AI model helps understand viruses likely to jump from animals to humans
Branco Weiss Fellow Daniel Bojar is lead-author of a study published in Cell Reports magazine that discusses a new model that applies artificial intelligence to carbohydrates. Carbohydrates – or glycans – are still not well understood despite participating in nearly all biological processes in the human body – for good or for bad. For example, nearly all viruses use glycans as their first contact with our cells in the process of infection. The newly developed artificial intelligence-based model analyzes glycans with an unprecedented level of accuracy and thus improves the understanding of the infection process by making it possible to predict new virus-glycan interactions. This could help predict which viruses are likely to spread from animals to humans. In addition, the improved understanding of the infection process might help prevent viral infection by developing glycan-based antivirals that suppress the replication ability of viruses.
Read the article in Cell Reports
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