Krista Ritchie
New algorithms that make it possible to view multispectral images of genetic sequences are discussed in this article. We demonstrated the practical challenges of comparative genomics and gave examples of how such mappings are constructed. Due to their representativeness and informativeness, new DNA visualization tools appear promising. The study shows how comparative genetics can benefit from a novel type of multispectral mapping that is based on decomposition across multiple parametric spaces. In the study of the genetic coding phenomenon and in actual activities like forensics, genetic testing, genealogical analysis, etc., this appears to be an essential step. For a variety of coordinate systems, examples of multispectral parametric sets are provided in the article. We use binary sub-alphabets of keto/amino and purine/pyrimidine to create mappings. We displayed 2D and 3D renderings in a variety of distinctive spaces: third-order spherical, structural, integral, cyclic and spherical. The author's previous method for visualizing genetic information using new molecular genetic algorithms is the foundation of this study. An object of discrete geometry, a high-dimensional symmetrical square matrix, is one type of mapping, specifically two-dimensional. Using the developed mathematical apparatus for representing large volumes of complexly organized molecular genetic information, we are able to discuss the close connection between the phenomenon of genetic coding and symmetry thanks to the fundamental properties of symmetry that are traced on these mappings.
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