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Extracting Common DNA Segments from the Complete Genomes of 7538 Viruses and Five Selected Mammals

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Advances in Computational Collective Intelligence (ICCCI 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2165))

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Abstract

This paper aims to extract common DNA consecutive sequences appearing in both of the complete genomes of viruses and that of mammals. With these common DNA sequences as genomic fossils, biologists or virologists can trace possible pathway of genomic evolution across species. To meet the requirement of huge computation to extract common DNA sequences from complete genomes of all viruses and mammals selected, this study adopts one previously developed approach that was based on MapReduce programming model. This study has experiments for extracting common DNA sequences run on a Hadoop cluster containing ten computing nodes. Experimental resources includes the whole genomic sequences of 7,538 viruses and five selected mammals, including \(\textit{Homo sapiens}\) (Human), \(\textit{Pan troglodytes}\) (Chimpanzee), \(\textit{Mus musculus}\) (House Mouse), \(\textit{Rattus norvegicus}\) (Brown Rat) and \(\textit{Sus scrofa}\) (Wild Boar). There are a huge amount of common DNA consecutive sequences extracted and, for simplicity, there are only 26 ones whose lengths are longer than 50 base-pair (bp) selected for illustration. Among above 26, there are 13 reverified as no repetitive sequences that could be seemed as the clues to reinspect the relationship of viruses and mammals. Via cloud computing that can provide with more computing nodes then ten used in this study, it is believed that this approach can handle with more complete genomes of species, and then provide more common genomic fossils to biologists or virologist to verify the potential connections among diverse species in the future.

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Acknowledgement

The project is funded in part by the Ministry of Science and Technology (MOST) under Grant No. 107-2632-E-468-002. Thanks for Prof. Tsung-Chi Chen discussing plant viruses. Thanks for Mr. Ren-Der Huang for maintaining Hadoop cluster computing environment.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, Asia University, No. 500, Lioufeng Road Wufeng Division, Taichung, Taiwan

    Jing-Doo Wang

  2. Department of Biomedical Sciences, Chung Shan Medical University, No. 110, Sec.1, Jianguo North Road, Taichung, Taiwan

    Yi-Chun Wang

Authors
  1. Jing-Doo Wang
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  2. Yi-Chun Wang
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Correspondence to Jing-Doo Wang .

Editor information

Editors and Affiliations

  1. and Technology, Wrocław University of Science, Wrocław, Poland

    Ngoc-Than Nguyen

  2. University of Leipzig, Leipzig, Germany

    Bogdan Franczyk

  3. University of Leipzig, Leipzig, Germany

    André Ludwig

  4. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Nunez

  5. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

  6. University of Münster, Münster, Germany

    Gottfried Vossen

  7. and Technology, Wrocław University of Science, Wrocław, Poland

    Adrianna Kozierkiewicz

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Wang, JD., Wang, YC. (2024). Extracting Common DNA Segments from the Complete Genomes of 7538 Viruses and Five Selected Mammals. In: Nguyen, NT., et al. Advances in Computational Collective Intelligence. ICCCI 2024. Communications in Computer and Information Science, vol 2165. Springer, Cham. https://doi.org/10.1007/978-3-031-70248-8_29

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  • DOI: https://doi.org/10.1007/978-3-031-70248-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-70247-1

  • Online ISBN: 978-3-031-70248-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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