict strains of bacteria likely to cause food poisoning outbreaks, research has found. The study – which focused on harmful strains of E. coli bacteria – could help public health officials to target interventions and reduce risk to human health. The team trained the software on DNA sequences from strains isolated from cattle herds and human infections in the UK and the US. The study highlights the potential of machine learning approaches for identifying these strains early and prevent outbreaks of this infectious disease.