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IBM Research is using A.I. algorithms to unlock the secrets of dark matter DNA

You may have heard of dark matter, a mysterious form of lesser-studied matter that is thought to be composed of some as-yet undiscovered subatomic particles, but which makes up an astonishing 85% of the matter in the universe. But how about dark matter DNA? These unexplored molecules and matter surrounding our genes make up more than half of the human genome — but are a total conundrum in terms of what they encode and, more importantly, affect.

The good folks at IBM and the Munich Leukemia Laboratory think they can help come up with some answers — and they’ve used some groundbreaking A.I. algorithms to help.

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“Despite it making up a large portion of our genome, dark matter DNA has been ignored, as most scientists believe it plays no role,” Laxmi Parida, IBM Research Fellow in Computational Genomics, told Digital Trends. “At IBM Research, we thought there might be more to dark matter DNA than we have been led to believe.”

The researchers designed what they refer to as a “stochastic regularization A.I. model” that was specifically built for DNA data. Using this model, which they termed ReVeal, the team was able to train algorithms on data from patients’ blood samples; allowing the A.I. to learn from and separate specific signals from the dark matter, as well as the rest of the DNA.

“Our most exciting finding was that using ReVeal, we could achieve a 75% accuracy rate in identifying blood cancers just by looking at the DNA or dark matter DNA alone in a patients’ blood sample,” Parida continued. “This is compared to just a 35% accuracy rate with standard A.I. methods on this data.”

From these findings, the researchers suggest that dark matter DNA plays a much larger role than previously thought in influencing the phenotype of cells and tissues. This suggests that dark matter DNA, far from being an inconsequential research footnote, may have a much greater role to play in our genome than people realized. The results also show that DNA alone contains enough signals to accurately classify blood cancers. This lays the groundwork for further analysis into how blood tests could be used to diagnose these complex diseases — which, up until now, required invasive tissue biopsies, histologies, and more.

“In the long term, we hope this leads to more breakthroughs into how dark matter DNA influences the human genome, and clues it can give us into better understanding our genetics and complex disease,” Parida said.

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