Specificity Analysis of Genome Based on Statistically Identical K-words with Same Base Combination

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dc.contributor.authorSeo, Hyeinko
dc.contributor.authorSong, YongJoonko
dc.contributor.authorCho, Kihoko
dc.contributor.authorCho, Dong-Hoko
dc.date.accessioned2021-02-03T08:10:21Z-
dc.date.available2021-02-03T08:10:21Z-
dc.date.created2020-10-12-
dc.date.created2020-10-12-
dc.date.created2020-10-12-
dc.date.created2020-10-12-
dc.date.issued2020-07-
dc.identifier.citationIEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY, v.1, pp.214 - 219-
dc.identifier.issn2644-1276-
dc.identifier.urihttp://hdl.handle.net/10203/280514-
dc.description.abstractGoal: Individual characteristics are determined through a genome consisting of a complex base combination. This base combination is reflected in the k-word profile, which represents the number of consecutive k bases. Therefore, it is important to analyze the genome-specific statistical specificity in the k-word profile to understand the characteristics of the genome. In this paper, we propose a new k-word-based method to analyze genome-specific properties. Methods: We define k-words consisting of the same number of bases as statistically identical k-words. The statistically identical k-words are estimated to appear at a similar frequency by statistical prediction. However, this may not be true in the genome because it is not a random list of bases. The ratio between frequencies of two statistically identical k-words can then be used to investigate the statistical specificity of the genome reflected in the k-word profile. In order to find important ratios representing genomic characteristics, a reference value is calculated that results in a minimum error when classifying data by ratio alone. Finally, we propose a genetic algorithm-based search algorithm to select a minimum set of ratios useful for classification. Results: The proposed method was applied to the full-length sequence of microorganisms for pathogenicity classification. The classification accuracy of the proposed algorithm was similar to that of conventional methods while using only a few features. Conclusions: We proposed a new method to investigate the genome-specific statistical specificity in the k-word profile which can be applied to find important properties of the genome and classify genome sequences.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleSpecificity Analysis of Genome Based on Statistically Identical K-words with Same Base Combination-
dc.typeArticle-
dc.type.rimsART-
dc.citation.volume1-
dc.citation.beginningpage214-
dc.citation.endingpage219-
dc.citation.publicationnameIEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY-
dc.identifier.doi10.1109/OJEMB.2020.3009055-
dc.contributor.localauthorCho, Dong-Ho-
dc.contributor.nonIdAuthorCho, Kiho-
dc.description.isOpenAccessY-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorAlignment-free-
dc.subject.keywordAuthorgenetic algorithm-
dc.subject.keywordAuthork-word-
dc.subject.keywordAuthormicrobial pathogenicity-
dc.subject.keywordAuthorstatistical specificity in k-word profile-
dc.subject.keywordPlusDNA-
dc.subject.keywordPlusPHYLOGENY-
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