Researchers are using “machine learning”, a process by which computers use compiled data to develop algorithms, to try and determine distinctive characteristics of viruses with pandemic potential, like H7N9. It’s hoped that being able to identify these properties will help alert virologists when new strains emerge containing them. Machine learning enables researchers to cross-reference tremendous amounts of data – “hundreds of thousands of flu strains” – to look for similar markers of pathogenicity.
Wired – “‘It’s changing the field radically,’ said Nir Ben-Tal, a computational biologist at Tel Aviv University in Israel. Researchers are also using these approaches to investigate a broad range of viral mysteries, including what makes some viruses more harmful than others and the factors that influence a virus’s ability to trigger an immune response. The latter could ultimately aid the development of flu vaccines. A study published in July analyzed differences in the human immune system’s response to flu, identifying for the first time genetic variants that seem to influence an individual’s ability to fight off H1N1. Machine learning techniques might even accelerate future efforts to identify the animal source of mystery viruses.”
Read more here.
(image: Axs Deny/Flickr)