Efficient Bee Identification

Kiah, Han Mao; Vardy, Alexander; Yao, Hanwen

doi:10.1109/isit45174.2021.9518112

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…They also compare the error exponents of random code ensembles and typical random codes and show that typical random codes provide a significant improvement. Since then, followup works have refined these error exponents, considered different scenarios in terms of what constitutes an error when recovering σ and whether all bees are observed at the output [TTV20; TM20], and have proposed efficient ways to perform the joint decoding [KVY21].…”

Section: Independent Decoding and The Bee Identification Problemmentioning

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: Independent Decoding and The Bee Identification Problemmentioning

confidence: 99%

Information-Theoretic Foundations of DNA Data Storage

Shomorony

Heckel

2022

FNT in Communications and Information Theory

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“…Out-of-order channels have also been considered in the context of the noisy permutation channel [18,42], which is a channel that breaks codewords into individual symbols and shuffles them. The bee identification problem [43][44][45][46] is another example of an out-of-order channel, where barcodes are output in a noisy and unordered fashion.…”

Section: Introductionmentioning

confidence: 99%

An Information Theory for Out-of-Order Media With Applications in DNA Data Storage

Ravi,

Vahid,

Shomorony

2024

IEEE Trans. Mol. Biol. Multi-Scale Commun.

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Recent advancements in DNA-based storage prototypes focus on encoding information across multiple DNA molecules. This approach utilizes high-throughput sequencing technologies, leading to outputs that are out-of-order. We study the shuffling channel, where input codewords are split into fixed-size fragments. We show that achieving channel capacity uses index-based coding, which assigns unique indices to each fragment. We also introduce two more complex channels, which aim to model popular sequencing strategies in DNA sequencing. In the torn-paper channel, the input codeword is torn up into fragments of random sizes, while in the shotgun sequencing channel, fixed-length random substrings of the input codeword are observed at the output. In both of these channels, the lack of ordering cannot be circumvented by simply adding unique indices to the fragments. We show how the capacity of both of these channels can be achieved using random codes. We introduce and analyze code constructions based on index sequences. While these codes are computationally efficient, they are not capacityachieving, and we leave the questions of finding efficient capacityachieving codes for these settings as open problems.

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