Skip to main content
SpringerLink
Log in

Emerging Models of Computation: Directions in Molecular Computing

Position Paper for InterLink Workshop, May 2007

  • Chapter
Software-Intensive Systems and New Computing Paradigms

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5380))

Abstract

Computing as we have known it for 60 years is based on the von Neumann stored-program concept and its ubiquitous implementation in the form of electronic instruction processors. For the past four decades, processors have been fabricated using semiconductor integrated circuits, the dominant material being silicon, and the dominant technology CMOS. Relentless miniaturization has been decreasing feature size and increasing both the operating frequency and the number of elements per chip, giving rise to so-called Moore’s law (which we interpret broadly to mean the expectation of an exponential improvement in salient performance parameters).

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

Access this chapter

Log in via an institution
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. Ganusov, I., Burtscher, M.: Future execution: A prefetching mechanism that uses multiple cores to speed up single threads. ACM Transactions on Architecture and Code Optimization 3(4), 424–449 (2006)

    Article  Google Scholar 

  2. Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight Jr., T.F., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous computing. Communications of the ACM 43(5), 74–82 (2000)

    Article  Google Scholar 

  3. Goldstein, S.C., Rosewater, D.: Digital logic using molecular electronics. In: IEEE International Solid-State Circuits Conference, San Francisco, CA, p. 12.5 (February 2002)

    Google Scholar 

  4. Gruau, F., Lhuillier, Y., Reitz, P., Temam, O.: Blob computing. In: Computing Frontiers 2004 ACM SIGMicro (June 2004)

    Google Scholar 

  5. Adleman, L.M.: Molecular computation of solutions to combinatorial problems. Science 266(5187), 1021–1024 (1994)

    Article  Google Scholar 

  6. Deaton, R.J., Garzon, M., Rose, J.A., Franceschetti, D.R., Stevens Jr., S.E.: DNA computing: A review. Fundamenta Informaticae 35(1-4), 231–245 (1998)

    MathSciNet  MATH  Google Scholar 

  7. Lipton, R.J.: DNA solution of hard computational problems. Science 268, 542–545 (1995)

    Article  Google Scholar 

  8. Ruben, A.J., Landweber, L.F.: Timeline: The past, present and future of molecular computing. Nature Reviews Molecular Cell Biology 1, 69–72 (2000)

    Article  Google Scholar 

  9. Wang, L., Liu, Q., Corn, R.M., Condon, A.E., Smith, L.M.: Multiple word DNA computing on surfaces. Journal of the American Chemical Society 122(31), 7435–7440 (2000)

    Article  Google Scholar 

  10. Winfree, E.: On the computational power of DNA annealing and ligation. In: Lipton, Baum (eds.) [93], pp. 199–221

    Google Scholar 

  11. Winfree, E.: Complexity of restricted and unrestricted models of molecular computation. In: Lipton, Baum (eds.) [93], pp. 187–198

    Google Scholar 

  12. Watson, J.D., Crick, F.H.C.: A structure for deoxyribose nucleic acid. Nature 171, 737 (1953)

    Article  Google Scholar 

  13. LaBean, T.H., Yan, H., Kopatsch, J., Liu, F., Winfree, E., Reif, J.H., Seeman, N.C.: Construction, analysis, ligation, and self-assembly of DNA triple crossover complexes. Journal of the American Chemical Society 122, 1848–1860 (2000)

    Article  Google Scholar 

  14. Watson, J.D., Hopkins, N.H., Roberts, J.W., Steitz, J.A., Weiner, A.M.: Molecular Biology of the Gene, 4th edn., Benjamin/Cummings, Menlo Park, CA (1988)

    Google Scholar 

  15. Winfree, E., Liu, F., Wenzler, L.A., Seeman, N.C.: Design and self-assembly of two-dimensional DNA crystals. Nature 394, 539–544 (1998)

    Article  Google Scholar 

  16. Wang, L., Hall, J.G., Lu, M., Liu, Q., Smith, L.M.: A DNA computing readout operation based on structure-specific cleavage. Nature Biotechnology 19, 1053–1059 (2001)

    Article  Google Scholar 

  17. Braich, R.S., Chelyapov, N., Johnson, C., Rothemund, P.W.K., Adleman, L.: Solution of a 20-variable 3-SAT problem on a DNA computer. Science 296, 499–502 (2002)

    Article  Google Scholar 

  18. Morimoto, N., Arita, M., Suyama, A.: Solid phase DNA solution to the Hamiltonian path problem. In: Rubin, Wood (eds.) [92], pp. 193–206

