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Parallel Progressive Multiple Sequence Alignment

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Computer Aided Systems Theory – EUROCAST 2005 (EUROCAST 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3643))

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Abstract

Multiple Sequence Alignment is an essential tool in the analysis and comparison of biological sequences. Unfortunately, the complexity of this problem is exponential. Currently feasible methods are, therefore, only approximations. The progressive multiple sequence alignment algorithms are the most widespread among these approximations. Still, the computation speed of typical problems is often not satisfactory. Hence, the well known progressive alignment scheme of ClustalW has been subject to parallelization to further accelerate the computation. In the course of this action a unique scheme to parallelize sequence alignment in particular and dynamic programming in general was discovered, which yields an average of n / 2 parallel calculations for problem size n. The scalability of O(n) tasks for problem size n can be even maintained for slower networks.

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References

  1. Hastings, N.A.J.: Dynamic Programming: With Management Applications, Butterworths (1973)

    Google Scholar 

  2. Needleman, S.B., Wunsch, C.D.: A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins. Journal of Molecular Biology 48, 443–453 (1970)

    Article  Google Scholar 

  3. Myers, E.W., Miller, W.: Optimal alignments in linear space. Computer Applications in the Biosciences 4, 11–17 (1988)

    Google Scholar 

  4. Higgins, D.G., Sharp, P.M.: CLUSTAL: a package for performing multiple sequence alignment on a microcomputer. Gene 73, 237–244 (1988)

    Article  Google Scholar 

  5. Thompson, J.D., Higgins, D.G., Gibson, T.J.: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research 22, 4673–4680 (1994)

    Article  Google Scholar 

  6. Saitou, N., Nei, M.: The Neighbor-joining Method: A New Method for Reconstructing Phylogenetic Trees. Journal of Molecular Biology and Evolution 4, 406–425 (1987)

    Google Scholar 

  7. Studier, J.A., Keppler, K.J.: A Note on the Neighbor-Joining Algorithm of Saitou and Nei. Journal of Molecular Biology and Evolution 5, 729–731 (1988)

    Google Scholar 

  8. Mattson, T.G., Sanders, B.A., Massingil, B.L.: A Pattern Language for Parallel Programming. Addison Wesley, Reading (2004)

    Google Scholar 

  9. Kern, T.: Biomedical Information Systems (2003), http://biomis.fh-hagenberg.at (last visited March 2005)

  10. Pitzer, E.: Acceleration of Progressive Multiple Sequence Alignment by Parallelization and Complexity Reduction of Existing Algorithms. Master’s thesis, University of Applied Sciences Hagenberg, Austria (2004)

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© 2005 Springer-Verlag Berlin Heidelberg

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Pitzer, E. (2005). Parallel Progressive Multiple Sequence Alignment. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_61

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  • DOI: https://doi.org/10.1007/11556985_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29002-5

  • Online ISBN: 978-3-540-31829-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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