The key insight making this possible is that many properties of biological systems can be interpreted in terms of words and sentences. “We’re learning the language of evolution,” says Bonnie Berger, a computational biologist at the Massachusetts Institute of Technology.
 
In the last few years, a handful of researchers including teams from geneticist George Church’s lab and Salesforce have shown that protein sequences and genetic codes can be modeled using NLP techniques.
 
In a study published in Science today, Berger and her colleagues pull several of these strands together and use NLP to predict mutations that allow viruses to avoid being detected by antibodies in the human immune system, a process known as viral immune escape. The basic idea is that the interpretation of a virus by an immune system is analogous to the interpretation of a sentence by a human.

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