Over the past decade, several studies have shown that DNA-based storage systems can potentially become the standard for data archival due to their high data density and durability. However, the current bottleneck involves the synthesis and sequencing costs, along with a lack of coding solutions to address the unique error characteristics of DNA-based systems.
This work tackles multiple challenges that hinder the practical implementation of DNA storage. First, we explore theoretical aspects of the deletion channel, presenting detailed findings from the maximum likelihood decoder for both single and dual-channel outputs. Next, we address the DNA reconstruction problem, aiming to accurately reconstruct a DNA sequence from multiple noisy copies. We propose several reconstruction algorithms that significantly enhance accuracy compared to previously published approaches. Furthermore, we investigate two novel synthesis methods, the composite synthesis and the combinatorial composite synthesis, highlighting their potential benefits and inherent complexities. These methods require innovative algorithmic and coding solutions, and thus we design error-correction codes specifically tailored for these technologies.
Finally, we introduce the DNA storalator, a software tool designed to simulate the biological and computational processes of DNA storage, aiding our research and facilitating further exploration within the scientific community. Overall, the results presented in this work advance several aspects of DNA data storage and promote the feasibility of this storage solution further.
