Skip to main content

Approximating Border Length for DNA Microarray Synthesis

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4978))

Abstract

We study the border minimization problem (BMP), which arises in microarray synthesis to place and embed probes in the array. The synthesis is based on a light-directed chemical process in which unintended illumination may contaminate the quality of the experiments. Border length is a measure of the amount of unintended illumination and the objective of BMP is to find a placement and embedding of probes such that the border length is minimized. The problem is believed to be NP-hard. In this paper we show that BMP admits an \(O(\sqrt{n}\log^2{n})\)-approximation, where n is the number of probes to be synthesized. In the case where the placement is given in advance, we show that the problem is O(log2 n)-approximable. We also study a related problem called agreement maximization problem (AMP). In contrast to BMP, we show that AMP admits a constant approximation even when placement is not given in advance.

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. Bartal, Y.: Probabilistic approximation of metric spaces and its algorithmic applications. In: Proc. 37th FOCS, pp. 184–193 (1996)

    Google Scholar 

  2. Bonizzoni, P., Vedova, G.D.: The complexity of multiple sequence alignment with SP-score that is a metric. Theoretical Computer Science 259(1–2), 63–79 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  3. Carvalho Jr., S.A., Rahmann, S.: Improving the layout of oligonucleotide. microarrays: Pivot partitioning. In: Proc. 6th WABI, pp. 321–332 (2006)

    Google Scholar 

  4. Carvalho Jr., S.A., Rahmann, S.: Microarray layout as quadratic assignment problem. In: Proc. GCB, pp. 11–20 (2006)

    Google Scholar 

  5. Carvalho Jr., S.A., Rahmann, S.: Improving the design of genechip arrays by combining placement and embedding. In: Proc. 6th CSB, pp. 54–63 (2007)

    Google Scholar 

  6. Christofides, N.: Worst-case analysis of a new heuristic for the travelling salesman problem. Technical Report 388, Graduate School of Industrial Administration, Carnegie-Mellon University, Pittsburgh, PA (ND33) (1976)

    Google Scholar 

  7. Feng, D.F., Doolittle, R.F.: Approximation algorithms for multiple sequence alignment. Theoretical Computer Science 182(1), 233–244 (1987)

    Google Scholar 

  8. Fodor, S., Read, J.L., Pirrung, M.C., Stryer, L., Lu, A.T., Solas, D.: Light-directed, spatially addressable parallel chemical synthesis. Science 251(4995), 767–773 (1991)

    Article  Google Scholar 

  9. Gerhold, D., Rushmore, T., Caskey, C.T.: DNA chips: promising toys have become powerful tools. Trends in Biochemical Sciences 24(5), 168–173 (1999)

    Article  Google Scholar 

  10. Gąsieniec, L., Li, C.Y., Sant, P., Wong, P.W.H.: Randomized probe selection algorithm for microarray design. Journal of Theoretical Biology 248(3), 512–521 (2007)

    Article  Google Scholar 

  11. Gusfield, D.: Efficient methods for multiple sequence alignment with guaranteed error bounds. Bulletin of Mathematical Biology 55(1), 141–154 (1993)

    MATH  MathSciNet  Google Scholar 

  12. Hannenhalli, S., Hubell, E., Lipshutz, R., Pevzner, P.A.: Combinatorial algorithms for design of DNA arrays. Advances in Biochemical Engineering/Biotechnology 77, 1–19 (2002)

    Article  Google Scholar 

  13. Hirschberg, D.S.: A linear space algorithm for computing maximal common subsequences. Communications of the ACM 18(6), 341–343 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  14. Kaderali, L., Schliep, A.: Selecting signature oligonucleotides to identify organisms using DNA arrays. Bioinformatics 18, 1340–1349 (2002)

    Article  Google Scholar 

  15. Kahng, A.B., Mandoiu, I.I., Pevzner, P.A., Reda, S., Zelikovsky, A.: Scalable heuristics for design of DNA probe arrays. Journal of Computational Biology 11(2/3), 429–447 (2004)

    Article  Google Scholar 

  16. Kahng, A.B., Mandoiu, I.I., Reda, S., Xu, X., Zelikovsky, A.: Computer-aided optimization of DNA array design and manufacturing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 25(2), 305–320 (2006)

    Article  Google Scholar 

  17. Kasif, S., Weng, Z., Detri, A., Beigel, R., DeLisi, C.: A computational framework for optimal masking in the synthesis of oligonucleotide microarrays. Nucleic Acids Research 30(20), e106 (2002)

    Google Scholar 

  18. Li, F., Stormo, G.: Selection of optimal DNA oligos for gene expression arrays. Bioinformatics 17(11), 1067–1076 (2001)

    Article  Google Scholar 

  19. Rahmann, S.: The shortest common supersequence problem in a microarray production setting. Bioinformatics 19(suppl. 2), 156–161 (2003)

    Article  Google Scholar 

  20. Reinert, K., Lenhof, H.P., Mutzel, P., Mehlhorn, K., Kececioglu, J.D.: A branch-and-cut algorithm for multiple sequence alignment. In: Proc. 1st RECOMB, pp. 241–250 (1997)

    Google Scholar 

  21. Slonim, D.K., Tamayo, P., Mesirov, J.P., Golub, T.R., Lander, E.S.: Class prediction and discovery using gene expression data. In: Proc. 4th RECOMB, pp. 263–272 (2000)

    Google Scholar 

  22. Sung, W.K., Lee, W.H.: Fast and accurate probe selection algorithm for large genomes. In: Proc. 2nd CSB, pp. 65–74 (2003)

    Google Scholar 

  23. Wu, B.Y., Lancia, G., Bafna, V., Chao, K.M., Ravi, R., Tang, C.Y.: A polynomial-time approximation scheme for minimum routing cost spanning trees. SIAM Journal on Computing 29(3), 761–778 (1999)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Manindra Agrawal Dingzhu Du Zhenhua Duan Angsheng Li

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, C.Y., Wong, P.W.H., Xin, Q., Yung, F.C.C. (2008). Approximating Border Length for DNA Microarray Synthesis. In: Agrawal, M., Du, D., Duan, Z., Li, A. (eds) Theory and Applications of Models of Computation. TAMC 2008. Lecture Notes in Computer Science, vol 4978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79228-4_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-79228-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79227-7

  • Online ISBN: 978-3-540-79228-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics