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Phylogenetic and Biological Analysis of Evolutionary Components from Various Genomes

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Intelligent Systems

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

There are various mathematical models to analyze molecular as well as morphological information of various genes through phylogeny. Major threats in phylogenetic analysis are focused mainly that the search should use authentic as well as efficient approaches to grasp the large amount of sequential data found from latest genome sequencing. Another major issue is to determine the relationships among the evolution of structural elements as well as their experimental implementation, which is mainly neglected in previous research. In this paper, we implemented the structural element in the metazoan genome, known as key K-string, which could deliver on the point of ground as the construction of phylogenetic trees. The trees achieved against the key K-string were logically comprehensive in the present aspect of metazoan phylogeny as well as presented a higher analytical topology as compared to the trees drawn by the use of other methods. Moreover, the appropriate structural aspect of the key K-string shall have a few applications in the inspection of the structure and function relation of protein as well as in the decision of evolutionary species. The innovations as well as potential gravity of key K-string point us to accept their crucial evolutionarily, and they might show a major role in the course of species expansion.

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References

  1. Xie Q, Lin J, Qin Y, Zhou J, Bu W (2011) Structural diversity of eukaryotic 18S rRNA and its impact on alignment and phylogenetic reconstruction. Protein Cell 2:161–170

    Article  Google Scholar 

  2. Gruning B et al (2018) Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods 15:475–476

    Article  Google Scholar 

  3. Ondov BD et al (2016) Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17:132

    Article  Google Scholar 

  4. Li Q, Xu Z, Hao B (2010) Composition vector approach to whole-genome-based prokaryotic phylogeny: success and foundations. J Biotechnol 149:115–119

    Article  Google Scholar 

  5. Smith SA et al (2011) Understanding angiosperm diversification using small and large phylogenetic trees. Am J Bot 98:404–414

    Article  Google Scholar 

  6. Sankarasubramanian J, Vishnu US, Gunasekaran P, Rajendhran J (2016) A genome-wide SNP-based phylogenetic analysis distinguishes different biovars of Brucella suis. Infect Genet Evol 41:213–217

    Article  Google Scholar 

  7. Lomsadze A, Gemayel K, Tang S, Borodovsky M (2018) Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes. Genome Res 28:1079–1089

    Article  Google Scholar 

  8. Girault G, Blouin Y, Vergnaud G, Derzelle S (2014) High-throughput sequencing of Bacillus anthracis in France: investigating genome diversity and population structure using whole-genome SNP discovery. BMC Genom 15:288

    Article  Google Scholar 

  9. Griffing SM et al (2015) Canonical single nucleotide polymorphisms (SNPs) for high-resolution subtyping of Shiga-toxin producing Escherichia coli (STEC) O157:H7. PLoS One 10:e0131967

    Google Scholar 

  10. Gardner SN, Slezak T, Hall BG (2015) kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinforma 31:2877–2878

    Google Scholar 

  11. Sahl JW et al (2015) Phylogenetically typing bacterial strains from partial SNP genotypes observed from direct sequencing of clinical specimen metagenomic data. Genome Med 7:52

    Article  Google Scholar 

  12. Sahl JW et al (2016) NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats. Microb Genom 2:e000074

    Google Scholar 

  13. Li PE et al (2017) Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform. Nucleic Acids Res 45:67–80

    Article  Google Scholar 

  14. Klenk H, Göker M (2010) En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol 33:175–182

    Article  Google Scholar 

  15. Sims GE, Kim SH (2011) Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs). Proc Natl Acad Sci USA 108:8329–8334

    Article  Google Scholar 

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Singh, K., Gupta, M.K., Kumar, A. (2021). Phylogenetic and Biological Analysis of Evolutionary Components from Various Genomes. In: Sheth, A., Sinhal, A., Shrivastava, A., Pandey, A.K. (eds) Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-2248-9_17

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