2022/04/06 by Haoling Zhang, Zhang, Haoling, Zhaojun Lan +11
Biochemistry, Genetics and Molecular Biology · Computer Science · #46N60 #68P25 #94B70 #94C15 #Advanced Data Storage Technologies #Algorithms and Data Compression #Combinatorics (math.CO) #D.2.8 #DNA and Biological Computing #E.3 #Emerging Technologies (cs.ET) #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #G.2.2 #Genomics (q-bio.GN) #I.1.2 #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.2204.02855
openalex publication_date 2022/04/06 · openalex created_date 2022/04/15 · openalex updated_date 2026/07/28
DNA has been considered a promising medium for storing digital information. As an essential step in the DNA-based data storage workflow, coding algorithms are responsible to implement functions including bit-to-base transcoding, error correction, etc. In previous studies, these functions are normally realized by introducing multiple algorithms. Here, we report a graph-based architecture, named SPIDER-WEB, providing an all-in-one coding solution by generating customized algorithms automatically. SPIDERWEB is able to correct a maximum of 4% edit errors in the DNA sequences including substitution and insertion/deletion (indel), with only 5.5% redundant symbols. Since no DNA sequence pretreatment is required for the correcting and decoding processes, SPIDER-WEB offers the function of real-time information retrieval, which is 305.08 times faster than the speed of single-molecule sequencing techniques. Our retrieval process can improve 2 orders of magnitude faster compared to the conventional one under megabyte-level data and can be scalable to fit exabyte-level data. Therefore, SPIDER-WEB holds the potential to improve the practicability in large-scale data storage applications.