Skip to main content

Combining Randomness and a High-Capacity DNA Memory

  • Conference paper
DNA Computing (DNA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4848))

Included in the following conference series:

Abstract

In molecular computing, it has long been a central focus to realize robust computational processes by suppressing the randomness of molecular reactions. To this end, several methods have been developed to control hybridization reactions of DNA molecules by optimizing DNA sequences and reaction parameters. However, another direction in the field is to take advantage of molecular randomness rather than avoid it. In this paper, we show that randomness can be useful in combination with a huge-capacity molecular memory, and demonstrate its application to an existing technology — DNA ink.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Leonard, M.: Adleman: Molecular Computation of Solutions to Combinatorial Problems. Science 266, 1021–1024 (1994)

    Article  Google Scholar 

  2. Braich, R.S., Chelyapov, N., Johnson, C., Rothemund, P.W.K., Adleman, L.: Solution to a 20-Variable 3-SAT Problem on a DNA Computer. Science 296, 499–502 (2002)

    Article  Google Scholar 

  3. Fujibayashi, K., Murata, S.: A Method of Error Suppression for Self-assembling DNA Tiles. In: Ferretti, C., Mauri, G., Zandron, C. (eds.) DNA Computing. LNCS, vol. 3384, pp. 113–127. Springer, Heidelberg (2005)

    Google Scholar 

  4. Gotoh, O., Sakai, Y., Mawatari, Y., Gunji, W., Murakami, Y., Suyama, A.: Normalized molecular encoding method for quantitative gene expression profiling. In: Carbone, A., Pierce, N.A. (eds.) DNA Computing. LNCS, vol. 3892, p. 395. Springer, Heidelberg (2006)

    Google Scholar 

  5. Itakura, Y., Hashiyada, M., Nagashima, T., Fukuyama, M.: Validation Experiment Report on DNA Information for Personal Identification (Part I). Technical Report of IEICE ISEC2001-12 (2001-05), The Institute of Electronics, Information and Communication Engineers, pp. 1–8 (2001) (in Japanese)

    Google Scholar 

  6. Itakura, Y., Hashiyada, M., Nagashima, T., Tsuji, S.: Validation Experiment Report on DNA Information for Personal Identification (Part II). Technical Report of IEICE ISEC2001-13 (2001-05), The Institute of Electronics, Information and Communication Engineers , 9–16 (2001) (in Japanese)

    Google Scholar 

  7. Kashiwamura, S., Yamamoto, M., Kameda, A., Shiba, T., Ohuchi, A.: Hierarchical DNA Memory Based on Nested PCR. In: Hagiya, M., Ohuchi, A. (eds.) DNA Computing. LNCS, vol. 2568, pp. 112–123. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  8. Kashiwamura, S., Kameda, A., Yamamoto, M., Ohuchi, A.: Two-Step Search for DNA Sequence Design. IEICE E87-A(6), 1446–1453 (2004)

    Google Scholar 

  9. Kashiwamura, S., Yamamoto, M., Kameda, A., Shiba, T., Ohuchi, A.: Potential for Enlarging DNA Memory: The Validity of Experimental Operations of Scaled-up Nested Primer Molecular Memory. BioSystems 80, 99–112 (2005)

    Article  Google Scholar 

  10. Kubota, M., Hagiya, M.: Minimum Basin Algorithm: An Effective Analysis Technique for DNA Energy Landscapes. In: Ferretti, C., Mauri, G., Zandron, C. (eds.) DNA Computing. LNCS, vol. 3384, pp. 202–214. Springer, Heidelberg (2005)

    Google Scholar 

  11. Nitta, N., Suyama, A.: Autonomous biomolecular computer modeled after retroviral replication. In: Chen, J., Reif, J.H. (eds.) DNA Computing. LNCS, vol. 2943, pp. 203–212. Springer, Heidelberg (2004)

    Google Scholar 

  12. Soloveichik, D., Winfree, E.: Complexity of Compact Proofreading for Self-assembled Patterns. In: Carbone, A., Pierce, N.A. (eds.) DNA Computing. LNCS, vol. 3892, pp. 305–324. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Suyama, A.: Programmable DNA computer with application to mathematical and biological problems. Preliminary Proceedings of the Eighth International Meeting on DNA Based Computers, 91 (2002)

    Google Scholar 

  14. Takahashi, K., Yaegashi, S., Asanuma, H., Hagiya, M.: Photo- and Thermoregulation of DNA Nanomachines. In: Carbone, A., Pierce, N.A. (eds.) DNA Computing. LNCS, vol. 3892, pp. 336–346. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  15. Yamamoto, M., Kashiwamura, S., Ohuchi, A.: DNA Memory with 16.8M addresses. DNA13 (submitted 2007)

    Google Scholar 

  16. Yurke, B., Turberfield, A.J., Mills Jr., A.P., Simmel, F.C., Neumann, J.L.: A DNA-fuelled molecular machine made of DNA. Nature 406, 605–608 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Max H. Garzon Hao Yan

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kameda, A., Kashiwamura, S., Yamamoto, M., Ohuchi, A., Hagiya, M. (2008). Combining Randomness and a High-Capacity DNA Memory. In: Garzon, M.H., Yan, H. (eds) DNA Computing. DNA 2007. Lecture Notes in Computer Science, vol 4848. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77962-9_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77962-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77961-2

  • Online ISBN: 978-3-540-77962-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics