AlphaMissense is a machine learning model that predicts the likelihood of

About ten years ago, Žiga Avsec was a physics student taking a crash course in genomics through his university module on machine learning.

He was soon working in the lab that studied rare diseases, on a project aiming to pin down the exact genetic mutation that caused an unusual mitochondrial disease.

This was, as he calls it, a needle in a haystack problem.

There were millions of potential culprits lurking in the genetic code and so many variations in the code that could wreak havoc on a person’s biology.

Of particular interest were so-called missense variants, which are single-letter changes to the gene that result in a different amino acid being made within a protein.

Amino acids are the building blocks of proteins, and proteins are the basis of everything else in the body, so even small changes can have large and far-reaching effects.

There are 71 million possible missesense variants in the human genome.

Only 2 percent have been categorized as either pathogenic

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