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    Neural networks in the analysis of nucleotide genomic signals
    (Maltepe Üniversitesi, 2009) Cristea, Paul Dan
    Converting nucleotide sequences to digital signals [1] allows to apply signal processing methods for the analysis of genomic data. The method reveals surprising regularities in the distribution of nucleotides, pairs of nucleotides and small groups of nucleotides along a chromosome, in both prokaryotes and eukaryotes. These features of nucleotide sequences would be difficult to find by using only symbolic genomic sequences and standard statistical and pattern matching methods [2]. The mapping we have used in our work [1, 3] is a one-to-one unbiased representation of nucleotide equivalence classes, which attaches quadrantal complex numbers to adenine, cytosine, guanine and thymine nucleotides.