Representing Information on DNA using Patterns Induced by Enzymatic Labeling
<|reference_start|>Representing Information on DNA using Patterns Induced by Enzymatic Labeling: Enzymatic DNA labeling is a powerful tool with applications in biochemistry, molecular biology, biotechnology, medical science, and genomic research. This paper contributes to the evolving field of DNA-based data storage by presenting a formal framework for modeling DNA labeling in strings, specifically tailored for data storage purposes. Our approach involves a known DNA molecule as a template for labeling, employing patterns induced by a set of designed labels to represent information. One hypothetical implementation can use CRISPR-Cas9 and gRNA reagents for labeling. Various aspects of the general labeling channel, including fixed-length labels, are explored, and upper bounds on the maximal size of the corresponding codes are given. The study includes the development of an efficient encoder-decoder pair that is proven optimal in terms of maximum code size under specific conditions.<|reference_end|>
@article{bar-lev2024representing,
    title={Representing Information on DNA using Patterns Induced by Enzymatic
  Labeling},
    author={Daniella Bar-Lev, Tuvi Etzion, Eitan Yaakobi, Zohar Yakhini},
    journal={arXiv preprint arXiv:2405.08475},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.08475},
    primaryClass={cs.IT math.IT}
}