    Google Scholar 

  19. Ouyang, Q., Kaplan, P.D., Liu, S., Libchaber, A.: DNA solution of the maximal clique problem. Science 278, 446–449 (1997)

    Article  Google Scholar 

  20. Pirrung, M.C., Connors, R.V., Odenbaugh, A.L., Montague-Smith, M.P., Walcott, N.G., Tollett, J.J.: The arrayed primer extension method for DNA microchip analysis. Molecular computation of satisfaction problems. Journal of the American Chemical Society 122, 1873–1882 (2000)

    Article  Google Scholar 

  21. Garzon, M., Gao, Y., Rose, J.A., Murphy, R.C., Deaton, R.J., Franceschetti, D.R., Stevens Jr., S.E.: In vitro implementation of finite-state machines. In: Wood, D., Yu, S. (eds.) WIA 1997. LNCS, vol. 1436, pp. 56–74. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  22. Guarnieri, F., Fliss, M., Bancroft, C.: Making DNA add. Science 273, 220–223 (1996)

    Article  Google Scholar 

  23. Hug, H., Schuler, R.: DNA-based parallel computation of simple arithmetic. In: Jonoska, N., Seeman, N.C. (eds.) DNA 2001. LNCS, vol. 2340. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  24. Mao, C., LaBean, T.H., Reif, J.H., Seeman, N.C.: Logical computation using algorithmic self-assembly of DNA triple-crossover molecules. Nature 407, 493–496 (2000); Erratum. Nature 408, 750 (2000)

    Article  Google Scholar 

  25. Rothemund, P.W.K., Winfree, E.: The program-size complexity of self-assembled squares. In: STOC 2000: The Thirty-Second Annual ACM Symposium on Theory of Computing (May 2000)

    Google Scholar 

  26. Faulhammer, D., Cukras, A.R., Lipton, R.J., Landweber, L.F.: Molecular computation: RNA solutions to chess problems. Proceedings of the National Academy of Sciences of the USA (PNAS) 97(4), 1385–1389 (2000), http://www.pnas.org/cgi/content/full/97/4/1385/DC1

    Article  Google Scholar 

  27. Hartmanis, J.: On the weight of computation. Bulletin of the EATCS 55, 136–138 (1995)

    MATH  Google Scholar 

  28. Hug, H., Schuler, R.: Strategies for the development of a peptide computer. Bioinformatics 17(4), 364–368 (2001)

    Article  Google Scholar 

  29. Winfree, E.: Simulations of computing by self-assembly. In: Kari, L., Rubin, H., Wood, D.H. (eds.) DNA Based Computers IV, DIMACS Workshop 1998 (University of Pennsylvania: Philadelphia, PA, Biosystems, vol. 52(1-3), pp. 213–242. Elsevier, Amsterdam (1998)

    Google Scholar 

  30. Rothemund, P.W.K.: Folding DNA to create nanoscale shapes and patterns. Nature 440, 297–302 (2006)

    Article  Google Scholar 

  31. Basu, S., Karig, D., Weiss, R.: Engineering signal processing in cells: Towards molecular concentration band detection. In: Hagiya, M., Ohuchi, A. (eds.) DNA 2002. LNCS, vol. 2568. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  32. Conrad, M.: On design principles for a molecular computer. Communications of the ACM 28(3), 464–480 (1985)

    Article  Google Scholar 

  33. Guet, C.C., Elowitz, M.B., Wang, W., Leibler, S.: Combinatorial synthesis of genetic networks. Science 296, 1466–1470 (2002)

    Article  Google Scholar 

  34. Hayes, B.: Computing comes to life. American Scientist 89, 204–208 (2001)

    Article  Google Scholar 

  35. Ji, S.: The cell as the smallest DNA-based molecular computer. BioSystems 52, 123–133 (1999)

    Article  Google Scholar 

  36. Knight Jr., T.F., Sussman, G.J.: Cellular gate technology. In: Proceedings UMC 1998, First International Conference on Unconventional Models of Computation (1998)

    Google Scholar 

  37. LaBean, T.H., Winfree, E., Reif, J.H.: Experimental progress in computation by self-assembly of DNA tilings. In: Winfree, E., Gifford, D.K. (eds.) DNA Based Computers V, DIMACS Workshop 1999 (MIT: Cambridge, MA). Series in Discrete Mathematics and Theoretical Computer Science, vol. 54, pp. 123–140. American Mathematical Society (2000)

