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集成的错误纠正以提高基于DNA纳米结构的数字数据存储的效率

Cuiping Mao^1,2, Shuo Zheng³, Zhihao Huang¹

¹Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, P. R. China.

|August 7, 2025

概括

一个集成的错误校正 (IEC) 算法通过有效地纠正错误来增强DNA数据存储. 这种新的方法提高了合成DNA信息系统的数据完整性和解码效率.

科学领域:

生物技术是生物技术.
生物信息学是一种生物信息学.
数据存储数据存储数据存储

背景情况:

合成DNA提供高密度,持久的信息存储.
数据完整性因DNA读取过程中的错误而受到挑战.
现有的错误纠正方法减少了存储密度,并且由于冗余而增加了成本.

研究的目的:

开发用于合成DNA数据存储的综合错误校正 (IEC) 算法.
为了提高数据完整性,存储密度和解码效率.
为了克服传统的纠错代码的局限性.

主要方法:

开发了一种IEC算法,它结合了Levenshtein距离用于集群,滑动窗优化的Hamming距离用于插入/删除纠正,以及对序列选择进行分数加权多数投票.
实现了耐错误聚类 (10倍更快) 和优化序列选择 (2%更高的准确性).
使用2.4%的低冗余率同时纠正插入,删除和替换错误.

主要成果:

实现了每核酸1.4位的逻辑存储密度,远高于传统方法.
证明了插入,删除和替换错误的同时纠正,其冗余率为2.4%,而典型的最小值为7%.
将序列数量减少了3个数量级,最大限度地降低了计算开销,提高了解码效率.

结论:

该IEC算法有效地从含有错误的合成DNA中恢复数据,确保高保真度.
IEC显著提高了存储密度和解码效率,同时最大限度地减少了冗余.
这种方法代表了可靠和高效的DNA数据存储的重大进步.

关键词:

DNA 储存 DNA 存储纠正错误纠正错误纠正错误纠正错误健康和医疗数据健康和医疗数据高密度数据存储高密度数据存储协同作用机制协同作用机制

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