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A Study of Compression–Based Methods for the Analysis of Barcode Sequences

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Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2012)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7845))

Abstract

In this paper it is introduced a new methodology for the analysis of barcode sequences. Barcode DNA is a very short nucleotide sequence, corresponding for the animal kingdom to the mitochondrial gene cytochrome c oxidase subunit 1, that acts as a unique element for identification and taxonomic purposes. Traditional barcode analysis uses well consolidated bioinformatics techniques such as sequence alignment, computation of evolutionary distances and phylogenetic trees. The proposed alignment-free approach consists in the use of two different compression-based approximations of Universal Similarity Metric in order to compute dissimilarity matrices among barcode sequences of 20 datasets belonging to different species. From these matrices phylogenetic trees are computed and compared, in terms of topology and branch length, with trees built from evolutionary distance. The results show high similarity values between compression-based and evolutionary-based trees allowing us to consider the former methodology worth to be employed for the study of barcode sequences

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Authors and Affiliations

  1. ICAR-CNR, National Research Council of Italy, viale delle Scienze Ed.11, 90128, Palermo, Italy

    Massimo La Rosa, Antonino Fiannaca, Riccardo Rizzo & Alfonso Urso

Authors
  1. Massimo La Rosa
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  2. Antonino Fiannaca
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  3. Riccardo Rizzo
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  4. Alfonso Urso
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Editor information

Editors and Affiliations

  1. Center for Biostatistics, TMHRI, Weill Cornell Medical College, ll,, Cornell University,, 6565 Fannin Street, Mary Gibbs Jones Ha, 77030, Houston, TX, USA

    Leif E. Peterson

  2. DIBRIS, University of Genova, Via Dodecaneso 35, 16146, Genova, Italy

    Francesco Masulli

  3. Sbarro Institute for Cancer Research and Moleculare Medicine, Center for Biotechnology, Temple University, 1900 N 12th Street, BioLife Science Bldg, 19122, Philadelphia, PA, USA

    Giuseppe Russo

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La Rosa, M., Fiannaca, A., Rizzo, R., Urso, A. (2013). A Study of Compression–Based Methods for the Analysis of Barcode Sequences. In: Peterson, L.E., Masulli, F., Russo, G. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2012. Lecture Notes in Computer Science(), vol 7845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38342-7_10

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  • DOI: https://doi.org/10.1007/978-3-642-38342-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38341-0

  • Online ISBN: 978-3-642-38342-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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