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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/114937...
Part of book or chapter of book . 2005 . Peer-reviewed
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DBLP
Conference object . 2017
Data sources: DBLP
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A Weighted Insertion-Deletion Stacked Pair Thermodynamic Metric for DNA Codes

Authors: Arkadii G. D'yachkov; Anthony J. Macula; Wendy K. Pogozelski; Thomas E. Renz; Vyacheslav V. Rykov; David C. Torney;

A Weighted Insertion-Deletion Stacked Pair Thermodynamic Metric for DNA Codes

Abstract

Thermodynamic distance functions are important components in the construction of DNA codes and DNA codewords are structural and information building blocks in biomolecular computing and other biotechnical applications that employ DNA hybridization assays. We introduce new metrics for DNA code design that capture key aspects of the nearest neighbor thermodynamic model for hybridized DNA duplexes. One version of our metric gives the maximum number of stacked pairs of hydrogen bonded nucleotide base pairs that can be present in any secondary structure in a hybridized DNA duplex without pseudoknots. We introduce the concept of (t-gap) block isomorphic subsequences to describe new string metrics that are similar to the weighted Levenshtein insertion-deletion metric. We show how our new distances can be calculated by a generalization of the folklore longest common subsequence dynamic programming algorithm. We give a Varshamov-Gilbert like lower bound on the size of some of codes using our distance functions as constraints. We also discuss software implementation of our DNA code design methods.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Top 10%
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