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Convex Recolorings of Strings and Trees: Definitions, Hardness Results and Algorithms

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Algorithms and Data Structures (WADS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3608))

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Abstract

A coloring of a tree is convex if the vertices that pertain to any color induce a connected subtree. Convex colorings of trees arise in areas such as phylogenetics, linguistics, etc. e.g., a perfect phylogenetic tree is one in which the states of each character induce a convex coloring of the tree.

When a coloring of a tree is not convex, it is desirable to know ”how far” it is from a convex one, and what are the convex colorings which are ”closest” to it. In this paper we study a natural definition of this distance – the recoloring distance, which is the minimal number of color changes at the vertices needed to make the coloring convex. We show that finding this distance is NP-hard even for a path, and for some other interesting variants of the problem. In the positive side, we present algorithms for computing the recoloring distance under some natural generalizations of this concept: the uniform weighted model and the non-uniform model. Our first algorithms find optimal convex recolorings of strings and bounded degree trees under the non-uniform model in linear time for any fixed number of colors. Next we improve these algorithms for the uniform model to run in linear time for any fixed number of bad colors. Finally, we generalize the above result to hold for trees of unbounded degree.

This research was supported by the Technion VPR-fund and by the Bernard Elkin Chair in Computer Science.

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References

  1. Agrawala, R., Fernandez-Baca, D.: Simple algorithms for perfect phylogeny and triangulating colored graphs. International Journal of Foundations of Computer Science 7(1), 11–21 (1996)

    Article  Google Scholar 

  2. Ben-Dor, A., Friedman, N., Yakhini, Z.: Class discovery in gene expression data. In: RECOMB, pp. 31–38 (2001)

    Google Scholar 

  3. Bittner, M., et al.: Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406(6795), 536–40 (2000)

    Google Scholar 

  4. Bodlaender, H.L., Fellows, M.R., Warnow, T.: Two strikes against perfect phylogeny. In: ICALP, pp. 273–283 (1992)

    Google Scholar 

  5. Downey, R.G., Fellows, M.R.: Newblock Parameterized Complexity. Springer, Heidelberg (1999)

    Google Scholar 

  6. Dress, A., Steel, M.A.: Convex tree realizations of partitions. Applied Mathematics Letters 5(3), 3–6 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  7. Fernndez-Baca, D., Lagergren, J.: A polynomial-time algorithm for near-perfect phylogeny. SIAM Journal on Computing 32(5), 1115–1127 (2003)

    Article  MathSciNet  Google Scholar 

  8. Fitch, W.M.: A non-sequential method for constructing trees and hierarchical classifications. Journal of Molecular Evolution 18(1), 30–37 (1981)

    Article  MathSciNet  Google Scholar 

  9. Goldberg, L.A., Goldberg, P.W., Phillips, C.A., Sweedyk, Z., Warnow, T.: Minimizing phylogenetic number to find good evolutionary trees. Discrete Applied Mathematics 71, 111–136 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  10. Gusfield, D.: Efficient algorithms for inferring evolutionary history. Networks 21, 19–28 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  11. Hirsh, A., Tsolaki, A., DeRiemer, K., Feldman, M., Small, P.: From the cover: Stable association between strains of mycobacterium tuberculosis and their human host populations. PNAS 101, 4871–4876 (2004)

    Article  Google Scholar 

  12. Kannan, S., Warnow, T.: Inferring evolutionary history from DNA sequences. SIAM J. Computing 23(3), 713–737 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  13. Kannan, S., Warnow, T.: A fast algorithm for the computation and enumeration of perfect phylogenies when the number of character states is fixed. SIAM J. Computing 26(6), 1749–1763 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  14. Moran, S., Snir, S.: Convex recoloring of strings and trees. Technical Report CS-2003-13, Technion (November 2003)

    Google Scholar 

  15. Sankoff, D.: Minimal mutation trees of sequences. SIAM Journal on Applied Mathematics 28, 35–42 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  16. Semple, C., Steel, M.A.: Phylogenetics. Oxford University Press, Oxford (2003)

    MATH  Google Scholar 

  17. Steel, M.: The complexity of reconstructing trees from qualitative characters and subtrees. Journal of Classification 9(1), 91–116 (1992)

    Article  MATH  MathSciNet  Google Scholar 

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Moran, S., Snir, S. (2005). Convex Recolorings of Strings and Trees: Definitions, Hardness Results and Algorithms. In: Dehne, F., López-Ortiz, A., Sack, JR. (eds) Algorithms and Data Structures. WADS 2005. Lecture Notes in Computer Science, vol 3608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11534273_20

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  • DOI: https://doi.org/10.1007/11534273_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28101-6

  • Online ISBN: 978-3-540-31711-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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