Core Insights - The research team at Tianjin University has developed a new DNA storage system called HELIX, specifically designed for storing biomedical data, achieving the storage and recovery of 60MB of spatiotemporal omics images [1][2] - Traditional storage methods are becoming inadequate in the era of big data, leading to the emergence of DNA information storage technology, which is seen as a potential solution for large-scale data storage [1] - DNA can store hundreds of exabytes of data per gram and can preserve information for thousands of years without power, making it particularly promising for biomedical data applications [1] System Features - HELIX consists of three core modules: image compression, error correction coding, and image restoration, enhancing the system's fault tolerance and recovery capabilities [1][2] - The team optimized existing compression algorithms to address potential base errors during DNA storage, significantly improving the system's robustness [2] - Deep learning techniques were incorporated to enhance the success rate of image decoding and information recovery during the image restoration process [1][2] Experimental Results - In wet lab experiments, the team successfully encoded two 60MB spatiotemporal omics images into 130,000 DNA sequences, each containing 183 bases, and recovered the image data using DNA synthesis and sequencing technology [2] - The HELIX system demonstrated strong robustness, requiring only about 5.8 times the sequencing depth to recover the majority of the image information [2] - This achievement marks a significant step towards the practical application of DNA information storage technology, showcasing superior storage efficiency and reliability [2]

新华社天津5月19日电（记者张建新、栗雅婷）近日，我国科研人员在DNA存储领域取得新突破，研发了一种全新的DNA存储系统——HELIX， 该系统专门用于存储生物医学数据，并成功实现了60MB的时空组学图像的存储与恢复。 研究团队利用DNA成功存储两张图片。新华社发 吴华明介绍，每克DNA能够存储数百艾字节的数据，并且在无需电力的情况下能够保存长达数千年。尤其在生物医学数据领域，DNA存储的潜力 尤为显著，其存储的图片数据分辨率高、存储周期长、且相似度强，具有巨大的应用前景。 据介绍，研究团队开发的HELIX系统包含三个核心模块：图像压缩、图像纠错编码和图像复原。针对DNA存储过程中可能出现的碱基错误， HELIX对现有压缩算法进行了优化，大幅增强了系统的容错能力。同时，为了进一步提升图像解码的成功率，团队还引入了深度学习技术，在图 像修复过程中显著增强了信息恢复的能力。 在实验室中，研究团队成功将两张共60MB的时空组学图像编码为13万条、每条183个碱基的DNA序列，并通过DNA合成与测序技术，成功恢复了 图像数据。 吴华明表示，该研究表明，针对特定数据类型量身定制的DNA存储系统，不仅在存储效率上表现卓越 ...