Gene Tagging and the Data Hiding Rate

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Title: Gene Tagging and the Data Hiding Rate
Authors: Balado, Félix
Haughton, David
Permanent link: http://hdl.handle.net/10197/3835
Date: 28-Jun-2012
Abstract: We analyze the maximum number of ways in which one can intrinsically tag a very particular kind of digital asset: a gene, which is just a DNA sequence that encodes a protein. We consider gene tagging under the most relevant biological constraints: protein encoding preservation with and without codon count preservation. We show that our finite and deterministic combinatorial results are asymptotically—as the length of the gene increases— particular cases of the stochastic Gel’fand and Pinsker capacity formula for communications with side information at the encoder, which lies at the foundations of data hiding theory. This is because gene tagging is a particular case of DNA watermarking.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: The Institution of Engineering and Technology
Copyright (published version): 2012, The Institution of Engineering and Technology
Keywords: Gene tagging;DNA watermarking;Combinatorial analysis;Gel’fand;Pinsker capacity
Subject LCSH: Genes
DNA
Data encryption (Computer science)
Digital watermarking
Combinatorial analysis
Language: en
Status of Item: Peer reviewed
Conference Details: 23nd IET Irish Signals and Systems Conference, Maynooth, Ireland, 28-29th June, 2012
Appears in Collections:Computer Science Research Collection

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