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The Best Supercomputers for Research
Used to Simulate Protein Clustering

Azure

According to DEO Science News Source, researchers at Berkeley National Laboratory and the Joint Genome Institute developed an algorithm that allows biologists to harness massively parallel supercomputers to organize datasets with 100s of millions of proteins and other cellular components.

More specifically, researchers took on one of the most widely used clustering approaches in biology—the Markov Clustering (MCL) algorithm. They were able to modify it to run effectively and efficiently at scale on distributed memory supercomputers. In many regards, this opens the door for supercomputers to solve many puzzles that, until now, have been unsolvable.

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