Efficient and Explicit Balanced Primer Codes

Chee, Yeow Meng; Kiah, Han Mao; Wei, Hengjia

doi:10.1109/isit.2019.8849437

Cited by 9 publications

(5 citation statements)

References 22 publications

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“…Several recent works have focused on designing error-correcting codes for the specific types of errors that may arise during writing, storing and reading data on DNA. Some important aspects addressed in the recent literature include DNA synthesis constraints such as sequence composition [KPM16; Yaz+15; EZ17; Kov19], the asymmetric nature of the DNA sequencing error channel [GKM15], the need for codes that correct insertions and deletions [Sal+17; KT18a; CKN19; KNY20; CKY20], the need for codes that avoid homopolymers (consecutive repeated nucleotides) as they are conducive to sequencing errors [EZ17; Kov19; KPM16], and the need for codes with balanced GC-content (i.e., roughly the same number of G/C as A/T) [CKW19].…”

Section: Designing Practical Codes For Dna Data Storagementioning

confidence: 99%

Information-Theoretic Foundations of DNA Data Storage

Shomorony

Heckel

2022

FNT in Communications and Information Theory

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Due to its longevity and enormous information density, DNA is an attractive medium for archival data storage. Natural DNA more than 700.000 years old has been recovered, and about 5 grams of DNA can in principle hold a Zetabyte of digital information, orders of magnitude more than what is achieved on conventional storage media. Thanks to rapid technological advances, DNA storage is becoming practically feasible, as demonstrated by a number of experimental storage systems, making it a promising solution for our society's increasing need of data storage.While in living things, DNA molecules can consist of millions of nucleotides, due to technological constraints, in practice, data is stored on many short DNA molecules, which are preserved in a DNA pool and cannot be spatially ordered. Moreover, imperfections in sequencing, synthesis, and handling, as well as DNA decay during storage, introduce random noise into the system, making the task of reliably storing and retrieving information in DNA challenging.This unique setup raises a natural information-theoretic question: how much information can be reliably stored on and reconstructed from millions of short noisy sequences? The goal of this monograph is to address this question by discussing the fundamental limits of storing information on DNA. Motivated by current technological constraints on DNA synthesis and sequencing, we propose a probabilistic channel model that captures three key distinctive aspects of the DNA storage systems: (1) the data is written onto many short DNA molecules that are stored in an unordered fashion; (2) the molecules are corrupted by noise and (3) the data is read by randomly sampling from the DNA pool. Our goal is to investigate the impact of each of these key aspects on the capacity of the DNA storage system. Rather than focusing on coding-theoretic considerations and computationally efficient encoding and decoding, we aim to build an information-theoretic foundation for the analysis of these channels, developing tools for achievability and converse arguments.

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Section: Designing Practical Codes For Dna Data Storagementioning

confidence: 99%

Information-Theoretic Foundations of DNA Data Storage

Shomorony

Heckel

2022

FNT in Communications and Information Theory

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“…The unordered manner of data storing in DNA storage systems motivates the study of coding problem over sets, following several papers on this topic [3], [6], [9], [10], [14]- [16], [18]. In [10], the authors studied the storage model where the errors are a combination of loss of sequences, as well as symbol errors inside the sequences, such This work was supported in part by the Israel Science Foundation (ISF) under Grant 270/18.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, codes that can be used as primer addresses were proposed in [3], [18] to equip the DNA storage system with random-access capabilities.…”

Section: Introductionmentioning

confidence: 99%

Improved Coding over Sets for DNA-Based Data Storage

Wei¹,

Schwartz²

2020

Preprint

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Error-correcting codes over sets, with applications to DNA storage, are studied. The DNA-storage channel receives a set of sequences, and produces a corrupted version of the set, including sequence loss, symbol substitution, symbol insertion/deletion, and limited-magnitude errors in symbols. Various parameter regimes are studied. New bounds on code parameters are provided, which improve upon known bounds. New codes are constructed, at times matching the bounds up to lower-order terms or small constant factors.

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“…Hence, finding codes and algorithms for the clustering process is an important challenge. A naive solution is to add redundancy to the index part in order to correct potential errors in the index [3]. However, this will incur an unavoidable reduction in the storage rate of the DNA storage system.…”

Section: Introductionmentioning

confidence: 99%

Clustering-Correcting Codes

Shinkar

Yaakobi

Lenz

et al. 2019

2019 IEEE International Symposium on Information Theory (ISIT)

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A new family of codes, called clustering-correcting codes, is presented in this paper. This family of codes is motivated by the special structure of data that is stored in DNA-based storage systems. The data stored in these systems has the form of unordered sequences, also called strands, and every strand is synthesized thousands to millions of times, where some of these copies are read back during sequencing. Due to the unordered structure of the strands, an important task in the decoding process is to place them in their correct order. This is usually accomplished by allocating a part of the strand for an index. However, in the presence of errors in the index field, important information on the order of the strands may be lost.Clustering-correcting codes ensure that if the distance between the index fields of two strands is small, then there will be a large distance between their data fields. It is shown how this property enables to place the strands together in their correct clusters even in the presence of errors. We present lower and upper bounds on the size of clustering-correcting codes and an explicit construction of these codes which uses only a single bit of redundancy.

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Efficient and Explicit Balanced Primer Codes

Cited by 9 publications

References 22 publications

Information-Theoretic Foundations of DNA Data Storage

Information-Theoretic Foundations of DNA Data Storage

Improved Coding over Sets for DNA-Based Data Storage

Clustering-Correcting Codes

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