- Shares in Stellantis, Aston Martin skid on profit warnings
- Dali prints found in London garage sold at auction
- ECB chief backs bank mergers amid UniCredit, Commerzbank talk
- China stocks soar on stimulus, but US and Europe retreat
- 100 dead in storm Helene damage, flooding across US southeast
- China stocks soar on stimulus, Europe slides on automaker woes
- German antitrust watchdog steps up monitoring of Microsoft
- Nepal's urban poor count cost of 'nightmare' floods
- E.Guinea, Gabon clash at ICJ over oil-rich islands
- New blow for UK's Starmer as growth data disappoints
- China's top banks to tweak mortgage rates to boost housing market
- Muslim women break taboos navigating east London's waterways
- Nepal dam-building spree powers electric vehicle boom
- More than 60 dead from storm Helene as rescue, cleanup efforts grow
- Dozens missing, 9 dead in migrant boat wreck off Spanish Canaries
- Death toll from Hurricane John hits eight in Mexico
- Storm Helene's toll rises as rescue and cleanup efforts gain pace
- SpaceX launches mission to return stranded astronauts
- Storm Helene kills 44, threatens more 'catastrophic' flooding as cleanup begins
- SpaceX set to launch mission to return stranded astronauts
- Storm Helene kills 44, threatens more 'catastrophic' flooding
- Boeing strike grinds on as latest talks fail to reach agreement
- Iran 'news' sites, hackers target Trump ahead of US election
- US ports brace for potential dockworkers strike
- Japan's speedy, spotless Shinkansen bullet trains turn 60
- US hurricane deaths rise to 44, fears of more 'catastrophic' flooding
- Global stocks mostly rise, cheering Beijing stimulus
- Europe en route for Moon with new simulator, says astronaut Pesquet
- Fireworks forecast if comet survives risky Sun flypast
- Argentina judge orders dictionary to delete pejorative definition of 'Jewish'
- Global stocks rise on rate hopes, Beijing stimulus
- S.African woman turns 118, among the oldest in the world
- UK clears $4 bn AI partnership between Amazon, Anthropic
- Barca fans barred from Champions League away game over racist banner
- Chinese stocks extend surge, Europe higher on Beijing stimulus
- Pope says Church must 'seek forgiveness' for child sexual abuse
- China caps week of 'bazooka' stimulus for ailing economy with rate cut
- Cuts, cash, credit: China bids to jumpstart flagging economy
- France's debt weighs heavier ahead of budget debate
- Iran treads carefully, backing Hezbollah while avoiding war
- Return to sender: waste stranded at sea stirs toxic dispute
- 'Broken' news industry faces uncertain future
- On remote Greek island, migratory birds offer climate clues
- Taken from mother by nuns, victim seeks answers as pope visits Belgium
- China cuts amount banks hold in reserve to boost lending
- Hong Kong, Shanghai extend surge as China optimism boosts markets
- Vietnam president reiterates support for Cuba during official visit
- Drought reduces Amazon River in Colombia by as much as 90%: report
- Stay or go? Pacific Islanders face climate's grim choice
- Florida bracing for 'unsurvivable' Hurricane Helene
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Google AI tool predicts danger of genetic mutations
Researchers at Google DeepMind, the tech giant's artificial intelligence arm, on Tuesday introduced a tool that predicts whether genetic mutations are likely to cause harm, a breakthrough that could help research into rare diseases.
The findings are "another step in recognising the impact that AI is having in the natural sciences," said Pushmeet Kohli, vice president for research at Google DeepMind.
The tool focuses on so-called "missense" mutations, where a single letter of the genetic code is affected.
A typical human has 9,000 such mutations throughout their genome; they can be harmless or cause diseases such as cystic fibrosis or cancer, or damage brain development.
To date, four million of these mutations have been observed in humans, but only two percent of them have been classified, either as disease-causing or benign.
In all, there are 71 million such possible mutations. The Google DeepMind tool, called AlphaMissense, reviewed these mutations and was able to predict 89 percent of them, with 90 percent accuracy.
A score was assigned to each mutation, indicating the risk of it causing disease (otherwise referred to as pathogenic).
The result: 57 percent were classified as probably benign, and 32 percent as probably pathogenic -- the remainder being uncertain.
The database was made public and available to scientists, and an accompanying study was published on Tuesday in the journal Science.
AlphaMissense demonstrates "superior performance" than previously available tools, wrote experts Joseph Marsh and Sarah Teichmann in an article also published in Science.
"We should emphasize that the predictions were never really trained or never really intended to be used for clinical diagnosis alone," said Jun Cheng of Google DeepMind.
"However, we do think that our predictions can potentially be helpful to increase the diagnosed rate of rare disease, and also potentially to help us find new disease-causing genes," Cheng added.
Indirectly, this could lead to the development of new treatments, the researchers said.
The tool was trained on the DNA of humans and closely-related primates, enabling it to recognize which genetic mutations are widespread.
Cheng said the training allowed the tool to input "millions of protein sequences and learns what a regular protein sequence looks like."
It then could identify a mutation and its potential for harm.
Cheng compared the process to learning a language.
"If we substitute a word from an English sentence, a person that is familiar with English can immediately see whether this word substitution will change the meaning of the sentence or not."
D.Philippon--CPN