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The principle "like begets like" in algebra-matrix genetics and code biology.
- Source :
-
Biosystems . Nov2023, Vol. 233, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
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Abstract
- The article is devoted to analysis of emergent properties of the system of binary oppositions in the genetic code ensemble. The epochal model of the double helix of DNA by Watson and Crick showed that the multiple reproduction of genetic information on DNA strands uses the ancient principle "like begets like" based on the simple complementarity in pairs of nucleobases. Each of these pairs is built on the binary opposition "purine-pyrimidine". But the system of DNA n -plet alphabets and genetic coding is much richer in types of binary oppositions, which also have some coding meanings related to this principle. The article contains the results of the application of the author's "method of hierarchy binary stochastics" (HBS-method) to the analysis of the quasi-stochastic organization of binary sequences of hydrogen bonds in genomic single-stranded DNAs. This analysis revealed hidden probability rules related to dichotomous fractal-like probability trees. The relationship between inherited bodily dichotomies in living organisms and the discovered probability dichotomies in information sequences of genomic DNAs is discussed. The encoding properties of molecular binary oppositions in the DNA nucleotide system allows the algorithmic construction of (2 n ∗2 n )-matrices of probabilities of n -plets in these binary sequences, which are matrix representations of 2 n -dimensional hyperbolic numbers. Connections of these multidimensional numbers with some inherited physiological phenomena and deep neural networks are noted. A unified algebra-numeric certification of the DNAs of genomes and genes - based on these multidimensional numerical systems - is proposed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03032647
- Volume :
- 233
- Database :
- Academic Search Index
- Journal :
- Biosystems
- Publication Type :
- Academic Journal
- Accession number :
- 172887834
- Full Text :
- https://doi.org/10.1016/j.biosystems.2023.105019