AI classifier flags bird flu genomes more likely to spread in mammals

Phys.org

A research team from the LKS Faculty of Medicine at the University of Hong Kong (HKUMed) has developed a machine-learning classifier capable of analyzing the genomes of influenza A viruses (IAVs) to accurately predict their potential risk of transmission among mammals. The team has successfully identified the key clues that may explain cross-species transmission of influenza A viruses from birds to mammals, and even to humans. The study, published in Nature Microbiology, found that when guanine (G) or cytosine (C) associated in the IAV genome decreased, the virus demonstrated a higher risk for sustained transmission in mammals, including humans. The research team recommends incorporating this genome signature into future influenza pandemic risk assessment frameworks to facilitate the early identification of high-risk viral strains.