Conversion of nucleotides sequences into genomic signals

Area of Science:

• Bioinformatics
• Computational Biology
• Genetics

Background:

• The Genetic Code (GC) exhibits complex structure, degeneracy, and evolutionary trends.
• Existing representations may not fully capture these intricate properties.
• Analysis of genomic sequences often relies on traditional methods that can be enhanced.

Purpose of the Study:

• To define an original tetrahedral representation of the Genetic Code (GC).
• To explore dimensionality reduction and complex representations of the GC.
• To derive optimal symbolic-to-digital mappings for genomic signal analysis.

Main Methods:

• Development of a tetrahedral representation for the Genetic Code.
• Projection of the GC tetrahedron onto a plane for dimensional reduction.
• Creation of symbolic-to-digital mappings for nucleotide, codon, and amino acid sequences.
• Application of signal processing techniques to digital genomic signals.
• Introduction of new tools for genomic signal analysis (phase, path, stem representation).

Main Results:

• A new tetrahedral representation of the Genetic Code is established.
• Equivalent complex representations of the GC are derived.
• Nucleic acid and polypeptide sequences are converted into digital genomic signals.
• The existence of a global helicoidal wrapping of bases along DNA sequences is reported.
• New analytical tools for genomic signals at multiple levels (nucleotide, codon, amino acid) are introduced.

Conclusions:

• The proposed tetrahedral representation offers a superior framework for understanding GC structure, degeneracy, and evolution.
• Converting genomic sequences into digital signals facilitates advanced signal processing and analysis.
• The discovery of global helicoidal wrapping provides novel insights into DNA sequence organization.
• The developed tools enhance the extraction of essential features from nucleotide sequences.