Coding for DNA Storage

DNA-based storage has attracted significant attention due to recent demonstrations of the viability of storing information in macromolecules. Unlike classical optical and magnetic storage technologies, DNA-based storage does not require electrical supply to maintain data integrity, and given the trends in cost decreases of DNA synthesis and sequencing, it is estimated that within the next decade DNA storage may become a highly competitive archiving technology. However, existing coding solutions to address various problems associated with implementations of DNA-based storage systems are very limited in their development.The goal of this research is to develop coding methods and techniques by designing novel and advanced solutions that are specifically targeted for the unique structure and error behavior of DNA-based storage systems. The proposed analytical framework will allow to address coding-theoretic challenges arising in the context of synthesis, storage, and sequencing of DNA strands. To achieve these goals, we aim to design codes for clustering, trace-reconstruction techniques, error-correction codes, and constrained codes. These codes are applicable for long-term storage and recovery of data recorded in DNA, while overcoming the unique challenges associated with the DNA storage channel.We expect that knowledge, techniques, and qualitative insights gained in our investigation will advance DNA storage technologies capable of accommodating the massive amounts of data. Furthermore, solving the proposed coding problems will require new methods and ideas that will also impact adjacent scientific disciplines such as bioinformatics, combinatorics, and theoretical computer science. Thus, the proposed investigation is likely to lead to the development of new paradigms and directions of research that may have far-reaching societal and economic impact. Lastly, the accompanying experimental testing will allow for practical as assessments of system performance and cost.