BUILDING A PARALLEL DECISION-MAKING SYSTEM BASED ON RULE-BASED CLASSIFIERS IN MOLECULAR ROBOTICS

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 8 , ISSUE 2 (June 2015) > List of articles

BUILDING A PARALLEL DECISION-MAKING SYSTEM BASED ON RULE-BASED CLASSIFIERS IN MOLECULAR ROBOTICS

Wibowo Adi * / Kosuke Sekiyama

Keywords : Molecular robotics, DNA strand displacement, Rule-based classifiers, Binary tree classification.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 2, Pages 944-965, DOI: https://doi.org/10.21307/ijssis-2017-790

License : (CC BY-NC-ND 4.0)

Received Date : 20-February-2015 / Accepted: 27-March-2015 / Published Online: 01-June-2015

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ABSTRACT

Controlled drug delivery based on cellular components can be achieved by exploiting disease-specific properties, but these require a rapid, sensitive, and selective method of detection in a biomolecular system. We propose a parallel decision-making system for disease detection and classification based on the fact that DNA computing along with biomolecular systems can be subjected to massively parallel processing. We designed and programmed a DNA strand displacement reaction to implement rule-based classifiers from a binary tree classification as a decision-making system. In our framework for molecular robot development, the system components of molecular robots and simple classifier rules were used to alleviate the computational burden. The design consists of a basic model that generates rule-based classifier gates in several binary tree and cancer classifications based on micro (mi)RNA expression. Simulation results showed that detection and classification were rapid using this system. Moreover, experiments using the synthetic miRNA hsa-miR-21 demonstrated that our model could be a feasible decision-making system for drug delivery.

