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International Workshop on Combinatorial Image Analysis

IWCIA 2018: Combinatorial Image Analysis pp 179–188Cite as

Evaluation of Chaos Game Representation for Comparison of DNA Sequences

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11255))

Abstract

Chaos Game Representation (CGR) of DNA sequences has been used for visual representation as well as alignment-free comparisons. CGR is considered to be of great value as the images obtained from parts of a genome present the same structure as those obtained for the whole genome. However, the robustness of the CGR method to compare DNA sequences obtained in a variety of scenarios is not yet fully demonstrated. This paper addresses this issue by presenting a method to evaluate the potential of CGR to distinguish various classes in a DNA dataset. Two indices are proposed for this purpose - a rejection rate (\(\alpha \)) and an overlapping rate (\(\beta \)). The method was applied to 4 datasets, with between 31 to 400 classes each. Nearly 430 million pairs of DNA sequences were compared using the CGR.

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Author information

Authors and Affiliations

  1. Departamento de Matemática, Faculdade de Ciências, Universidade do Porto, Porto, Portugal

    André R. S. Marcal

Authors
  1. André R. S. Marcal
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Correspondence to André R. S. Marcal .

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Editors and Affiliations

  1. State University of New York at Fredonia, Fredonia, NY, USA

    Reneta P. Barneva

  2. State University of New York, Buffalo, NY, USA

    Valentin E. Brimkov

  3. University of Porto, Porto, Portugal

    João Manuel R.S. Tavares

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Marcal, A.R.S. (2018). Evaluation of Chaos Game Representation for Comparison of DNA Sequences. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Combinatorial Image Analysis. IWCIA 2018. Lecture Notes in Computer Science(), vol 11255. Springer, Cham. https://doi.org/10.1007/978-3-030-05288-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-05288-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05287-4

  • Online ISBN: 978-3-030-05288-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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