Reconstruction From Noisy Substrings

This paper studies the problem of encoding messages into sequences which can be uniquely recovered from some noisy observations about their substrings. The observed reads comprise consecutive substrings with some given minimum overlap. This coded reconstruction problem has applications in DNA storage. We consider both single-strand reconstruction codes and multi-strand reconstruction codes, where the message is encoded into a single strand or a set of multiple strands, respectively. Various parameter regimes are studied. New codes are constructed, some of whose rates asymptotically attain the upper bounds.

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Publication Details

Journal
IEEE Transactions on Information Theory
Published
2024-09-03
DOI
https://doi.org/10.1109/tit.2024.3454119
Citations
2
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.69

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article

Reconstruction From Noisy Substrings

Gennian Ge, Moshe Schwartz, Hengjia Wei
2 citations
IEEE Transactions on Information Theory
Algorithms and Data Compression
0.69
article

Reconstruction From Noisy Substrings

Gennian Ge, Moshe Schwartz, Hengjia Wei
article en
2 citations

Abstract

This paper studies the problem of encoding messages into sequences which can be uniquely recovered from some noisy observations about their substrings. The observed reads comprise consecutive substrings with some given minimum overlap. This coded reconstruction problem has applications in DNA storage. We consider both single-strand reconstruction codes and multi-strand reconstruction codes, where the message is encoded into a single strand or a set of multiple strands, respectively. Various parameter regimes are studied. New codes are constructed, some of whose rates asymptotically attain the upper bounds.

IEEE Transactions on Information TheoryVol. 70(11)
Ben-Gurion University of the Negev (IL), Xi'an Jiaotong University (CN), Capital Normal University (CN), McMaster University (CA)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 25%
Algorithms and Data Compression
0.69
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