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New Algorithm Can Pinpoint Mutations Favored by Natural Selection in Large Sections of the Human Genome

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The finding provides deeper insight into how evolution works.

A team of scientists at the University of California, San Diego, has developed an algorithm that can accurately pinpoint, in large regions of the human genome, mutations favored by natural selection.

Credit: Beata Mierzwa/

Researchers at the University of California, San Diego (UCSD) have developed iSAFE, an algorithm that can accurately identify mutations in the human genome favored by natural selection.

They say this breakthrough provides deeper insight into how evolution works, and could lead to better treatments for genetic disorders.

"Computer science and data science are playing a significant role to better understand the code of life and uncover the hidden patterns in our genome," says UCSD's Ali Akbari.

The new algorithm works by using population genetic signals imprinted in the genomes of the sampled individuals and machine-learning techniques to identify the mutation favored by selection.

The team trained iSAFE on regions of the human genome that contain known favored mutations, ranking the correct mutation as the top one out of more than 21,000 possibilities in 69% of cases.

The algorithm also identified several previously unknown mutations, including five that involve genes related to pigmentation.

From Jacobs School of Engineering (UCSD)
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