Skip to main content
SpringerLink
Log in

Complexity Study on Two Clustering Problems

Extended Abstract

  • Conference paper
  • First Online:
Algorithms and Computation (ISAAC 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2223))

Included in the following conference series:

Abstract

The complexity issues of two clustering problems are studied. We prove that the Smooth Clustering and Biclustering problems are NP-hard; we also propose an 0.5 approximation algorithm and 0.8 inapproximability for a simplified clutering problem.

Supported in part by a NSTB grant.

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. A. Alizadeh et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature 403(2000), 503–510.

    Article  Google Scholar 

  2. A. Ben-Dor, Z. Yakhini. Clustering gene expression patterns. In Proceedings of Recomb’99, 33–42.

    Google Scholar 

  3. Y. Chen, E. Dougherty, M. Bitter. Ratio-based decisions and the quantitative analysis of cDNA microarray images. J. Biomed. Optics 2 (1997), 364–374.

    Article  Google Scholar 

  4. Y. Cheng and G. Church. Biclustering of expression data, In Proceedings of ISMB’2000, 93–103.

    Google Scholar 

  5. M. B. Eisen, P. T. Spellman, P. O. Browns, D. Botstein. Clustering Analysis and display of genome-wide expression pattern. PNAS 95(1998), 14863–68.

    Google Scholar 

  6. M. R. Garey and D. Johnson. Computers and Intractability: A Guide to the Theory of NP-completeness. San Francisco: Freeman, 1979.

    MATH  Google Scholar 

  7. E. Hartuv, A. Schmitt, J. Lange, S. Meier-Ewert, H. Lehrach, and R. Shamir. An algorithm for clustering cDNAs for gene expression analysis, In Proceedings of Recomb’99, 188–197.

    Google Scholar 

  8. P. Tamayo, D. Slonim, J. Mesirov, Q. Zhu, S. Kitareewan, E. Dmitrovskay, E. S. Lander, T. R. Gloub. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. PNAS 96(1999), 2907–12.

    Google Scholar 

  9. O. Troyanskaya, M. Cantor, O. Alter, G. Sherlock, P. Brown, D. Botstein, R. Tibshirani, T. Hastie, and R. Altamn. Missing value estimation methods for DNA microarrays. Bioinformatics 17(2001), 520–525.

    Article  Google Scholar 

  10. L. Zhang and S. Zhu. A new approach to clustering gene expression data. Submitted for publication.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bioinformatics Lab, Kent Ridge Digital Labs, Singapore

    Louxin Zhang

  2. Department of Mathematics & KRDL, National University of Singapore, 117543, Singapore

    Song Zhu

Authors
  1. Louxin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Song Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Basser Department of Computer Science, University of Sydney, Madsen Building F09, 2006, Sydney, NSW, Australia

    Peter Eades

  2. Department of Computer Science, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

    Tadao Takaoka

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, L., Zhu, S. (2001). Complexity Study on Two Clustering Problems. In: Eades, P., Takaoka, T. (eds) Algorithms and Computation. ISAAC 2001. Lecture Notes in Computer Science, vol 2223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45678-3_56

Download citation

  • DOI: https://doi.org/10.1007/3-540-45678-3_56

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42985-2

  • Online ISBN: 978-3-540-45678-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation