Trellis BMA: Coded Trace Reconstruction on IDS Channels for DNA Storage

Srinivasavaradhan, Sundara Rajan; Gopi, Sivakanth; Pfister, Henry D.; Yekhanin, Sergey

doi:10.1109/isit45174.2021.9517821

Cited by 43 publications

(33 citation statements)

References 30 publications

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“…5a shows the average normalized Hamming distance between the decoded information and the original one under different sequence copies. Clearly, the proposed method (red color) dramatically outperforms the Trellis BMA 6 (blue color) and the multiply posteriors method (orange color) by Lenz et al 13 . This indicates our modulation-based decoding method is superior to the other two HMM-based methods.…”

Section: Resultsmentioning

confidence: 89%

“…We compare our decoding performance with that of Trellis BMA 4 on a real dataset published by the Microsoft group. In order to apply the proposed method on this dataset, we first construct a carrier strand for each DNA sequence by translating A/T to 0 and G/C to 1.…”

Section: Resultsmentioning

confidence: 99%

“…As the amount of available data grows exponentially, recent developments in synthesis and sequencing technology are making synthetic DNA more attractive as a new data storage medium 1, 2, 3 . Compared with traditional electric/optical/magnetic storage media, DNA synthesis and sequencing are highly error prone processes characterized by aggregated insertions, deletions and substitutions (IDSs) 4 . It is estimated that third-generation synthesis and sequencing technologies may introduce 10–15% errors in the writing and reading processes 5 .…”

Section: Introductionmentioning

confidence: 99%

“…The total amount of data stored in synthetic DNA has reached the GB level; various practical automated read/write technologies for DNA storage have been proposed [3][4][5] . Unlike traditional electric/optical/magnetic storage media, DNA storage is characterized by large amount of insertions, deletions, and substitutions(IDSs) due to high error prone DNA synthesis and sequencing processes 6 . The difficulty of data recovery mainly comes from the synchronization problem because of random insertions and deletions.…”

Section: Introductionmentioning

confidence: 99%

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A robust and efficient DNA storage architecture based on modulation encoding and decoding

Zan

Xie

Yao

et al. 2022

Preprint

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Thanks to its high density and long durability, synthetic DNA has been widely considered as a promising solution to the data explosion problem. However, due to the large amount of random base insertion-deletion-substitution (IDSs) errors from sequencing, reliable data recovery remains a critical challenge, which hinders its large-scale application. Here, we propose a modulation-based DNA storage architecture. Experiments on simulation and real datasets demonstrate that it has two distinct advantages. First, modulation encoding provides a simple way to ensure the encoded DNA sequences comply with biological sequence constraints (i.e., GC balanced and no homopolymers); Second, modulation decoding is highly efficient and extremely robust for the detection of insertions and deletions, which can correct up to ~40% errors. These two advantages pave the way for future high-throughput and low-cost techniques, and will kickstart the actualization of a viable, large-scale system for DNA data storage.

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Section: Resultsmentioning

confidence: 89%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A robust and efficient DNA storage architecture based on modulation encoding and decoding

Zan

Xie

Yao

et al. 2022

Preprint

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“…Among other applications, the input entropy is relevant to DNA reconstruction algorithms, since in several of these algorithms such as [6], [37], [43], there is a limitation on the number of noisy copies that are considered by the algorithm's decoder, due to design restrictions and run-time considerations. Therefore, in case the number of received noisy copies is greater than this limitation, a subset of these copies should be considered.…”

Section: Introductionmentioning

confidence: 99%

The Input and Output Entropies of the $k$-Deletion/Insertion Channel

Shubhransh¹,

Sabary²,

Bar-Lev³

et al. 2022

Preprint

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This paper is eligible for the Jack Keil Wolf ISIT Student Paper Award. The channel output entropy of a transmitted word is the entropy of the possible channel outputs and similarly the input entropy of a received word is the entropy of all possible transmitted words. The goal of this work is to study these entropy values for the k-deletion, k-insertion channel, where exactly k symbols are deleted, inserted in the transmitted word, respectively. If all possible words are transmitted with the same probability then studying the input and output entropies is equivalent. For both the 1-insertion and 1-deletion channels, it is proved that among all words with a fixed number of runs, the input entropy is minimized for words with a skewed distribution of their run lengths and it is maximized for words with a balanced distribution of their run lengths. Among our results, we establish a conjecture by Atashpendar et al. which claims that for the binary 1-deletion channel, the input entropy is maximized for the alternating words.

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