Abstract
We present results on the performance of a stochastic local search algorithm for the design of DNA codes, namely sets of equallength words over the nucleotides alphabet A,C,G, T that satisfy certain combinatorial constraints. Using empirical analysis of the algorithm, we gain insight on goodd esign principles. We report several cases in which our algorithm finds word sets that match or exceed the best previously known constructions.1
This material is basedup on work supportedb y the U.S. National Science Foundation under Grant No. 0130108, by the National Sciences and the Engineering Research Council of Canada.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Galina T. Bogdanova, Andries E. Brouwer, Stoian N. Kapralov & Patric R. J. Ostergard, Error-Correcting Codes over an Alphabet of Four Elements, Andries Brouwer (aeb@cwi.nl)
A. Ben-Dor, R. Karp, B. Schwikowski, and Z. Yakhini, “Universal DNA tag systems: a combinatorial design scheme,” Proc. RECOMB 2000, ACM, pages 65–75.
R.S. Braich, C. Johnson, P.W.K. Rothemund, D. Hwang, N. Chelyapov, and L.M. Adleman, “Solution of a satisfiability problem on a gel-based DNA computer,” Preliminary Proc. Sixth International Meeting on DNA BasedComputers, Leiden, The Netherlands, June, 2000.
S. Brenner and R. A. Lerner, “Encoded combinatorial chemistry,” Proc. Natl. Acad. Sci. USA, Vol 89, pages 5381–5383, June 1992.
R. Deaton, R. C. Murphy, M. Garzon, D. R. Franceschetti, and S. E. Stevens, Jr., “Gooden codings for DNA-based solutions to combinatorial problems,” Proc. DNA Based Computers II, DIMACS Workshop June 10–12, 1996, L. F. Landweber and E. B. Baum, Editors, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol. 44, 1999, pages 247–258.
R. Deaton, M. Garzon, R. C. Murphy, J. A. Rose, D. R. Franceschetti, and S. E. Stevens, Jr., “Genetic search of reliable encodings for DNA-based computation,” Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors), Proceedings of the First Annual Conference on Genetic Programming 1996.
A. A. El Gamal, L. A. Hemachandra, I. Shperling, and V. K. Wei, “Using simulated annealing to design good codes,” IEEE Transactions on Information Theory, Vol. IT–33, No. 1, January 1987.
Faulhammer, D., Cukras, A. R., Lipton, R.J., and L. F. Landweber, “Molecular computation: RNA solutions to chess problems,” Proc. Natl. Acad. Sci. USA, 97: 1385–1389.
U. Feldkamp, W. Banzhaf, H. Rauhe, “A DNA sequence compiler,” Poster presentedat the 6th International Meeting on DNA Based Computers, Leiden, June, 2000. See also http://ls11-www.cs.unidortmund.de/molcomp/Publications/publications.html (visited November 11, 2000).
A. G. Frutos, Q. Liu, A. J. Thiel, A. M. W. Sanner, A. E. Cond on, L. M. Smith, and R. M. Corn, “Demonstration of a word design strategy for DNA computing on surfaces,” Nucleic Acids Research, Vol. 25, No. 23, December 1997, pages 4748–4757.
M. Garzon, R. J. Deaton, J. A. Rose, and D. R. Franceschetti, “Soft molecular computing,” Preliminary Proc. Fifth International Meeting on DNA BasedComputers, June 14–15, MIT, 1999, pages 89–98.
A.J. Hartemink, D.K. Gifford, and J. Khodor, “Automated constraint-based nucleotide sequence selection for DNA computation,” 4th Annual DIMACSWorkshop on DNA-BasedCom puters, Philadelphia, Pennsylvania, June 1998
Holger H. Hoos, Stochastic Local Search-Methods, Models, Applications, infix-Verlag, Sankt Augustin, Germany, ISBN 3-89601-215-0, 1999.
H.H. Hoos and C. Boutilier, “Solving combinatorial auctions using stochastic local search,” In Proceedings of the Seventeenth National Conference on Artificial Intelligence, pages 22–29, Austin, TX, 2000.
H.H. Hoos and T. Stützle, “Evaluating Las Vegas Algorithms — Pitfalls and Remedies,” In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), 1998, pages 238–245.
M. Li, H-J. Lee, A. E. Condon, and R. M. Corn, “DNA Word Design Strategy for Creating Sets of Non-interacting Oligonucleotides for DNA Microarrays,” Langmuir, 18, 2002, pages 805–812.
A. Marathe, A. Condon, and R. Corn, “On combinatorial DNA word design,” J. Computational Biology, 8:3, 2001, 201–220.
D. McAllester, H. Kautz, and B. Selman, “Evidence for invariants in local search,” Proc. AAAI-97, 321–326, Providence, RI, 1997.
J. A. Rose, R. Deaton, D. R. Franceschetti, M. Garzon, and S. E. Stevens, Jr., “A statistical mechanical treatment of error in the annealing biostep of DNA computation,” Special program in DNA andM olecular Computing at the Genetic and Evolutionary Computation Conference (GECCO-99), Orlando, FL., July 13–17, 1999, Morgan Kaufmann.
H. Yoshida and A. Suyama, “Solution to 3-SAT by breadth first search,” Proc. 5th Intl. Meeting on DNA Based Computers, M.I.T. 1999, pages 9–20.
B-T. Zhang and S-Y. Shin, “Molecular algorithms for efficient and reliable DNA computing,” Proc. 3rdA nnual Genetic Programming Conference, Edited by J. R. Koza, K. Deb, M. Doringo, D.B. Fogel, M. Garzon, H. Iba, and R. L. Riolo, Morgan Kaufmann, 1998, pages 735–742.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tulpan, D.C., Hoos, H.H., Condon, A.E. (2003). Stochastic Local Search Algorithms for DNA Word Design. In: Hagiya, M., Ohuchi, A. (eds) DNA Computing. DNA 2002. Lecture Notes in Computer Science, vol 2568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36440-4_20
Download citation
DOI: https://doi.org/10.1007/3-540-36440-4_20
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00531-5
Online ISBN: 978-3-540-36440-5
eBook Packages: Springer Book Archive