    Google Scholar 

  38. Landweber, L.F., Kari, L.: The evolution of cellular computing: nature’s solution to a computational problem. BioSystems 52(1–3), 3–13 (1999)

    Article  Google Scholar 

  39. Landweber, L.F., Kuo, T.-C., Curtis, E.A.: Evolution and assembly of an extremely scrambled gene. Proceedings of the National Academy of Sciences of the USA 97(7), 3298–3303 (2000)

    Article  Google Scholar 

  40. Reif, J.H.: Parallel biomolecular computation. In: Rubin, Wood (eds.) [92], pp. 217–254

    Google Scholar 

  41. Saylor, G.: Construction of genetic logic gates for biocomputing. In: 101st General Meeting of the American Society for Microbiology (2001)

    Google Scholar 

  42. Weiss, R.: Cellular Computation and Communication using Engineered Genetic Regulatory Networks. PhD thesis, Massachusetts Institute of Technology (September 2001)

    Google Scholar 

  43. Weiss, R., Basu, S.: The device physics of cellular logic gates. In: First Workshop on Non-Silicon Computing (February 2002)

    Google Scholar 

  44. Weiss, R., Homsy, G., Nagpal, R.: Programming biological cells. Technical report, MIT Laboratory for Computer Science and Artificial Intelligence (1998)

    Google Scholar 

  45. Weiss, R., Homsy, G.E., Knight Jr., T.F.: Towards in vivo digital circuits. In: DIMACS Workshop on Evolution as Computation (January 1999)

    Google Scholar 

  46. Winfree, E., Yang, X., Seeman, N.C.: Universal computation via self-assembly of DNA: Some theory and experiments. In: Landweber, L.F., Baum, E.B. (eds.) DNA Based Computers II, DIMACS Workshop 1996 (Princeton University: Princeton, NJ). Series in Discrete Mathematics and Theoretical Computer Science, vol. 44, pp. 191–213. American Mathematical Society (1999), http://www.dna.caltech.edu/Papers/self-assem.errata

  47. Patwardhan, J., Johri, V., Dwyer, C., Lebeck, A.R.: A defect tolerant self-organizing nanoscale simd architecture. In: Proceedings of the Twelth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS XII (2006)

    Google Scholar 

  48. Cox, J.C., Ellington, A.D.: DNA computation function. Current Biology 11(9), R336 (2001)

    Article  Google Scholar 

  49. Yurke, B., Mills Jr., A.P., Cheng, S.L.: DNA implementation of addition in which the input strands are separate from the operator strands. BioSystems 52(1–3), 165–174 (1999)

    Article  Google Scholar 

  50. Stojanovic, M.N., de Prada, P., Landry, D.W.: Catalytic molecular beacons. Chem. Bio. Chem. 2(6), 411–415 (2001)

    Article  Google Scholar 

  51. Stojanovic, M.N., Mitchell, T.E., Stefanovic, D.: Deoxyribozyme-based logic gates. Journal of the American Chemical Society 124(14), 3555–3561 (2002)

    Article  Google Scholar 

  52. Stojanovic, M.N., Kolpashchikov, D.: Modular aptameric sensors. Journal of the American Chemical Society 126(30), 9266–9270 (2004)

    Article  Google Scholar 

  53. Stojanovic, M.N., Semova, S., Kolpashchikov, D., Morgan, C., Stefanovic, D.: Deoxyribozyme-based ligase logic gates and their initial circuits. Journal of the American Chemical Society 127(19), 6914–6915 (2005)

    Article  Google Scholar 

  54. Stojanovic, M.N., Stefanovic, D.: Deoxyribozyme-based half adder. Journal of the American Chemical Society 125(22), 6673–6676 (2003)

    Article  Google Scholar 

  55. Stojanovic, M.N., Stefanovic, D.: A deoxyribozyme-based molecular automaton. Nature Biotechnology 21(9), 1069–1074 (2003)

    Article  Google Scholar 

  56. Macdonald, J., Li, Y., Sutovic, M., Lederman, H., Pendri, K., Lu, W., Andrews, B.L., Stefanovic, D., Stojanovic, M.N.: Medium scale integration of molecular logic gates in an automaton. Nano Letters 6(11), 2598–2603 (2006)

    Article  Google Scholar 

  57. Andrews, B.: Games, strategies, and boolean formula manipulation. Master’s thesis, University of New Mexico (December 2005)

