Researchers like Raul Rabadan, a theoretical physicist working in biology at Columbia University, want to understand how viruses that ordinarily infect birds or pigs suddenly jump to humans and then become easily transmissible: “What are the specific mutations that contribute to a virus becoming a human pathogen?” he explained.
Traditionally, answering this question would have required a painstaking comparison of the DNA or protein sequence of different viruses. But armed with rapidly growing databases of virus sequences, scientists are now using sophisticated machine learning techniques — a branch of artificial intelligence in which computers develop algorithms based on the data they have been given — to identify key properties in viruses like H7N9. Knowing these properties will help researchers identify the most dangerous new flu strains and could lead to more effective vaccines. Most importantly, scientists can now look at hundreds or thousands of flu strains simultaneously, which could reveal common mechanisms across different viruses or a broad diversity of transformations that enable human transmission.
via Wired
