Coding Over Coupon Collector Channels for Combinatorial Motif-Based DNA Storage

Encoding information in combinations of pre-synthesised deoxyribonucleic acid (DNA) strands (referred to as motifs) is an interesting approach to DNA storage that could potentially circumvent the prohibitive costs of nucleotide-by-nucleotide DNA synthesis. Based on our analysis of an empirical data set from HelixWorks, we propose two channel models for this setup (with and without interference) and analyse their fundamental limits. We propose a coding scheme that approaches those limits by leveraging all information available at the output of the channel, in contrast to earlier schemes developed for a similar setup by Preuss et al. We highlight an important connection between channel capacity curves and the fundamental trade-off between synthesis (writing) and sequencing (reading) costs, and offer a way to mitigate an exponential growth in decoding complexity with the size of the motif library.

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Publication Details

Journal
IEEE Transactions on Communications
Published
2024-11-27
DOI
https://doi.org/10.1109/tcomm.2024.3506938
Citations
8
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
1.87
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article

Coding Over Coupon Collector Channels for Combinatorial Motif-Based DNA Storage

Roman Sokolovskii, Thomas Heinis, Luis Alberto Croquevielle, Parv Agarwal et al.
8 citations
IEEE Transactions on Communications
DNA and Biological Computing
1.87
article

Coding Over Coupon Collector Channels for Combinatorial Motif-Based DNA Storage

Roman Sokolovskii, Thomas Heinis, Luis Alberto Croquevielle, Parv Agarwal, Zijian Zhou
article en
8 citations

Abstract

Encoding information in combinations of pre-synthesised deoxyribonucleic acid (DNA) strands (referred to as motifs) is an interesting approach to DNA storage that could potentially circumvent the prohibitive costs of nucleotide-by-nucleotide DNA synthesis. Based on our analysis of an empirical data set from HelixWorks, we propose two channel models for this setup (with and without interference) and analyse their fundamental limits. We propose a coding scheme that approaches those limits by leveraging all information available at the output of the channel, in contrast to earlier schemes developed for a similar setup by Preuss et al. We highlight an important connection between channel capacity curves and the fundamental trade-off between synthesis (writing) and sequencing (reading) costs, and offer a way to mitigate an exponential growth in decoding complexity with the size of the motif library.

IEEE Transactions on CommunicationsVol. 73(6)
Imperial College London (GB)
Openalex Percentile: Top 14%
DNA and Biological Computing
1.87
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Coding Over Coupon Collector Channels for Combinatorial Motif-Based DNA Storage — Roman Sokolovskii, Thomas Heinis, et al. · IEEE Transactions on Communications (2024) | TGRS Research Map | TGRS