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An Algorithm for Multiple and Global Alignments

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Bioinformatics Research and Development (BIRD 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 13))

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Abstract

In this paper, we develop a new algorithm to construct Multiple and Global Alignments (MGA) of primary structures, i.e., strings coding biological macromolecules. The construction of such alignments is based on the one of the (longest) Approximate Common Subsequences (ACS), made up by longer approximate substrings appearing, approximately, in the same positions in all the strings. This ACS represents a MGA. Constructing such alignments is a way to find homologies between biological macromolecules. Our algorithm is of complexity O(N 2*L 2*(log(L))2) in computing time, where N is the number of the strings and L is the length of the longest string.

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References

  1. Sagot, M.F.: Ressemblance Lexicale et Structurale Entre Macromolécules -Formalisation et Approches Combinatoires, Thèse de Doctorat, Université de Marne-La-Vallée, France (1996)

    Google Scholar 

  2. Hannenhalli, S.: Transforming Men Into Mice a Computationnal Theory of Genome Rearrangements, PhD Thesis, The Pennsylvania State University (1995)

    Google Scholar 

  3. Hannenhalli, S., Pevzner, P.: Transforming Cabbage Into Turnip (Polynomial Algorithm for Srting Signed Permutations By Reversals). In: Proc. 27th Annual ACM Symposium on the Theory of Computing, pp. 178–189 (1995)

    Google Scholar 

  4. Christie, D.: Genome Rearrangement Problems Ph.D Thesis, University of Glasgow (1998)

    Google Scholar 

  5. Corpet, F.: Multiple Sequence Alignment With Hierarchical Clustering. Nucleic Acids Research 16(22), 10881–10890 (1988)

    Article  Google Scholar 

  6. Depiereux, E., Feytmans, E.: MATCH-BOX - A fundamentally new Algorithm for The Simultaneous Alignment of Several Protein Sequences. Comput. Appl. Biosci. 8(5), 501–509 (1992)

    Google Scholar 

  7. Delcher, A.L., Phillippy, A., Carlton, J., Salzberg, S.L.: Fast Algorithms for Large-ScaleGenome Alignment and Comparison. Nucleic Acids Research 30(11), 2478–2483 (2002)

    Article  Google Scholar 

  8. Lee, C., Grasso, C., Sharlow, M.: Multiple Sequence Alignment UingPpartial Order Graphs. Bioinformatics (18), 452–464 (2002)

    Article  Google Scholar 

  9. Brudno, M., Chapman, M., Göttgens, B., Batzoglou, S., Morgenstern, B.: Fast and Sensitive Multiple Alignment of Large Genomic Sequences. BMC Bioinformatics 4(66), 1–11 (2003)

    Google Scholar 

  10. Bray, N., Pachter, L.: MAVID: Constrained Ancestral Alignment of Multiple Sequences. Genome Research (14), 693–699 (2004)

    Article  Google Scholar 

  11. Lassmann, T., Sonnhammer, E.: Kalign: An Accurate and Fast Multiple Sequence Alignment Algorithm. BMC Bioinformatics (6), 298 (2005)

    Article  Google Scholar 

  12. Schwartz, A., Pachter, L.: Multiple Alignment by Sequence Annealing. Bioinformatics (2006)

    Google Scholar 

  13. Morgenstern, B., Dress, A., Werner, T.: Multiple DNA and Protein Sequence Alignment Based on Segment-to-Segment Comparison. Proc. Natl. Acad. Sci. U.S.A. (93), 2098–12103 (1996)

    Article  Google Scholar 

  14. Morgenstern, B., Frech, K., Dress, A., Werner, T.: DIALIGN: Finding Local Similarities by Multiple Sequence Alignment. Bioinformatics 14(3), 290–294 (1998)

    Article  Google Scholar 

  15. Lenhof, H.P., Morgenstern, B., Reinert, K.: An Exact Solution for The Segment-to-Segment Multiple Sequence Alignment Problem. Bioinformatics (15), 203–210 (1999)

    Article  Google Scholar 

  16. Schwartz, S., Kent, W.J., Smit, A., Zhang, Z.: Human-Mouse Alignments with Blastz. Genome Research, 103–107 (2003)

    Google Scholar 

  17. Brudno, M., Do, C.B., Cooper, G.M., Kim, M.F., Davydov, E., Green, E.D., Sidow, A., Batzoglou, S.: LAGAN and Multi-LAGAN: Efficient Tools for Large-Scale Multiple Alignment of Genomic DNA. Genome Research (13), 721–731 (2003)

    Article  Google Scholar 

  18. Frith, M.C., Hansen, U., Spouge, J.L.: Finding Functional Sequence Elements by Multiple Local Alignments. Nucleic Acids Research 32(1), 189–200 (2004)

    Article  Google Scholar 

  19. Morgenstern, B.: DIALIGN: Multiple DNA and Protein Sequence Alignment at BiBiServ. Nucleic Acids Research 32(Web Server Issue) (2004)

    Google Scholar 

  20. Ovcharenko, I., Loots, G.G., Giardine, B.M., Hou, M., Ma, J., Hardison, R.C., Stubbs, L., Millers, W.: Mulan: Multiple-Sequence Local Alignment and Visualization for Studying Function and Evolution. Genome Research (15), 184–194 (2005)

    Article  Google Scholar 

  21. 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 Biolog (48), 443–453 (1970)

    Article  Google Scholar 

  22. Byers, T.H., Waterman, M.S.: Determining All Optimal and Near-Optimal Solutions when Solving Shortest Path Problems by Dynamic Programming. Operations Research 32(6), 1381–1384 (1984) Operations Research Society of America (Eds.)

