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    Area of Science:

    • Biotechnology
    • Bioinformatics
    • Data Storage

    Background:

    • Exponential data growth necessitates novel, high-density storage solutions.
    • DNA offers a persistent and compact medium for data archiving.
    • Current DNA data storage methods face challenges with error rates due to DNA synthesis and hybridization.

    Purpose of the Study:

    • To develop an optimized coding set for DNA data storage.
    • To enhance the thermodynamic properties and reduce error rates in DNA storage systems.
    • To improve the overall accuracy and robustness of DNA data storage.

    Main Methods:

    • Application of a thermodynamic minimum free energy (MFE) constraint for coding set construction.
    • Utilization of the Brownian multi-verse optimizer (BMVO) algorithm, integrating Brownian motion and Nelder-Mead methods.
    • Design and evaluation of DNA storage coding sets using the BMVO algorithm.

    Main Results:

    • The BMVO algorithm successfully designed DNA coding sets with improved thermodynamic properties.
    • The size of the generated coding sets increased by 4%-50% compared to previous methods.
    • Enhanced coding set quality led to improved accuracy and robustness in DNA data storage.

    Conclusions:

    • The BMVO algorithm provides an effective approach for designing high-quality DNA coding sets.
    • Optimized DNA coding sets significantly enhance the performance and reliability of DNA data storage systems.
    • This work contributes to the advancement of DNA data storage as a viable long-term data archiving solution.