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Synchronization errors, such as insertions and deletions, present a fundamental challenge in DNA-based data storage systems, arising from both synthesis and sequencing noise. These channels are often modeled as…

Information Theory · Computer Science 2025-06-23 Ziv Aharoni , Henry D. Pfister

Motivated by DNA storage in living organisms, and by known biological mutation processes, we study the reverse-complement string-duplication system. We fully classify the conditions under which the system has full expressiveness, for all…

Information Theory · Computer Science 2021-12-23 Eyar Ben-Tolila , Moshe Schwartz

DNA strands serve as a storage medium for $4$-ary data over the alphabet $\{A,T,G,C\}$. DNA data storage promises formidable information density, long-term durability, and ease of replicability. However, information in this intriguing…

Information Theory · Computer Science 2024-08-06 Canberk İrimağzı , Yusuf Uslan , Ahmed Hareedy

DNA data storage offers a high-density, long-term alternative to traditional storage systems, addressing the exponential growth of digital data. Composite DNA extends this paradigm by leveraging mixtures of nucleotides to increase storage…

Information Theory · Computer Science 2026-02-13 Busra Tegin , Tolga M Duman

As the global need for large-scale data storage is rising exponentially, existing storage technologies are approaching their theoretical and functional limits in terms of density and energy consumption, making DNA based storage a potential…

Emerging Technologies · Computer Science 2021-10-12 Yotam Nahum , Eyar Ben-Tolila , Leon Anavy

In this paper we study error-correcting codes for the storage of data in synthetic deoxyribonucleic acid (DNA). We investigate a storage model where a data set is represented by an unordered set of $M$ sequences, each of length $L$. Errors…

Information Theory · Computer Science 2020-02-13 Andreas Lenz , Paul H. Siegel , Antonia Wachter-Zeh , Eitan Yaakobi

This paper is concerned with the problem of error-free communication over the i.i.d. duplication channel which acts on a transmitted sequence $ x_1 \cdots x_n $ by inserting a random number of copies of each symbol $ x_i $ next to the…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević

DNA-based data storage has been attracting significant attention due to its extremely high data storage density, low power consumption, and long duration compared to conventional data storage media. Despite the recent advancements in DNA…

Information Theory · Computer Science 2024-11-12 Yi Ding , Xuan He , Tuan Thanh Nguyen , Wentu Song , Zohar Yakhini , Eitan Yaakobi , Linqiang Pan , Xiaohu Tang , Kui Cai

We consider the problem of constructing a code capable of correcting a single long tandem duplication error of variable length. As the main contribution of this paper, we present a $q$-ary efficiently encodable code of length $n+1$ and…

Information Theory · Computer Science 2023-04-26 Daniil Goshkoder , Nikita Polyanskii , Ilya Vorobyev

The emerging field of DNA storage employs strands of DNA bases (A/T/C/G) as a storage medium for digital information to enable massive density and durability. The DNA storage pipeline includes: (1) encoding the raw data into sequences of…

Genomics · Quantitative Biology 2025-01-28 Hadas Abraham , Barak Gahtan , Adir Kobovich , Orian Leitersdorf , Alex M. Bronstein , Eitan Yaakobi

In [1], the authors proposed a new model of DNA storage system that integrates all three steps of retrieval and introduced the concept of DNA-correcting codes, which guarantees that the output of the storage system can be decoded to the…

Information Theory · Computer Science 2023-11-17 Huawei Wu

Reconstruction codes are generalizations of error-correcting codes that can correct errors by a given number of noisy reads. The study of such codes was initiated by Levenshtein in 2001 and developed recently due to applications in modern…

Information Theory · Computer Science 2023-02-21 Zuo Ye , Xin Liu , Xiande Zhang , Gennian Ge

Deep Neural Networks (DNNs) are a revolutionary force in the ongoing information revolution, and yet their intrinsic properties remain a mystery. In particular, it is widely known that DNNs are highly sensitive to noise, whether adversarial…

Machine Learning · Computer Science 2020-05-01 Netanel Raviv , Siddharth Jain , Pulakesh Upadhyaya , Jehoshua Bruck , Anxiao Jiang

Due to their sequential nature, traditional DNA synthesis methods are expensive in terms of time and resources. They also fabricate multiple copies of the same strand, introducing redundancy. This redundancy can be leveraged to enhance the…

Information Theory · Computer Science 2025-10-29 Frederik Walter , Yonatan Yehezkeally

Deep neural networks (DNNs) suffer from noisy-labeled data because of the risk of overfitting. To avoid the risk, in this paper, we propose a novel DNN training method with sample selection based on adaptive k-set selection, which selects k…

Machine Learning · Computer Science 2021-04-06 H. Song , N. Mitsuo , S. Uchida , D. Suehiro

Encoding data as a set of unordered strings is receiving great attention as it captures one of the basic features of DNA storage systems. However, the challenge of constructing optimal redundancy codes for this channel remained elusive. In…

Information Theory · Computer Science 2023-08-16 Jin Sima , Netanel Raviv , Jehoshua Bruck

It has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid cells of the mammalian cortex, analog error correction…

Machine Learning · Computer Science 2025-03-26 Alexander Zlokapa , Andrew K. Tan , John M. Martyn , Ila R. Fiete , Max Tegmark , Isaac L. Chuang

This paper studies achievable rates of nanopore-based DNA storage when nanopore signals are decoded using a tractable channel model that does not rely on a basecalling algorithm. Specifically, the noisy nanopore channel (NNC) with the…

Information Theory · Computer Science 2025-08-13 Brendon McBain , Emanuele Viterbo

This paper introduces a new family of reconstruction codes which is motivated by applications in DNA data storage and sequencing. In such applications, DNA strands are sequenced by reading some subset of their substrings. While previous…

Information Theory · Computer Science 2022-05-10 Yonatan Yehezkeally , Daniella Bar-Lev , Sagi Marcovich , Eitan Yaakobi

This paper extends the foundational work of Dollma \emph{et al}. on codes for ordered composite DNA sequences. We consider the general setting with an alphabet of size $q$ and a resolution parameter $k$, moving beyond the binary ($q=2$)…

Information Theory · Computer Science 2026-02-19 Zuo Ye , Yuling Li , Zhaojun Lan , Gennian Ge