Rotating labeling of entropy coders for synthetic DNA data storage

Over the past years, the ever-growing trend on data storage demand, has motivated research for alternative systems of data storage. Because of its biochemical characteristics, synthetic DNA molecules are considered as potential candidates for a new storage paradigm. Because of this trend, several co...

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Vydané v:International Conference on Digital Signal Processing proceedings s. 1 - 5
Hlavní autori: Pic, Xavier, Antonio, Eva Gil San, Dimopoulou, Melpomeni, Antonini, Marc
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 11.06.2023
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ISSN:2165-3577
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Shrnutí:Over the past years, the ever-growing trend on data storage demand, has motivated research for alternative systems of data storage. Because of its biochemical characteristics, synthetic DNA molecules are considered as potential candidates for a new storage paradigm. Because of this trend, several coding solutions have been proposed over the past years for the storage of digital information into DNA. Despite being a promising solution, DNA storage faces two major obstacles: the large cost of synthesis and the noise introduced during sequencing. Additionally, this noise increases when biochemically defined coding constraints are not respected: avoiding homopolymers and patterns, as well as balancing the GC content. This paper describes a novel entropy coder which can be embedded to any block-based image-coding schema and aims to robustify the decoded results. Our proposed solution introduces variability in the generated quaternary streams, reduces the amount of homopolymers and repeated patterns to reduce the probability of errors occurring. While constraining the code to better satisfy the constraints would degrade the compression efficiency, in this work, we propose an alternative method to further robustify an already-existing code without affecting the compression rate. To this end, we integrate the proposed entropy coder into four existing JPEG-inspired DNA coders. We then evaluate the quality -in terms of biochemical constraints- of the encoded data for all the different methods by providing specific evaluation metrics.
ISSN:2165-3577
DOI:10.1109/DSP58604.2023.10167907