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New Symmetries and Fractal-Like Structures in the Genetic Coding System

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Advances in Computer Science for Engineering and Education (ICCSEEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 754))

Abstract

The achievements of molecular genetics and bioinformatics lead to significant changes in technological, medical and many other areas of our lives. This article is devoted to new results of study of structural organization of genetic information in living organisms. A new class of symmetries and fractal-like patterns in long DNA-texts is represented in addition to two Chargaff’s parity rules, which played an important role in development of genetics and bioinformatics. Our results provide new approaches for modeling genetic informatics from viewpoints of quantum informatics and theory of dynamic chaos.

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Author information

Authors and Affiliations

  1. Mechanical Engineering Research Institute, Russian Academy of Sciences, M. Kharitonievsky Pereulok, 4, Moscow, Russia

    Sergey Petoukhov, Elena Petukhova & Vitaliy Svirin

Authors
  1. Sergey Petoukhov
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  2. Elena Petukhova
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  3. Vitaliy Svirin
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Corresponding author

Correspondence to Sergey Petoukhov .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kiev Polytechnic Institute”, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Ft. Lauderdale, Florida, USA

    Matthew He

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Petoukhov, S., Petukhova, E., Svirin, V. (2019). 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. https://doi.org/10.1007/978-3-319-91008-6_59

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