Abstract
With the advent of new generation sequencing methods, an exponential increase in molecular-biological data is observed. Data banks of biological sequences, such as GenBank [1], UniProt [2], KEGG [3] and others have reached large sizes. At the same time, the velocity of the description of the sequenced sequences is considerably behind the rate of their accumulation. With such an increase in the volume of information, solving the problem of lagging is impossible without the use of effective algorithms. A rather interesting, complex and deserving attention and detailed study is the direction of genomics responsible for finding efficient algorithms for solving the problem of pro and eukaryote gene identification. The most popular are software products that allow finding genes in accordance with the received pairwise alignment of the sequences using the dynamic programming method. This approach does not allow to explore all areas of the nucleotide sequence, since most of the genes have evolved during evolution, for example, by point mutations or the encoding region of the gene was obtained due to the incorporation of several genes. In such a situation, information about the sites forming hybrid genes will not be available in the databases. Noteworthy is the non-trivial algorithm that was described in [4]. Finding the points of triplet periodicity change for a direct and backward complementary sequence enables the definition of coordinates that may indicate the location of the combination of the two genes.
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