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Efficiently Finding the Most Parsimonious Phylogenetic Tree Via Linear Programming

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Bioinformatics Research and Applications (ISBRA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4463))

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Abstract

Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we introduce an integer linear programming formulation to find the most parsimonious phylogenetic tree from a set of binary variation data. The method uses a flow-based formulation that could use exponential numbers of variables and constraints in the worst case. The method has, however, proved extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods. The program solves several large mtDNA and Y-chromosome instances within a few seconds, giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality.

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Authors and Affiliations

  1. Computer Science Department, Carnegie Mellon University,  

    Srinath Sridhar & Guy E. Blelloch

  2. Tepper School of Business, Carnegie Mellon University,  

    Fumei Lam & R. Ravi

  3. Department of Biological Sciences, Carnegie Mellon University,  

    Russell Schwartz

Authors
  1. Srinath Sridhar
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  2. Fumei Lam
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  3. Guy E. Blelloch
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  4. R. Ravi
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  5. Russell Schwartz
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Editor information

Ion Măndoiu Alexander Zelikovsky

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© 2007 Springer-Verlag Berlin Heidelberg

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Sridhar, S., Lam, F., Blelloch, G.E., Ravi, R., Schwartz, R. (2007). Efficiently Finding the Most Parsimonious Phylogenetic Tree Via Linear Programming. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_4

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  • DOI: https://doi.org/10.1007/978-3-540-72031-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72030-0

  • Online ISBN: 978-3-540-72031-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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