A supercomputer has found an archaeal life form that could help fight disease in the future

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Scientists have developed a supercomputer that can search a huge database of genetic material for life.

The technique, described in a paper published on Wednesday in Nature, can be used to find genetic variants of viruses that are highly conserved and, crucially, can help identify the most common pathogens.

“If you want to find viruses that cause the same disease, and you’re trying to identify the variants that cause a lot of disease, you can do that very easily with the data we have,” study leader and biologist Paul McKeon told CNN.

“So we can really, really look at that very, very closely, and we can identify the viruses that have the highest risk.”

McKeon’s team developed the system using a supercomputing platform called a superquark.

It is the equivalent of a super-computer with a fraction of the power, bandwidth and cooling costs. 

“We can look at it with a microscope, which is kind of an amazing, incredible capability,” McKeons team member Matthew Trew told CNN on Wednesday.

“That means you can look very, much more deeply into it than we have ever been able to before.”

The team’s technique is a lot more sophisticated than the work done by McKeo, who recently discovered a new archaemeal lifeform in the algae bacterium Clostridium difficile, which he said is “probably” the most conserved virus in the universe.

“It is the closest thing we have found to a superinfection in our data set,” McLeod said.

The team is now looking at the genomes of other viruses and trying to determine what they are.

“We’re not saying we know what it is, but it’s probably a supermicrobial, and so the goal is to try to figure out what that is,” McKeefe said.

Scientists in the field have found that viruses, such as the coronavirus, are often found in the genomes and proteins of plants.

McKeont’s team hopes to use their data to better understand how viruses evolve and evolve to other life forms.

“It’s a great example of how you can make a really large amount of data with a single data set, and that’s really exciting,” he said.

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