    Google Scholar 

  58. Epstein, I.R., Pojman, J.A.: An Introduction to Nonlinear Chemical Dynamics. Oxford University Press, New York (1998)

    Google Scholar 

  59. Field, R.J., Körös, E., Noyes, R.: Oscillations in chemical systems. II. Thorough analysis of temporal oscillation in the bromate-cerium-malonic acid system. Journal of the American Chemical Society 94, 8649–8664 (1972)

    Article  Google Scholar 

  60. Noyes, R., Field, R.J., Körös, E.: Oscillations in chemical systems. I. Detailed mechanism in a system showing temporal oscillations. Journal of the American Chemical Society 94, 1394–1395 (1972)

    Article  Google Scholar 

  61. Tyson, J.J.: The Belousov-Zhabotinskii Reaction. Lecture Notes in Biomathematics, vol. 10. Springer, Berlin (1976)

    MATH  Google Scholar 

  62. Hjelmfelt, A., Ross, J.: Chemical implementation and thermodynamics of collective neural networks. Proceedings of the National Academy of Sciences of the USA 89(1), 388–391 (1992)

    Article  Google Scholar 

  63. Hjelmfelt, A., Ross, J.: Pattern recognition, chaos, and multiplicity in neural networks of excitable systems. Proceedings of the National Academy of Sciences of the USA 91(1), 63–67 (1994)

    Article  Google Scholar 

  64. Hjelmfelt, A., Schneider, F.W., Ross, J.: Pattern recognition in coupled chemical kinetic systems. Science 260, 335–337 (1993)

    Article  Google Scholar 

  65. Hjelmfelt, A., Weinberger, E.D., Ross, J.: Chemical implementation of neural networks and Turing machines. Proceedings of the National Academy of Sciences of the USA 88(24), 10983–10987 (1991)

    Article  MATH  Google Scholar 

  66. Hjelmfelt, A., Weinberger, E.D., Ross, J.: Chemical implementation of finite-state machines. Proceedings of the National Academy of Sciences of the USA 89(1), 383–387 (1992)

    Article  Google Scholar 

  67. Laplante, J.-P., Pemberton, M., Hjelmfelt, A., Ross, J.: Experiments on pattern recognition by chemical kinetics. The Journal of Physical Chemistry 99(25), 10063–10065 (1995)

    Article  Google Scholar 

  68. Rössler, O.E., Seelig, F.F.: A Rashevsky-Turing system as a two-cellular flip-flop. Zeitschrift für Naturforschung 27b, 1444–1448 (1972)

    Google Scholar 

  69. Seelig, F.F., Rössler, O.E.: Model of a chemical reaction flip-flop with one unique switching input. Zeitschrift für Naturforschung 27b, 1441–1444 (1972)

    Google Scholar 

  70. Szilard, L.: Über die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift für Physik 53, 840–856 (1929)

    Article  MATH  Google Scholar 

  71. Matías, M.A., Güémez, J.: On the effects of molecular fluctuations on models of chemical chaos. Journal of Chemical Physics 102(4), 1597–1606 (1995)

    Article  Google Scholar 

  72. Moore, C.: Unpredictability and undecidability in dynamical systems. Physical Review Letters 64(20), 2354–2357 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  73. Wolfram, S.: Undecidability and intractability in theoretical physics. Physical Review Letters 54(8), 735–738 (1985)

    Article  MathSciNet  Google Scholar 

  74. Winfree, A.T.: Spiral waves of chemical activity. Science 175, 634–635 (1972)

    Article  Google Scholar 

  75. Steinbock, O., Kettunen, P., Showalter, K.: Chemical wave logic gates. Journal of Physical Chemistry 100, 18970–18975 (1996)

    Article  Google Scholar 

  76. Yurke, B., Turberfield, A.J., Mills Jr., A.P., Neumann, J.L.: A molecular machine made of and powered by DNA. In: The 2000 March Meeting of the American Physical Society (March 2000)

    Google Scholar 

  77. Magnasco, M.O.: Molecular combustion motors. Physical Review Letters 72(16), 2656–2659 (1994)

    Article  Google Scholar 

  78. Magnasco, M.O.: Chemical kinetics is Turing universal. Physical Review Letters 78(6), 1190–1193 (1997)

    Article  Google Scholar 

  79. Homsy, G.E.: Performance limits on biochemical computation. Technical report, MIT Artificial Intelligence Laboratory (2000)

