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Cleaning microarray expression data using Markov random fields based on profile similarity

Published: 13 March 2005 Publication History

Abstract

This paper proposes a method for cleaning the noise found in microarray expression data sets. While other methods either concentrate on the image processing phase, or apply normalization techniques to the resulting microarray raw expression values, we introduce a method based on Markov random fields for the data set. The cleaning process is guided by genes with similar expression profiles. As a result, data cleaning is conducted using biological similarity of genes.

References

[1]
J. M. Hammersley and P. Clifford. Markov field on finite graphs and lattices. Unpublished, 1971.
[2]
M. Katzer, F. Kummert, and G. Sagerer. Methods for automatic microarray image segmentation. 2(4):202--214, December 2003.
[3]
J. Kubica and A. Moore. Probabilistic noise identification and data cleaning. In X. Wu. A. Tuzhilin, and J. Shavlik, editors, Proc. 3rd IEEE International Conference on Data Mining, pages 131--138, November 2003.
[4]
S. Z. Li. Markov Random Field Modeling in Image Analysis. Computer Science Workbench. Springer-Verlag, 2001.
[5]
Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed. Normalization for cDNA microarray data. In Proc. SPIE International Biomedical Optics Symposium, pages 120--129, November 2003.

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  1. Cleaning microarray expression data using Markov random fields based on profile similarity

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      cover image ACM Conferences
      SAC '05: Proceedings of the 2005 ACM symposium on Applied computing
      March 2005
      1814 pages
      ISBN:1581139640
      DOI:10.1145/1066677
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      Published: 13 March 2005

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      Author Tags

      1. data cleaning
      2. markov random fields
      3. microarray expression profile similarity

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      SAC05
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      SAC05: The 2005 ACM Symposium on Applied Computing
      March 13 - 17, 2005
      New Mexico, Santa Fe

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      Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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