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    This study introduces a novel DNA data storage method using specific base sequences and coding rules. The approach enhances data error correction and recovery, ensuring reliable storage even with significant error rates.

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    Area of Science:

    • Biotechnology
    • Bioinformatics
    • Data Storage

    Background:

    • DNA offers high storage density, stability, and low energy consumption for data storage.
    • Traditional DNA storage schemes often overlook local stability and decoding robustness.
    • Existing methods require improvement for reliable large-scale data archiving.

    Purpose of the Study:

    • To develop a robust DNA data storage coding scheme.
    • To enhance error detection, correction, and data recovery capabilities.
    • To improve the reliability of DNA data storage.

    Main Methods:

    • Developed a coding scheme using 48 "0-1" mapping rules and specific base sequences.
    • Encoded data into DNA sequences with specific patterns for improved error handling.
    • Combined multivariate Huffman rotational coding with rule-indexed sequences.
    • Utilized comparison with specific base sequences and multiple sequencing for error detection and data recovery.

    Main Results:

    • Achieved local GC content between 45% and 55%, preventing long homopolymers.
    • Demonstrated near-complete data recovery with a 20% error rate using only 5 sequencing passes.
    • Showcased improved error tolerance by adjusting specific base sequence length and sequencing passes.
    • Attained an average storage density of 1.33 bits per nucleotide (bit/nt).

    Conclusions:

    • The proposed coding scheme significantly enhances the robustness and reliability of DNA data storage.
    • This method offers a new approach for dependable storage of large-scale biological data.
    • The scheme effectively addresses error correction and data recovery challenges in DNA storage.