Spectral Decomposition of Mappings of Molecular Genetic Information in the System Basis of Single Nucleotide Functions

This paper presents and visualizes examples of large amounts of genetic information using a new class of cognitive computer graphics algorithms. These algorithms are related to the semiotics of perception and allow the interpretation of those properties of nucleotide sequences that are difficult to perceive by simple reading or by standard means of statistical analysis. This article summarizes previously presented algorithms for visualizing long nucleic acids based on the primary Hadamard–Walsh function system. The described methods allow us to produce one-dimensional mappings of nucleic acids by levels corresponding to their scale-integral physicochemical parameters and construct a spectral decomposition of the nucleotide composition. An example of the spectral decomposition of parametric representations of molecular genetic structures is given. In addition, a multiscale composition of genetic functional mappings visualizing the structural features of nucleic acids is discussed. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Authors
Stepanyan I. 1, 2 , Lednev M.2
Journal
Publisher
MDPI AG
Number of issue
5
Language
English
Status
Published
Number
844
Volume
14
Year
2022
Organizations
  • 1 Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, Moscow, 117198, Russian Federation
  • 2 Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN), M. Kharitonyevskiy Pereulok, Moscow, 101990, Russian Federation
Keywords
big data; chromosomes; decomposition; DNA; geometry; nucleotides; spectral analysis; visualization
Date of creation
06.07.2022
Date of change
06.07.2022
Short link
https://repository.rudn.ru/en/records/article/record/83645/
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