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On the Longest Common Rigid Subsequence Problem

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Combinatorial Pattern Matching (CPM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3537))

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Abstract

The longest common subsequence problem (LCS) and the closest substring problem (CSP) are two models for the finding of common patterns in strings. The two problem have been studied extensively. The former was previously proved to be not polynomial-time approximable within ratio n δ for a constant δ. The latter was previously proved to be NP-hard and have a PTAS. In this paper, the longest common rigid subsequence problem (LCRS) is studied. LCRS shares similarity with LCS and CSP and has an important application in motif finding in biological sequences. LCRS is proved to be Max-SNP hard in this paper. An exact algorithm with quasi-polynomial average running time is also provided.

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References

  1. Identification of a src sh3 domain binding motif by screening a random phage display library. Journal of Biological Chemistry 269, 24034–24039 (1994)

    Google Scholar 

  2. Adebiyi, E.F., Kaufmann, M.: Extracting common motifs under the levenshtein measure: theory and experimentation. In: Guigó, R., Gusfield, D. (eds.) WABI 2002. LNCS, vol. 2452, pp. 140–156. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  3. Jiang, T., Li, M.: On the approximation of shortest common supersequence and longest common subsequences. SIAM Journal on Computing 24(5), 1122–1139 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  4. Keich, U., Pevzner, P.A.: Finding motifs in the twilight zone. In: Proceedings of the sixth annual international conference on computational biology, pp. 195–204 (2002)

    Google Scholar 

  5. Kevin Lanctot, J., Li, M., Ma, B., Wang, S., Zhang, L.: Distinguishing string selection problems. Information and Computation 185(1), 41–55 (2003); Early version appeared in SODA 1999

    Article  MATH  MathSciNet  Google Scholar 

  6. Li, M., Ma, B., Wang, L.: Finding Similar Regions in Many Strings. In: Proceedings of the thirty-first annual ACM symposium on Theory of computing (STOC), Atlanta, May 1999, pp. 473–482 (1999)

    Google Scholar 

  7. Li, M., Ma, B., Wang, L.: Finding Similar Regions in Many Sequences. Journal of Computer and System Sciences 65(1), 73–96 (2002); Early version appeared in STOC 1999

    Article  MathSciNet  Google Scholar 

  8. Li, M., Ma, B., Wang, L.: On the Closest String and Substring Problems. Journal of the ACM 49(2), 157–171 (2002); Early versions appeared in STOC 1999 and CPM 2000

    Article  MathSciNet  Google Scholar 

  9. Ma, B.: A Polynomial Time Approximation Scheme for the Closest Substring Problem. In: Giancarlo, R., Sankoff, D. (eds.) CPM 2000. LNCS, vol. 1848, pp. 99–107. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  10. Maier, D.: The complexity of some problems on subsequences and supersequences. Journal of the ACM 25, 322–336 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  11. Waterman, M.S., Arratia, R., Galas, D.J.: Pattern recognition in several sequences: consensus and alignment. Bulletin of Mathematical Biology 46(4), 515–527 (1984)

    MATH  MathSciNet  Google Scholar 

  12. Papadimitriou, C.H., Yannakakis, M.: Optimization, approximation, and complexity classes. Journal of Computer and System Sciences 43, 425–440

    Google Scholar 

  13. Rajasekaran, S., Balla, S., Huang, C.: Exact algorithms for planted motif challenge problems. In: Proceedings of the 3rd Asia Pacific Bioinformatics Conference (2005)

    Google Scholar 

  14. Rajasekaran, S., Balla, S., Huang, C.-H., Thapar, V., Gryk, M., Maciejewski, M., Schiller, M.: Exact algorithms for motif search. In: Proceedings of the 3rd Asia Pacific Bioinformatics Conference (2005)

    Google Scholar 

  15. Rigoutsos, I., Floratos, A.: Combinatorial pattern discovery in biological sequences: the teiresias algorithm. Bioinformatics 14(1), 55–67 (1998)

    Article  Google Scholar 

  16. Stormo, G., Hartzell III., G.W.: Identifying protein-binding sites from unaligned dna fragments. Proc. Natl. Acad. Sci. USA 88, 5699–5703 (1991)

    Article  Google Scholar 

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Ma, B., Zhang, K. (2005). On the Longest Common Rigid Subsequence Problem. In: Apostolico, A., Crochemore, M., Park, K. (eds) Combinatorial Pattern Matching. CPM 2005. Lecture Notes in Computer Science, vol 3537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11496656_2

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  • DOI: https://doi.org/10.1007/11496656_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26201-5

  • Online ISBN: 978-3-540-31562-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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