Tianjin University’s Frontiers Science Center for Synthetic Biology, in collaboration with Tianjin Huanhu Hospital, has achieved a significant milestone in DNA-based data storage by introducing the innovative DNA Palette coding scheme.
This groundbreaking method enables the successful encoding of brain magnetic resonance imaging (MRI) data into DNA, along with lossless decoding and three-dimensional reconstruction of the imaging data. This advancement paves the way for the development of advanced medical data storage technologies.
The research findings were recently published in the National Science Review.
Brain MRI scans are essential tools for clinical diagnosis, surgical planning, and treatment evaluation. However, the vast amounts of data generated pose significant challenges for long-term storage solutions. This issue is particularly critical for diseases such as juvenile Parkinson’s, epilepsy, and neurogenetic disorders, where lifelong data accumulation and analysis are crucial.
Current storage media struggle to meet the high demand for large-scale, long-term data preservation. DNA, renowned for its exceptional stability and storage density, has emerged as a promising medium for data storage.
The Tianjin University research team successfully encoded 11.28 megabytes of brain MRI data into approximately 250,000 DNA sequences, achieving an impressive data density of 2.39 bits per nucleotide base. The encoded oligonucleotides—short strands of synthetic DNA—are stored in dry powder form, weigh just 3 micrograms, and support over 300 read operations under current technical standards.
This breakthrough demonstrates DNA’s potential as a long-term, efficient, and secure storage medium for medical data. The study marks a crucial step toward the practical application of DNA data storage, offering a new technical route for safeguarding vast amounts of medical information and accelerating the broader adoption of DNA-based storage technologies.
Reference(s):
Researchers make breakthrough in DNA-based storage of brain MRI data
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