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REFERENCES

[1] C. Kaparissides, S. Alexandridou, K. Kotti, and S. Chaitidou, “Recent advances in novel drug delivery systems”. Journal of Nanotechnology, vol. 2, pp. 1–11, March 2006.
[2] M. Kumar, T. Ahmad, A. Sharma, U. Mabalirajan, A. Kulshreshtha, A. Agrawal, and G. Ghosh, “Let-7 microRNA-mediated regulation of IL-13 and allergic airway inflammation”. Journal of Allergy and Clinical Immunology, vol. 128, no. 5, pp. 1077–1085, November 2011.
[3] T. X. Lu, A. Munitz, and M. E. Rothenberg, “MicroRNA-21 is up-regulated in allergic airway inflammation and regulates IL-12p35 expression”. The Journal of Immunology, vol. 182, no. 8, pp. 4994–5002, April 2009.
[4] T. X. Lu and M. E. Rothenberg, “Diagnostic, functional, and therapeutic roles of micro RNA in allergic diseases”. Journal of Allergy and Clinical Immunology, vol. 132, no. 1, pp. 3–13, July 2013.
[5] X. Chen, Y. Ba, L. Ma, X. Cai, Y. Yin, K. Wang, J. Guo, Y. Zhang, J. Chen, X. Guo, Q. Li, X. Li, W. Wang, Y. Zhang, J. Wang, X. Jiang, Y. Xiang, C. Xu, P. Zheng, J. Zhang, R. Li, H. Zhang, X. Shang, T. Gong, G. Ning, J. Wang, K. Zen, J. Zhang, and C. Y. Zhang, “Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases”. Cell Research, vol. 18, no. 10, pp. 997–1006, October 2008.
[6] C. Mavroidis and A. Ferreira, Nanorobotics: Current Approaches and Techniques, C. Mavroidis and A. Ferreira, eds. Springer, New York, NY, pp. 3, 2013.
[7] A. Ummat, A. Dubey, and C. Mavroidis, “Bionanorobotics: a field inspired by nature,” in Y. Bar-Cohen, ed., Biomimetics: Biologically Inspired Technologies, CRC Press, Boca Raton, FL, pp. 201–227, 2005.
[8] K. Sanderson, “Bioengineering: What to make with DNA origami”. Nature, vol. 464, no. 7286, pp. 158–159, March 2010.
[9] S. Hiyama, Y. Isogawa, T. Suda, Y. Moritani, and K. Sutoh. A design of an autonomous molecule loading/transporting/unloading system using DNA hybridization and biomolecular linear motors. ” in Proc. European Nano Systems’05, pp. 75-80, 2005
[10] M. Hagiya, A. Konagaya, S. Kobayashi, H. Saito, and S. Murata, “Molecular Robots with Sensors and Intelligence”. Accounts of Chemical Research, vol. 47, no. 6, pp. 1681–1690, 2014.
[11] G. Paun, G. Rozenberg, and A. Salomaa, DNA computing: new computing paradigms. G. Paun, G. Rozenberg, A. Salomaa, eds. Springer, New York, NY,pp: 40-65, 1998.
[12] M. N. Win and C. D. Smolke, “Higher-order cellular information processing with synthetic RNA devices”. Science, vol. 322, no. 5900, pp. 456–460, October 2008.
[13] M. Hagiya, S. Wang, I. Kawamata, S. Murata, T. Isokawa, F. Peper, and K. Imai, “On DNA-Based Gellular Automata”, in O. H. Ibarra, L. Kari, and S. Kopecki, eds., Unconventional Computation and Natural Computation, Springer International Publishing, New York, NY, pp. 177–189, 2014.
[14] S. Ayukawa, M. Takinoue, and D. Kiga, “RTRACS: a modularized RNA-dependent RNA transcription system with high programmability”. Accounts of Chemical Research, vol. 44, no. 12, pp. 1369–1379, October 2011.
[15] D. Y. Zhang and G. Seelig, “Dynamic DNA nanotechnology using strand-displacement reactions”. Nature Chemistry, vol. 3, no. 2, pp. 103–113, January 2011.
[16] G. Seelig, D. Soloveichik, D. Y. Zhang, and E. Winfree, “Enzyme-free nucleic acid logic circuits”. Science, vol. 314, no. 5805, pp. 1585–1588, December 2006.
[17] D. Y. Zhang, A. J. Turberfield, B. Yurke, and E. Winfree, “Engineering entropy-driven reactions and networks catalyzed by DNA”. Science, vol. 318, no. 5853, pp. 1121–1125, November 2007.
[18] L. Qian, E. Winfree, and J. Bruck, “Neural network computation with DNA strand displacement cascades”. Nature, vol. 475, no. 7356, pp. 368–372, July 2011.
[19] L. Qian and E. Winfree, “Scaling up digital circuit computation with DNA strand displacement cascades”. Science, vol. 332, no. 6034, pp. 1196–1201, June 2011.
[20] P. N. Tan, M. Steinbach, and V. Kumar. Introduction to data mining. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, Chapter 5.1, pp: 207 – 219, 2005.
