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基于MOPE编码算法的高净信息密度DNA数据存储

High Net Information Density DNA Data Storage by the MOPE Encoding Algorithm.

作者信息

Zheng Yanfen, Cao Ben, Wu Jieqiong, Wang Bin, Zhang Qiang

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2023 Sep-Oct;20(5):2992-3000. doi: 10.1109/TCBB.2023.3263521. Epub 2023 Oct 9.

Abstract

DNA has recently been recognized as an attractive storage medium due to its high reliability, capacity, and durability. However, encoding algorithms that simply map binary data to DNA sequences have the disadvantages of low net information density and high synthesis cost. Therefore, this paper proposes an efficient, feasible, and highly robust encoding algorithm called MOPE (Modified Barnacles Mating Optimizer and Payload Encoding). The Modified Barnacles Mating Optimizer (MBMO) algorithm is used to construct the non-payload coding set, and the Payload Encoding (PE) algorithm is used to encode the payload. The results show that the lower bound of the non-payload coding set constructed by the MBMO algorithm is 3%-18% higher than the optimal result of previous work, and theoretical analysis shows that the designed PE algorithm has a net information density of 1.90 bits/nt, which is close to the ideal information capacity of 2 bits per nucleotide. The proposed MOPE encoding algorithm with high net information density and satisfying constraints can not only effectively reduce the cost of DNA synthesis and sequencing but also reduce the occurrence of errors during DNA storage.

摘要

由于具有高可靠性、高容量和高耐久性,DNA最近已被视为一种有吸引力的存储介质。然而,简单地将二进制数据映射到DNA序列的编码算法存在净信息密度低和合成成本高的缺点。因此,本文提出了一种高效、可行且高度稳健的编码算法,称为MOPE(改进的藤壶交配优化器与有效载荷编码)。改进的藤壶交配优化器(MBMO)算法用于构建非有效载荷编码集,有效载荷编码(PE)算法用于对有效载荷进行编码。结果表明,MBMO算法构建的非有效载荷编码集的下限比先前工作的最优结果高3%-18%,理论分析表明,所设计的PE算法的净信息密度为1.90比特/核苷酸,接近每个核苷酸2比特的理想信息容量。所提出的具有高净信息密度且满足约束条件的MOPE编码算法,不仅可以有效降低DNA合成和测序成本,还可以减少DNA存储过程中的错误发生。

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