    MATH  MathSciNet  Google Scholar 

  23. Waterman, M.S., Byers, T.H.: A Dynamic Programming Algorithm to Find All Solutions in a Neighborhood of The Optimum. Mathematical Biosciences (77), 179–188 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  24. Zuker, M.: Suboptimal Sequence Alignment in Molecular biology: 1nalysis with Errors. J. Mol. Biol. 221, 403–420 (1991)

    Article  Google Scholar 

  25. Naor, D., Brutlag, D.L.: On Near-Optimal Alignments of Biological Sequences. J. Comp. Biol. (4), 349–366 (1994)

    Article  Google Scholar 

  26. Kurtz, S., Ohlebusch, E., Schleiermacher, C., Stoye, J.: Reputer: The Manifold Applications of Repeat Analysis. Nucleic Acids Research 29(22), 4633–4642 (2001)

    Article  Google Scholar 

  27. Noé, L.: Recherche de Similarités dans Les Séquences d’ADN: Modèles et Algorithmes pour la Conception de Graines Efficaces, Thése de Doctorat, Université Henri Poincaré (2005)

    Google Scholar 

  28. Huang, W., Umbach, D.M., Leping, L.: Accurate Anchoring Alignment of Divergent Sequences. Bioinformatics, 22(1), 29–34 (2006)

    Article  Google Scholar 

  29. Zhang, X., Kahveci, T.: A New Approach for Alignment of Multiple Proteins. In: Pacific Symposium on Biocomputing, vol. 11, pp. 339–350 (2006)

    Google Scholar 

  30. Edgar, R.C.: MUSCLE: Multiple Sequence Alignment with High Accuracy and High throughput. Nucleic Acids Research 32(5), 1792–1797 (2004)

    Article  Google Scholar 

  31. Liang Ye, Y., Huang, X.: MAP2: Multiple Alignments of Syntenic Genomic sequences. Nucleic Acids Research 33(1), 162–170 (2005)

    Article  Google Scholar 

  32. Levenshtein, V.I.: Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Cybernetics and Control Theory 10(8), 707–710 (1966)

    MathSciNet  Google Scholar 

  33. Aho, A.V., Hopcroft, J.E., Ullman, J.D.: The Design and Analysis of Computer Algorithms, pp. 60–65. Addison-Wesley Publishing Company, Reading (1974)

    MATH  Google Scholar 

  34. Karp, R., Miller, R.E., Rosenberg, A.L.: Rapid Identification of Repeated Patterns in Strings, Trees and Arrays. In: 4th symposium of theory of Computing, pp. 125–136 (1972)

    Google Scholar 

  35. RNA Families Database of Alignments and CMs http://www.sanger.ac.uk/Software/Rfam

  36. Protein Families Database, http://www.sanger.ac.uk/Software/Pfam

  37. National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov

  38. Dayhoff, M.O., Schwartz, R.M., Orcutt, B.C.: A Model for Evolutionary Change. Atlas of Protein Sequence and Structure 5(3), 345–352 (1979)

    Google Scholar 

  39. Henikoff, S., Henikoff, J.G.: Amino Acid Substitution Matrices From Protein Blocks. Proc. Natl. Acad. Sci. U.S.A. 89, 10915–10919 (1992)

    Article  Google Scholar 

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Authors and Affiliations

  1. Higher School of Sciences and Technologies of Tunis, Research Unit of Technologies of Information and Communication, 5, Avenue Taha Hussein, Monfleury, 1008, Tunis, Tunisia

    Mourad Elloumi & Ahmed Mokaddem

Authors
  1. Mourad Elloumi
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  2. Ahmed Mokaddem
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Editor information

Mourad Elloumi Josef Küng Michal Linial Robert F. Murphy Kristan Schneider Cristian Toma

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Elloumi, M., Mokaddem, A. (2008). An Algorithm for Multiple and Global Alignments. In: Elloumi, M., Küng, J., Linial, M., Murphy, R.F., Schneider, K., Toma, C. (eds) Bioinformatics Research and Development. BIRD 2008. Communications in Computer and Information Science, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70600-7_37

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  • DOI: https://doi.org/10.1007/978-3-540-70600-7_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70598-7

  • Online ISBN: 978-3-540-70600-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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