[21] N. Rosenfeld, R. Aharonov, E. Meiri, S. Rosenwald, Y. Spector, M. Zepeniuk, H. Benjamin, N. Shabes, S. Tabak, A. Levy, D. Lebanony, Y. Goren, E. Silberschein, N. Targan, A. Ben-Ari, S. Gilad, N. Sion-Vardy, A. Tobar, M. Feinmesser, O. Kharenko, O. Nativ, D. Nass, M. Perelman, A. Yosepovich, B. Shalmon, S. Polak-Charcon, E. Fridman, A. Avniel, I. Bentwich, Z. Bentwich, D. Cohen, A. Chajut, I. Barshack, “MicroRNAs accurately identify cancer tissue origin”. Nature Biotechnology, vol. 26, no. 4, pp. 462–469, April 2008.
[22] N. Kosaka, H. Iguchi, and T. Ochiya, “Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis”. Cancer Science, vol. 101, no. 10, pp. 2087–2092, October 2010.
[23] D. Y. Zhang, “Dynamic DNA strand displacement circuits”. Ph.D. dissertation, California Institute of Technology, 2010.
[24] P. W. Rothemund, “Folding DNA to create nanoscale shapes and patterns”. Nature, vol. 440, no. 7082, pp. 297–302, January 2006.
[25] H. T. Maune, S. P. Han, R. D. Barish, M. Bockrath, W. A. Goddard III, P. W. Rothemund, and E. Winfree, “Self-assembly of carbon nanotubes into two-dimensional geometries using DNA origami templates”. Nature Nanotechnology, vol. 5, no. 1, pp. 61–66, November 2009.
[26] S. M. Douglas, H. Dietz, T. Liedl, B. Högberg, F. Graf, and W. M. Shih, “Self-assembly of DNA into nanoscale three-dimensional shapes”. Nature, vol. 459, no. 7245, pp. 414–418, May 2009.
[27] N. C. Seeman, “An overview of structural DNA nanotechnology”. Molecular Biotechnology, vol. 37, no. 3, pp. 246–257, November 2007.
[28] S. M. Douglas, A. H. Marblestone, S. Teerapittayanon, A. Vazquez, G. M. Church, and W. M. Shih, “Rapid prototyping of 3D DNA-origami shapes with caDNAno”. Nucleic Acids Research, vol. 37, no. 15, pp. 5001–5006, August 2009.
[29] CanDo - Computer-aided engineering for DNA origami, http://cando-dna-origami.org/, final request 19.11.2014.
[30] J. Liu, Z. Cao, and Y. Lu, “Functional nucleic acid sensors”. Chemical Reviews, vol. 109, no. 5, pp. 1948–1998, May 2009.
[31] A. P. De Silva and S. Uchiyama, “Molecular logic and computing,” Nature Nanotechnology, vol. 2, no. 7, pp. 399–410, 2007.
[32] Y. Benenson, “Biomolecular computing systems: principles, progress and potential”. Nature Reviews Genetics, vol. 13, no. 7, pp. 455–468, July 2012.
[33] J. S. Shin and N. A. Pierce, “A synthetic DNA walker for molecular transport”. Journal of the American Chemical Society, vol. 126, no. 35, pp. 10834–10835, September 2004.
[34] H. Qiu, J. C. Dewan, and N. C. Seeman, “A DNA decamer with a sticky end: the crystal structure of d-CGACGATCGT”. Journal of Molecular Biology, vol. 267, no. 4, pp. 881–898, April 1997.
[35] S.H. Cha and C. Tappert, “A genetic algorithm for constructing compact binary decision trees”. Journal of Pattern Recognition Research, vol. 4, no. 1, pp. 1–13, 2009.
[36] J. Han and M. Kamber. Data Mining, Southeast Asia Edition: Concepts and Techniques. Morgan Kaufmann, Burlington, MA,pp: 355-363, 2006.
[37] R. Garnier and J. Taylor, Discrete mathematics: proofs, structures and applications. CRC Press, Boca Raton, FL, 2009.
[38] Y. K. Lin and K. S. Fu, “Automatic classification of cervical cells using a binary tree classifier”. Pattern Recognition, vol. 16, no. 1, 69–80, 1983.
[39] B. Yurke, A. J. Turberfield, A. P. Mills, F. C. Simmel, and J. L. Neumann, “A DNA-fuelled molecular machine made of DNA”. Nature, vol. 406, no. 6796, pp. 605–608, August 2000.
[40] H. Chandran, N. Gopalkrishnan, A. Phillips, and J. Reif, “Localized hybridization circuits,” in L. Cardelli and W. Shih, eds., DNA Computing and Molecular Programming, Springer, Berlin, pp. 64–83, 2011.
[41] M. R. Lakin, S. Youssef, F. Polo, S. Emmott, and A. Phillips, “Visual DSD: a design and analysis tool for DNA strand displacement systems”. Bioinformatics vol. 27, no. 22, pp. 3211–3213, November 2011.
[42] P. P. Medina, M. Nolde, and F. J. Slack, “Oncomir addiction in an in vivo model of microRNA-21-induced pre-B-cell lymphoma”. Nature, vol. 467, no. 7311, pp. 86–90, September 2010.
[43] NUPACK – Nucleic Acid Package. Available: http://www.nupack.org/, final request 19.11.2014.

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