Abstract
This paper’s aim is to show the possibilities of modelling the information content carried by quantum mechanical DNA molecules by means of the formalism used in quantum informatics. Such modelling would open new options to reveal nature’s information patents and to use them, for instance, in quantum computing and artificial intelligence (A.I.). Moreover, it would give an opportunity of understanding the ways of managing information in living organisms. As an empirical base, the open accessible data from GenBank which contains hundreds of millions of long DNA texts collected from thousands of organisms can be used.
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References
Watson, J.D., Crick, F.H.C.: Molecular structure of nucleic acids: a structure for deoxyribose nucleic acid. Nature. Band 171, S. 737–738, 25 (April 1953). https://doi.org/10.1038/171737a0
Stewart, I.: Life’s Other Secret: The New Mathematics of the Living World. Penguin, New York (1999)
Matsuno, K., Paton, R.C.: Is there a biology of quantum information? BioSystems 55, 39–46 (2000)
Karafyllidis, I.G.: Quantum mechanical model for information transfer from DNA to protein. Biosystems 93(3), 191–8 (2008)
Patel, A.: Quantum Algorithms and the Genetic Code. arXiv:quant-ph/0002037 (2001)
Fimmel, E., Danielli, A., Strüngmann, L.: On dichotomic classes and bijections of the genetic code. J. Theor. Biol. 336, 221–230 (2013)
Gumbel, M., Fimmel, E., Danielli, A., Strüngmann, L.: On models of the genetic code generated by binary dichotomic algorithms. BioSystems 128, 9–18 (2015)
Petoukhov, S.V., He, M.: Symmetrical Analysis Techniques for Genetic Systems and Bioinformatics: Advanced Patterns and Applications. IGI Global, Hershey, USA (2009)
Fimmel, E., Strüngmann, L.: Mathematical Fundamentals for the noise immunity of the genetic code. BioSystems 164, 186–198 (2018)
Fimmel, E., Gumbel, M., Strüngmann, L.: Exploring structure and evolution of the genetic code with the software tool GCAT. In: AIMEE 2017: Advances in Artificial Systems for Medicine and Education, 658, pp. 14–22. Springer, Berlin (2018). https://doi.org/10.1007/978-3-319-67349-3-2
Petoukhov, S.V.: The system-resonance approach in modeling genetic structures. Biosystems 139, 1–11 (2016)
Petoukhov, S.V.: Genetic coding and united-hypercomplex systems in the models of algebraic biology. Biosystems 158, 31–46 (2017)
Petoukhov, S.V.: The rules of long DNA-sequences and tetra-groups of oligonucleotides. https://arxiv.org/abs/1709.04943, the 4th version (25.12.2017)
Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, New York (2010)
Petoukhov, S.V., Petukhova, E.S., Svirin, V.I.: New symmetries and fractal-like structures in the genetic coding system. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds.) Advances in Computer Science for Engineering and Education. ICCSEEA 2018. Advances in Intelligent Systems and Computing, vol. 754. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-91008-6_59
Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., Lloud, S. Quantum machine learning. Nature 549, 195–202 (14 Sept 2017). https://doi.org/10.1038/nature23474
Abo-Zahhad, M., Ahmed, S.M., Abd-Elrahman, S.A.: Genomic analysis and classification of exon and intron sequences using DNA numerical mapping techniques. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 4(8), 22–36 (2012). https://doi.org/10.5815/ijitcs.2012.08.03
Hossein, S.M., Roy, S.: A compression & encryption algorithm on DNA sequences using dynamic look up table and modified Huffman techniques. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 5(10), 39–61 (2013). https://doi.org/10.5815/ijitcs.2013.10.05
Meher, J.K., Panigrahi, M.R., Dash, G.N., Meher, P.K.: Wavelet based lossless DNA sequence compression for faster detection of eukaryotic protein coding regions. Int. J. Image Graph. Signal Process. (IJIGSP) 4(7), 47–53 (2012). https://doi.org/10.5815/ijigsp.2012.07.05
Fimmel, E., Michel, ChJ, Strüngmann, L.: Diletter circular codes over finite alphabets. Math. Biosci. 10(294), 120–129 (2017). https://doi.org/10.1016/j.mbs.2017.10.001
Fimmel, E., Michel, ChJ, Strüngmann, L.: Strong comma-free codes in genetic information. Bull. Math. Biol. 79(8), 1796–1819 (2017). https://doi.org/10.1007/s11538-017-0307-0
Fimmel, E., Strüngmann, L.: Codon distribution in error-detecting circular codes. Life 6(1), 14 (2016). https://doi.org/10.3390/life6010014
Fimmel, E., Michel, ChJ, Strüngmann, L.: n-nucleotide circular codes in graph theory. Phil. Trans. R. Soc. A 374, 20150058 (2016)
Fimmel, E., Giannerini, S., Gonzalez, D., Strüngmann, L.: Circular codes, symmetries and transformations. J. Math. Biol. 70(7), 1623–44 (2014)
Fickett, J.W., Burks, C.: Development of a database for nucleotide sequences. In: Waterman, M.S. (ed.) Mathematical Methods for DNA Sequences, pp. 1–34. CRC Press, Inc., Florida (1989)
Kraljic, K., Strüngmann, L., Fimmel, E., Gumbel, M.: Genetic code analysis toolkit: a novel tool to explore the coding properties of the genetic code and DNA sequences. SoftwareX 7, 1214, (January–June 2018), https://doi.org/10.1016/j.softx.2017.10.008
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Fimmel, E., Petoukhov, S.V. (2020). Genetic Code Modelling from the Perspective of Quantum Informatics. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Medicine and Education II. AIMEE2018 2018. Advances in Intelligent Systems and Computing, vol 902. Springer, Cham. https://doi.org/10.1007/978-3-030-12082-5_11
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