Conversion of nucleotides sequences into genomic signals

Abstract

The almost complete sequencing of the human genome [1, 2], as well as the public access to most of its content [3, 4], offer the opportunity to explore in depth its content and to data mine this unique information depository. The standard approach of representing the genomic information by sequences of nucleotide symbols in the strands of DNA and RNA molecules, by symbolic codons (triplets of nucleotides), or by symbolic sequences of amino acids in the corresponding polypeptide chains (for the genes) limits the methodology of handling the genomic information to mere pattern matching or statistical procedures. Using a base 4 real representation or an equivalent complex dual binary representation of the nucleotides, allows converting the DNA sequences into digital genomic signals and offers the possibility to apply a wealth of powerful signal processing methods for their analysis. Currently, only about 32000 genes containing the Conversion of nucleotides sequences into genomic signals P. D. Cristea * Bio-Medical Engineering Center, "Politehnica" University of Bucharest, Romania Received: March 11, 2002; Accepted: April 29, 2002 Abstract An original tetrahedral representation of the Genetic Code (GC) that better describes its structure, degeneration and evolution trends is defined. The possibility to reduce the dimension of the representation by projecting the GC tetrahedron on an adequately oriented plane is also analyzed, leading to some equivalent complex representations of the GC. On these bases, optimal symbolic-to-digital mappings of the linear, nucleic acid strands into real or complex genomic signals are derived at nucleotide, codon and amino acid levels. By converting the sequences of nucleotides and polypeptides into digital genomic signals, this approach offers the possibility to use a large variety of signal processing methods for their handling and analysis. It is also shown that some essential features of the nucleotide sequences can be better extracted using this representation. Specifically, the paper reports for the first time the existence of a global helicoidal wrapping of the complex representations of the bases along DNA sequences, a large scale trend of genomic signals. New tools for genomic signal analysis, including the use of phase, aggregated phase, unwrapped phase, sequence path, stem representation of components' relative frequencies, as well as analysis of the transitions are introduced at the nucleotide, codon and amino acid levels, and in a multiresolution approach.

Matrix Genetics and Algebraic Properties of the Multi-Level System of Genetic Alphabets

“…Genetic 8-dimensional hypercomplex numbers and their metric 4-dimensional subspaces can be used to construct new genetic algorithms and new decisions in the field of artificial intelligence, robotics, etc. Some works try to analyze genetic sequences on the base of complex and hypercomplex numbers but in these attempts a difficult problem exists: what kind of hypercomplex numbers should be chosen for the analysis from a great set of all the types of hypercomplex numbers (Cristea, 2002(Cristea, , 2010Shu and Li, 2010;Shu and Ouw, 2004)? It seems obviously that hypercomplex numbers, which are described in our article, should be actively used in analyzing genetic sequences.…”

“…Numeric presentations of genetic sequences are useful to study hidden genetic regularities (Cristea, 2002(Cristea, , 2010Petoukhov and He, 2010). On the base of the described results, new approaches of numeric presentations of genetic sequences can be proposed for such aims.…”

Sayisal Hari̇talama Tekni̇kleri̇ Ve Fourier Dönüşümü Kullanilarak Dna Di̇zi̇li̇mleri̇ni̇n Siniflandirilmasi

“…Bu düzlemler karmaşık (complex) düzleme dönüştürülür ve böylece A, G, C, T bazlarının karmaşık temsilleri elde edilir. Bir x(n) diziliminde bazların karmaşık temsili aşağıda gösterilmiştir [11][12][13][14][15].…”

“…Karmaşık teknikler için kullanılan diğer bir dönüşümde ise A=1, T=j, C=-j ve G=-1 değerleri verilir. Bu sayısal dönüşüm bazların zayıf reel ve zayıf imajiner karmaşık temsilinde kullanılır [11][12][13][14][15].…”

Novel methodologies for spectral classification of exon and intron sequences

“…In this article, nine 1-sequence numerical representations (Codes 1-9) [5][6][7][8][9][10][11][12][13][14][15][16] are identified though a literature search, which can be grouped under positiveinteger-value, real-value, and complex-value numerical representations. In addition, seven 1-sequence complexvalue numerical representations (Codes 10-16) are derived.…”