    Google Scholar 

  80. Hiratsuka, M., Aoki, T., Higuchi, T.: Enzyme transistor circuits for reaction-diffusion computing. IEEE Transactions on Circuits and systems—I: Fundamental Theory and Applications 46(2), 294–303 (1999)

    Article  Google Scholar 

  81. Hiratsuka, M., Aoki, T., Morimitsu, H., Higuchi, T.: Implementation of reaction-diffusion cellular automata. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 49(1), 10–16 (2002)

    Article  Google Scholar 

  82. Morgan, C., Stefanovic, D., Moore, C., Stojanovic, M.N.: Building the components for a biomolecular computer. In: Ferretti, C., Mauri, G., Zandron, C. (eds.) Preliminary Proceedings of the 10th International Workshop on DNA-Based Computers, DNA 2004. University of Milano-Bicocca, Milan (2004)

    Google Scholar 

  83. Farfel, J., Stefanovic, D.: Towards practical biomolecular computers using microfluidic deoxyribozyme logic gate networks. In: Carbone, A., Daley, M., Kari, L., McQuillan, I., Pierce, N. (eds.) Preliminary Proceedings of the 11th International Workshop on DNA-Based Computers, DNA 2005, pp. 221–232. University of Western Ontario, London (2005)

    Google Scholar 

  84. Alberts, B., Bray, D., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P.: Essential Cell Biology: An Introduction to the Molecular Biology of the Cell. Garland, New York (1998)

    Google Scholar 

  85. Arkin, A., Ross, J.: Computational functions in biochemical reaction networks. Biophysical Journal 67(2), 560–578 (1994)

    Article  Google Scholar 

  86. Goldbeter, A.: Biochemical Oscillations and Cellular Rhythms: The molecular bases of periodic and chaotic behaviour. Cambridge University Press, Cambridge (1996)

    Book  MATH  Google Scholar 

  87. Okamoto, M., Hayashi, K.: Dynamic behavior of cyclic enzyme systems. Journal of Theoretical Biology 104, 591–598 (1983)

    Article  Google Scholar 

  88. Okamoto, M., Sakai, T., Hayashi, K.: Switching mechanism of a cyclic enzyme system: Role as a “chemical diode”. BioSystems 21(1), 1–11 (1987)

    Article  Google Scholar 

  89. Sugita, M.: Functional analysis of chemical systems in vivo using a logical circuit equivalent. II. The idea of a molecular automaton. Journal of Theoretical Biology 4, 179–192 (1963)

    Article  Google Scholar 

  90. Fukuda, N., Sugita, M.: Mathematical analysis of metabolism using an analogue computer: I. Isotope kinetics of iodine metabolism in the thyroid gland. Journal of Theoretical Biology 1, 440–459 (1961)

    Google Scholar 

  91. Pei, R., Taylor, S.K., Stefanovic, D., Rudchenko, S., Mitchell, T.E., Stojanovic, M.N.: Behavior of polycatalytic assemblies in a substrate-displaying matrix. Journal of the American Chemical Society 128(39), 12693–12699 (2006)

    Article  Google Scholar 

  92. Rubin, H., Wood, D.H. (eds.): DNA Based Computers III, DIMACS Workshop 1997 (University of Pennsylvania: Philadelphia, PA). Series in Discrete Mathematics and Theoretical Computer Science, vol. 48. American Mathematical Society (1999)

    Google Scholar 

  93. Lipton, R.J., Baum, E.B.: DNA Based Computers, DIMACS Workshop 1995 (Princeton University: Princeton, NJ). Series in Discrete Mathematics and Theoretical Computer Science, vol. 27. American Mathematical Society (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of New Mexico, USA

    Darko Stefanovic

Authors
  1. Darko Stefanovic
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computer Science, LMU Munich, Munich, Germany

    Martin Wirsing  & Axel Rauschmayer  & 

  2. Université de Rennes I and INRIA/IRISA, Campus de Beaulieu, 35042, Rennes Cedex, France

    Jean-Pierre Banâtre

  3. Ludwig-Maximilians-Universität München, Germany

    Matthias Hölzl

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Stefanovic, D. (2008). Emerging Models of Computation: Directions in Molecular Computing . In: Wirsing, M., Banâtre, JP., Hölzl, M., Rauschmayer, A. (eds) Software-Intensive Systems and New Computing Paradigms. Lecture Notes in Computer Science, vol 5380. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89437-7_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89437-7_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89436-0

  • Online ISBN: 978-3-540-89437-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation