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Journal of Computational Biology
New t-Gap Insertion-Deletion-Like Metrics for DNA Hybridization Thermodynamic Modeling

To cite this article:
Arkadii G. D'yachkov, Anthony J. Macula, Wendy K. Pogozelski, Thomas E. Renz, Vyacheslav V. Rykov, David C. Torney. Journal of Computational Biology. May 2006, 13(4): 866-881. doi:10.1089/cmb.2006.13.866.

Published in Volume: 13 Issue 4: June 8, 2006

Full Text: • PDF for printing (142.6 KB) • PDF w/ links (175.9 KB)


Arkadii G. D'yachkov
Dept. of Probability Theory, Moscow State University, Moscow 119899, Russia.
Anthony J. Macula
Air Force Research Lab, IFTC, Rome Research Site, Rome NY 13441.
Wendy K. Pogozelski
Department of Chemistry, SUNY Geneseo, Geneseo, NY 14454.
Thomas E. Renz
Air Force Research Lab, IFTC, Rome Research Site, Rome NY 13441.
Vyacheslav V. Rykov
Dept. of Mathematics, University of Nebraska-Omaha, Omaha, NE 68182.
David C. Torney
Theoretical Biology and Biophys., Los Alamos Natl. Lab, Los Alamos, NM 87545.

We discuss the concept of t-gap block isomorphic subsequences and use it to describe new abstract string metrics that are similar to the Levenshtein insertion–deletion metric. Some of the metrics that we define can be used to model a thermodynamic distance function on single-stranded DNA sequences. Our model captures a key aspect 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. Thermodynamic distance functions are important components in the construction of DNA codes, and DNA codes are important components in biomolecular computing, nanotechnology, and other biotechnical applications that employ DNA hybridization assays. We show how our new distances can be calculated by using a dynamic programming method, and we derive a Varshamov–Gilbert–like lower bound on the size of some of codes using these distance functions as constraints. We also discuss software implementation of our DNA code design methods.

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