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A Polynomial Algebra Method for Computing Exemplar Breakpoint Distance

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Bioinformatics Research and Applications (ISBRA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6674))

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Abstract

The exemplar breakpoint distance problem is NP-hard. Assume two genomes have at most n genes from m gene families. We develop an O(2m n O(1)) time algorithm to compute the exemplar breakpoint distance if one of them has no repetition. We develop an O(2m m!n O(1)) time algorithm to compute the exemplar breakpoint distance between two arbitrary genomes. If one of the given genomes has at most d repetitions for each gene, the computation time of the second algorithm is only O((2d)m n O(1)). Our algorithms are based on a polynomial algebra approach which uses a multilinear monomial to represent a solution for the exemplar breakpoint distance problem.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Texas-Pan American, Edinburg, TX, 78539, USA

    Bin Fu

  2. Department of Mathematics, National University of Singapore, 119076, Singapore

    Louxin Zhang

Authors
  1. Bin Fu
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  2. Louxin Zhang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, 77843-3112, College Station, TX, USA

    Jianer Chen

  2. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Jianxin Wang

  3. Department of Computer Science, Georgia State University, 30303, Atlanta, GA, USA

    Alexander Zelikovsky

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Fu, B., Zhang, L. (2011). A Polynomial Algebra Method for Computing Exemplar Breakpoint Distance. In: Chen, J., Wang, J., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2011. Lecture Notes in Computer Science(), vol 6674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21260-4_29

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  • DOI: https://doi.org/10.1007/978-3-642-21260-4_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21259-8

  • Online ISBN: 978-3-642-21260-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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