AI can decode digital data stored in DNA in minutes instead of days

Artificial intelligence can read data stored in DNA strands within 10 minutes instead of days required for previous methods, making DNA storage closer to practical use in computing.

“DNA can store vast quantity in a very compact form and remain intact for thousands of years,” Denilla bar-lave At the University of California, San Diego. “Additionally, DNA is naturally replicated, providing a unique advantage for long -term data protection.”

But recovering the information encountered within DNA is a monumental challenge as the strands are mixed and connected together when stored. During the data-encoding process, individual strands are sometimes repeated incompletely, and some pieces may completely lose. As a result, reading data stored in DNA can be re-organized from a box filled with typo-free pages from reading the data stored in DNA.

“Traditional methods struggle with this anarchy, requiring the days of processing,” say bar-lave. She says that the new approach streamlines “trained to train the pattern in noise with AI”.

Bar-lav and their colleagues developed an AI-powered method, called DNaformer that can quickly and accurately decod DNA sequences. The system consists of a deep learning AI model trained to recreate DNA sequences, a separate computer algorithm that identifies and corrects errors and a third decoding algorithm that is all correcting any remaining mistakes Converts some back to digital data.

In experiments, DNAFORMER can read 100 megabyte DNA-comprehensive data, about 90 times faster than the next fastest method-which was developed with traditional, rule-based computing algorithms-while acquiring better or comparable accuracy. Decoded data includes a colorful image of test tubes, a 24-second audio clip and DNA of the famous Moon Landing speech of astronaut Neel Armstrong and why DNA is a promising data storage medium.

The team has planned to develop versions of DNAFORMER to suit new techniques for data encoding in DNA, Omar Sabari Technion – At Israel Institute of Technology.

“Importally, because our approach does not rely on specific (DNA) synthesis or sequencing methods, it can be adapted to the future, as is still-well-sanctioned technologies that can be more commercially viable, “They say.