Open Access Research Article

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

David KY Chiu* and Yan Wang

  • * Corresponding author: David KY Chiu

Author Affiliations

Department of Computing and Information Science, University of Guelph, Guelph, ON, Canada, N1G 2W1

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EURASIP Journal on Bioinformatics and Systems Biology 2006, 2006:35809 doi:10.1155/BSB/2006/35809


The electronic version of this article is the complete one and can be found online at: http://bsb.eurasipjournals.com/content/2006/1/35809


Received:23 November 2005
Revisions received:22 May 2005
Accepted:7 June 2006
Published:13 August 2006

© 2006 D. K. Y. Chiu and Y. Wang.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.

Research Article

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