Skip to main content
SpringerLink
Log in

Efficient Algorithms for Locating the Length-Constrained Heaviest Segments, with Applications to Biomolecular Sequence Analysis

Extended Abstract

  • Conference paper
  • First Online:
Mathematical Foundations of Computer Science 2002 (MFCS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2420))

Abstract

We study two fundamental problems concerning the search for interesting regions in sequences: (i) given a sequence of real numbers of length n and an upper bound U, find a consecutive subsequence of length at most U with the maximum sum and (ii) given a sequence of real numbers of length n and a lower bound L, find a consecutive subsequence of length at least L with the maximum average. We present an O(n)-time algorithm for the first problem and an O(n log L)-time algorithm for the second. The algorithms have potential applications in several areas of biomolecular sequence analysis including locating GC-rich regions in a genomic DNA sequence, post-processing sequence alignments, annotating multiple sequence alignments, and computing length-constrained ungapped local alignment. Our preliminary tests on both simulated and real data demonstrate that the algorithms are very efficient and able to locate useful (such as GC-rich) regions.

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

Access this chapter

Log in via an institution
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. N.N. Alexandrov and V.V. Solovyev. Statistical significance of ungapped alignments. Pacific Symposium on Biocomputing (PSB-98), pages 463–472, 1998.

    Google Scholar 

  2. A. Arslan and Ö Eğecioğlu. Algorithms for local alignments with constraints. Manuscript, 2001.

    Google Scholar 

  3. A. Arslan, Ö Eğecioğlu, and P. Pevzner. A new approach to sequence comparison: Normalized sequence alignment. Bioinformatics, 17:327–337, 2001.

    Article  Google Scholar 

  4. V. Bafna and D.H. Huson. The conserved exon method for gene finding. Proc. Int. Conf. Intell. Syst. Mol. Biol. (ISMB), 8:3–12, 2000.

    Google Scholar 

  5. S. Batzoglou, L. Pachter, J. Mesirov, B. Berger, and E. Lander. Comparative analysis of mouse and human DNA and applications to exon prediction. Proc. Int. Conf. Comp. Mol. Biol. (RECOMB), 4, 2000.

    Google Scholar 

  6. J. Bentley. Programming Pearls. Addison-Wesley, Reading, Massachusetts, 1986.

    Google Scholar 

  7. M.S. Boguski, R.C. Hardison, S. Schwartz, and W. Miller. Analysis of conserved domains and sequence motifs in cellular regulatory proteins and locus control regions using new software tools for multiple alignment and visualization. New Biol., 4:247–260, 1992.

    Google Scholar 

  8. S. Hannenhalli and S. Levy. Promoter prediction in the human genome. Bioinformatics, 17:S90–S96, 2001.

    Google Scholar 

  9. R.C. Hardison, D. Krane, C. Vandenbergh, J.-F.F. Cheng, J. Mansberger, J. Taddie, S. Schwartz, X. Huang, and W. Miller. Sequence and comparative analysis of the rabbit alpha-like globin gene cluster reveals a rapid mode of evolution in a G+C rich region of mammalian genomes. J. Mol. Biol., 222:233–249, 1991.

    Article  Google Scholar 

  10. R.C. Hardison, J.L. Slighton, D.L. Gumucio, M. Goodman, N. Stojanovic, and W. Miller. Locus control regions of mammalian beta-globin gene clusters: combining phylogenetic analyses and experimental results to gain functional insights. Gene, 205:73–94, 1997.

    Article  Google Scholar 

  11. X. Huang. An algorithm for identifying regions of a DNA sequence that satisfy a content requirement. CABIOS, 10:219–225, 1994.

    Google Scholar 

  12. A. Nekrutenko and W.-H. Li. Assessment of compositional heterogeneity within and between eukaryotic genomes. Genome Research, 10:1986–1995, 2000.

    Article  Google Scholar 

  13. P.S. Novichkov, M.S. Gelfand, and A.A. Mironov. Prediction of the exon-intron structure by comparison sequences. Mol. Biol., 34:200–206, 2000.

    Article  Google Scholar 

  14. P. Rice, I. Longden, and A. Bleasby. EMBOSS: the European molecular biology open software suite. Trends Genet., 16:276–277, 2000.

    Article  Google Scholar 

  15. N. Stojanovic, L. Florea, C. Riemer, D. Gumucio, J. Slightom, M. Goodman, W. Miller, and R. Hardison. Comparison of five method for finding conserved sequences in multiple alignments of gene regulatory regions. Nucleic Acids Research, 27:3899–3910, 1999.

    Article  Google Scholar 

  16. B.Y. Wu, K.-M. Chao, and C. Y. Tang. An efficient algorithm for the length-constrained heaviest path problem on a tree. Infomation Processing Letters, 69:63–67, 1999.

    Article  MathSciNet  Google Scholar 

  17. Z. Zhang, P. Berman, and W. Miller. Alignments without low-scoring regions. J. Comput. Biol., 5:197–200, 1998.

    Article  Google Scholar 

  18. Z. Zhang, P. Berman, T. Wiehe, and W. Miller. Post-processing long pairwise alignments. Bioinformatics, 15:1012–1019, 1999.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Management, Providence University, 200 Chung Chi Road, Shalu, Taichung County, Taiwan, 433

    Yaw-Ling Lin, Tao Jiang & Kun-Mao Chao

  2. Department of Computer Science and Engineering, University of California Riverside, Riverside, CA, 92521-0144, USA

    Yaw-Ling Lin, Tao Jiang & Kun-Mao Chao

  3. Department of Life Science, National Yang-Ming University, Taipei, Taiwan, 112

    Yaw-Ling Lin, Tao Jiang & Kun-Mao Chao

Authors
  1. Yaw-Ling Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tao Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kun-Mao Chao
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Informatics, Warsaw University, ul. Banacha 2, 02-097, Warszawa, Poland

    Krzysztof Diks  & Wojciech Rytter  & 

  2. Department of Computer Science, Liverpool University, Peach Street, Liverpool, L69 7ZF, UK

    Wojciech Rytter

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lin, YL., Jiang, T., Chao, KM. (2002). Efficient Algorithms for Locating the Length-Constrained Heaviest Segments, with Applications to Biomolecular Sequence Analysis. In: Diks, K., Rytter, W. (eds) Mathematical Foundations of Computer Science 2002. MFCS 2002. Lecture Notes in Computer Science, vol 2420. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45687-2_38

Download citation

  • DOI: https://doi.org/10.1007/3-540-45687-2_38

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44040-6

  • Online ISBN: 978-3-540-45687-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation