Skip to main content

Efficient Algorithms for Optimizing Whole Genome Alignment with Noise

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2906))

Abstract

Given the genomes (DNA) of two related species, the whole genome alignment problem is to locate regions on the genomes that possibly contain genes conserved over the two species. Motivated by existing heuristic-based software tools, we initiate the study of optimization problems that attempt to uncover conserved genes with a global concern. Another interesting feature in our formulation is the tolerance of noise. Yet this makes the optimization problems more complicated; a brute-force approach takes time exponential in the noise level. In this paper we show how an insight into the problem structure can lead to a drastic improvement in the time and space requirement (precisely, to O(k 2 n 2) and O(k 2 n), respectively, where n is the size of the input and k is the noise level). The reduced space requirement allows us to implement the new algorithms on a PC. It is exciting to see that when compared with the most popular whole genome alignment software (MUMMER) on real data sets, the new algorithms consistently uncover more conserved genes (that have been published by GenBank), while preserving the preciseness of the output.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baillie, D.L., Rose, A.M.: Waba success: A tool for sequence comparison between large genomes. Genome Research 10(8), 1071–1073 (2000)

    Article  Google Scholar 

  2. Batzoglou, S., Pachter, L., Mesirov, J.P., Berger, B., Lander, E.S.: Human and mouse gene structure: Comparative analysis and application to exon prediction. Genome Research 10, 950–958 (2000)

    Article  Google Scholar 

  3. Buhler, J.: Efficient large-scale sequence comparison by locality-sensitive hashing. Bioinformatics 17(5), 419–428 (2001)

    Article  Google Scholar 

  4. Delcher, A.L., Kasif, S., Fleischmann, R.D., Peterson, J., White, O., Salzberg, S.L.: Alignment of whole genomes. Nucleic Acids Research 27(11), 2369–2376 (1999)

    Article  Google Scholar 

  5. Delcher, A.L., Phillippy, A., Carlton, J., Salzberg, S.L.: Fast algorithms for large-scale genome alignment and comparison. Nucleic Acids Research 30(11), 2478–2483 (2002)

    Article  Google Scholar 

  6. Frazer, K.A., Elnitski, L., Church, D.M., Dubchak, I., Hardison, R.C.: Cross-species sequence comparisons: A review of methods and available resources. Genome Research 13, 1–12 (2003)

    Article  Google Scholar 

  7. Morgenstern, B.: Dialign 2: Improvement of the segment-to-segment approach to multiple sequence alignment. Bioinformatics 15, 211–218 (1999)

    Article  Google Scholar 

  8. Morgenstern, B., Frech, K., Dress, D., Werner, T.: Dialign: Finding local similarities by multiple sequence alignment. Bioinformatics 14, 290–294 (1998)

    Article  Google Scholar 

  9. Nieduszynski, C.A., Murray, J., Carrington, M.: Whole-genome analysis of animal a- and b-type cyclins. Genome Biology 3(12) (2002)

    Google Scholar 

  10. Schwartz, S., Zhang, Z., Frazer, K.A., Smit, A., Riemer, C., Bouck, J., Gibbs, R., Hardison, R., Miller, W.: Pipmaker - a web server for aligning two genomic dna sequences. Genome Research 10(4), 577–586 (2000)

    Article  Google Scholar 

  11. Vincens, P., Buffat, L., Andre, C., Chevrolat, J.P., Boisvieux, J.F., Hazout, S.: A strategy for finding regions of similarity in complete genome sequences. Bioinformatics 14, 715–725 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lam, T.W., Lu, N., Ting, H.F., Wong, P.W.H., Yiu, S.M. (2003). Efficient Algorithms for Optimizing Whole Genome Alignment with Noise. In: Ibaraki, T., Katoh, N., Ono, H. (eds) Algorithms and Computation. ISAAC 2003. Lecture Notes in Computer Science, vol 2906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24587-2_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24587-2_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20695-8

  • Online ISBN: 978-3-540-24587-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics