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Repetition coding as an effective error correction code for embedding information in DNA

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Author(s)
Haughton, David 
Balado, Félix 
Uri
http://hdl.handle.net/10197/3405
Date Issued
24 October 2011
Date Available
16T12:05:55Z December 2011
Abstract
The goal of DNA data embedding is to enable robust encoding of non-genetic information in DNA. This field straddles the areas of bioinformatics and digital communications, since DNA mutations can be seen as akin to a noisy channel from the point of view of information encoding. In this paper we present two algorithms which, building on a variant of a method proposed by Yachie et al., rely on repetition coding to effectively counteract the impact that mutations have on an embedded message. The algorithms are designed for resynchronising multiple, originally identical, information encoded DNA sequences, embedded within non-coding DNA (ncDNA) sections of a host genome. They use both BLAST and MUSCLE algorithms to accomplish this. Bit error rates at the decoder are established for mutations rates accumulated over a number of generations of the host organism. The empirical results obtained are compared to a theoretical bound for optimal decoding.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2011 IEEE
Keywords
  • DNA data wmbedding

  • Decoding performance

  • DNA watermarking

  • Sequence alignment

Subject – LCSH
DNA
Data encryption (Computer science)
Digital watermarking
Sequence alignment (Bioinformatics)
DOI
10.1109/BIBE.2011.45
Web versions
http://dx.doi.org/10.1109/BIBE.2011.45
Language
English
Status of Item
Peer reviewed
Part of
2011 IEEE 11th International Conference on Bioinformatics and Bioengineering (BIBE) [proceedings]
Conference Details
11th IEEE International Conference on Bioinformatics and Bioengineering (BIBE), 24-26, October 2011, Taichung, Taiwan
ISBN
978-1-61284-975-1
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
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Computer Science Research Collection
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