DNAsmart: Multiple attribute ranking tool for DNA data storage systems

Ezekannagha, Chisom; Welzel, Marius; Heider, Dominik; Hattab, Georges

doi:10.1016/j.csbj.2023.02.016

Cited by 8 publications

(4 citation statements)

References 45 publications

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“…The DNA information storage process consists of four main steps [27]: (a) Encoding digital information into a DNA sequence. (b) Synthesizing DNA sequences.…”

Section: Design Of the 64-element Coded Tablementioning

confidence: 99%

Highly Robust DNA Data Storage Based on Controllable GC Content and homopolymer of 64-Element Coded Tables

Yunfei,

Xuncai

2023

Preprint

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In this paper, we propose a DNA storage encoding scheme based on a 64-element coding table combined with forward error correction. The method encodes the data into DNA sequences by LZW compression of the original text, adding error correction codes and scrambling codes. In the encoding process, the effects of GC content limitation and long homopolymers on DNA sequences are considered. At the same time, RS error correction code is introduced to correct the DNA sequence to improve the accuracy of decoding. Finally, the feasibility and effectiveness of the program were verified by simulation experiments on Shakespeare’s sonnets. The data results show that the GC content of DNA sequences encoded by the program is kept at 50%, the homologous multimer length is not more than 2, and the original information can be recovered from the data of 10-fold sequencing depth without error with an error rate of 0.3%. We conducted simulation experiments of primer design, DNA sequence recombination, PCR amplification, and sequence reading on DNA sequences loaded with design information, which further proved the concrete feasibility of the scheme. This scheme provides a reliable and efficient encoding scheme for DNA information storage.

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“…The DNA information storage process consists of four main steps [27]: (a) Encoding digital information into a DNA sequence. (b) Synthesizing DNA sequences.…”

Section: Design Of the 64-element Coded Tablementioning

confidence: 99%

Highly Robust DNA Data Storage Based on Controllable GC Content and homopolymer of 64-Element Coded Tables

Yunfei,

Xuncai

2023

Preprint

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“…Utilizing DNA as a means to store data is an active field of research, with many advances that were reported in recent years. 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 One important aspect of DNA as a data storage device is the error types that are typically observed in DNA: substitutions, which involve the change from one base to another, insertions of one or more bases into the DNA strand, which lead to a positional shift of all following bases to the right in the DNA strand, and deletions of bases that lead to all following bases being shifted to the left. 11 The positional change of bases in a DNA strand increases the decoding complexity, and many different strategies have been developed for the decoding of sequences that contain indel (i.e., insertion or deletion) errors.…”

Section: Introductionmentioning

confidence: 99%

Turbo autoencoders for the DNA data storage channel with Autoturbo-DNA

Welzel,

Dreßler,

Heider

2024

iScience

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“…DNA, with a storage density of around , and a potential lifetime of hundreds of years [1], is one potential candidate for such a next-generation storage device. Utilizing DNA as a means to store data is an active field of research, with many advances that were reported in recent years [3, 4, 5, 6, 7, 8]. One important aspect of DNA as a data storage device is the error types that are typically observed in DNA: besides the change from one base to another (substitutions), other error types common in DNA are the insertion of a base into the DNA strand, leading to all bases that follow the erroneous base to be shifted one position to the right, or the deletion of a base, leading to all following bases being shifted one position to the left.…”

Section: Introductionmentioning

confidence: 99%

Autoturbo-DNA: Turbo-Autoencoders for the DNA data storage channel

Welzel,

Dreßler,

Heider

2023

Preprint

Self Cite

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DNA, with its high storage density and long-term stability, is a potential candidate for a next-generation storage device. The DNA data storage channel, comprised of synthesis, amplification, storage, and sequencing, exhibits error probabilities and error profiles specific to the components of the channel. Here, we present Autoturbo-DNA, a PyTorch framework for training error-correcting, overcomplete autoencoders specifically tailored for the DNA data storage channel. It allows training different architecture combinations and using a wide variety of channel component models for noise generation during training. It further supports training the encoder to generate DNA sequences that adhere to user-defined constraints.

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DNAsmart: Multiple attribute ranking tool for DNA data storage systems

Cited by 8 publications

References 45 publications

Highly Robust DNA Data Storage Based on Controllable GC Content and homopolymer of 64-Element Coded Tables

Highly Robust DNA Data Storage Based on Controllable GC Content and homopolymer of 64-Element Coded Tables

Turbo autoencoders for the DNA data storage channel with Autoturbo-DNA

Autoturbo-DNA: Turbo-Autoencoders for the DNA data storage channel

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