Publications by authors named "V A Kutyrkin"

New stochastic models based on a notion of stochastic codon are proposed. These models, presented by special random strings, describe practical structural-statistical properties which are peculiar to coding DNA both from prokaryotic and eukaryotic genomes. In such the case coding regions are considered as the realizations of random strings.

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Methods of the spectral-statistical approach (2S-approach) for revealing latent periodicity in DNA sequences are described. The results of data analysis in the HeteroGenome database which collects the sequences similar to approximate tandem repeats in the genomes of model organisms are adduced. In consequence of further developing of the spectral-statistical approach, the techniques for recognizing latent profile periodicity are considered.

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The concept of latent triplet periodicity in coding DNA sequences which has been earlier extensively discussed is confirmed in the result of analysis of a number of eukaryotic genomes, where latent periodicity of a new type, called profile periodicity, is recognized in the CDSs. Original model of Stochastic Homogeneous Organization of Coding (SHOC-model) in textual string is proposed. This model explains the existence of latent profile periodicity and regularity in DNA sequences.

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We present the first release of the HeteroGenome database collecting latent periodicity regions in genomes. Tandem repeats and highly divergent tandem repeats along with the regions of a new type of periodicity, known as profile periodicity, have been collected for the genomes of Saccharomyces cerevisiae, Arabidopsis thaliana, Caenorhabditis elegans and Drosophila melanogaster. We obtained data with the aid of a spectral-statistical approach to search for reliable latent periodicity regions (with periods up to 2000 bp) in DNA sequences.

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Novel methods for identifying a new type of DNA latent periodicity, called latent profile periodicity or latent profility, are used to search for periodic structures in genes. These methods reveal two distinct levels of organization of genetic information encoding. It is shown that latent profility in genes may correlate with specific structural features of their encoded proteins.

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