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dc.contributor.authorBelinsky, Alexandra
dc.contributor.authorKouzaev, Guennadi
dc.date.accessioned2023-02-28T07:37:22Z
dc.date.available2023-02-28T07:37:22Z
dc.date.created2023-02-16T11:23:21Z
dc.date.issued2022
dc.identifier.citationWSEAS Transactions on Circuits and Systems. 2022, 21 323-348.en_US
dc.identifier.issn1109-2734
dc.identifier.urihttps://hdl.handle.net/11250/3054444
dc.description.abstractThis work aims to study the virus RNAs using a novel accelerated algorithm to explore anylength repetitive genomic fragments in sequences using Hamming distance between the binaryexpressed characters of an RNA and a query pattern. Primary attention is paid to the building and analyzing 1-D distributions (walks) of atg-patterns - codon-starting triplets in genomes. These triplets compose a distributed set called a word scheme of RNA. A complete genome map is built by plotting the mentioned atg-walks, trajectories of separate (a-, c-, g-, and t-symbols) nucleotides, and the lines designating the genomic words. The said map can be additionally equipped by gene’s designations making this tool pertinent for multi-scale genomic analyses. The visual examination of atg-walks is followed by calculating statistical parameters of genomic sequences, including estimating walkgeometry deviation of RNAs and fractal properties of word-length distributions. This approach is applied to the SARS CoV-2, MERS CoV, Dengue, and Ebola viruses, whose complete genomic sequences are taken from GenBank and GISAID. The relative stability of these walks for SARS CoV-2 and MERS CoV viruses was found, unlike the Dengue and Ebola distributions that showed an increased deviation of their geometrical and fractal characteristics. The developed approach can be useful in further studying mutations of viruses and building their phylogenic trees.en_US
dc.language.isoengen_US
dc.publisherWorld Scientific and Engineering Academy and Society (WSEAS)en_US
dc.titleVisual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithmen_US
dc.title.alternativeVisual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithmen_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber323-348en_US
dc.source.volume21en_US
dc.source.journalWSEAS Transactions on Circuits and Systemsen_US
dc.identifier.doi10.37394/23201.2022.21.35
dc.identifier.cristin2126596
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode0


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