DNA mutation is a cardinal feature of biology. Small genetic variations – and the resulting proteins that build our cells – can lead to profound disruptions in physiological function, sometimes causing disease.
A handful of well-known genetic mutations and their associated conditions are well understood. However, dramatic leaps ahead in genome sequencing technology has not been followed with similarly rapid advances in the ability to interpret the meaning of the millions of genetic variations identified through human genome sequencing.
Harvard and Oxford researchers sought to make sense of these data by developing an AI tool called Eve (Evolutional model of Variant Effect). Eve uses machine learning to detect patterns of genetic variation across hundreds of thousands of non-human species and apply them to make predictions about the implications of variation in human genes.
In an analysis published in Nature, the researchers used Eve to assess 36 million...