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Simulated Annealing with Injecting Star-Alignment for Multiple Sequence Alignments

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

We present a novel algorithm SASAlignSimulated annealing with star-alignment. In the SASAlign, instead of starting with an initial solution chosen at random, we use the results formed by star-alignment to give a good starting point as the initial solution to the SA for further refinement. The time required by the algorithm scales linearly with the number of sequences in S, linearly with the number of iterations, and cube with the length of the sequences, that is O(Nnl 3). Experiments on the BAliBASE benchmark database also show that the proposed algorithm is efficient, and prove to be competitive with and better than the other method HMMT.

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References

  1. Jones, N.C., Pevzner, P.A.: An Introduction to Bioinformatics Algorithms. MIT Press, Cambridge (2004)

    Google Scholar 

  2. Gunsfield, D.: Algorithms on Strings, Trees and Sequences. Cambridge University Press, Cambridge (1999)

    Google Scholar 

  3. Huo, H.: Exercises and Solutions on Algorithms. Higher Education Press, China (2004)

    Google Scholar 

  4. Notredame, C.: Recent progresses in multiple sequence alignment: a survey. Pharmacogenomics 3, 131–144 (2002)

    Article  Google Scholar 

  5. Carrillo, H., Lipman, D.J.: The multiple sequence alignment problem in biology. SIAM Appl. Math. 48, 1073–1082 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  6. Pearson, W.R., Lipman, D.J.: Improved tools for biological sequence comparison. Proceedings of the National Academy of Sciences of the USA 4, 2444–2448 (1988)

    Article  Google Scholar 

  7. Feng, D.F., Doolittle, R.F.: Progressive sequence alignment as a prerequisite to correct phylogenetic trees. Molecular Evolution 25, 351–360 (1987)

    Article  Google Scholar 

  8. Konagurthu, A.S., Whisstock, J., Stuckey, P.J.: Progressive multiple alignment using sequence triplet optimizations and three-residue exchanges costs. Journal of Bioinformatics and Computational Biology 2, 719–745 (2004)

    Article  Google Scholar 

  9. Notredame, C., Higgins, D.G.: SAGA: sequence alignment by genetic algorithm. Nucleic Acids Research 24, 1515–1524 (1996)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Huo, H., Ming, H. (2005). Simulated Annealing with Injecting Star-Alignment for Multiple Sequence Alignments. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_121

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  • DOI: https://doi.org/10.1007/11596448_121

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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