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Bioinformatics Advance Access originally published online on October 28, 2004
Bioinformatics 2005 21(7):1062-1068; doi:10.1093/bioinformatics/bti094
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Extracting relations between promoter sequences and their strengths from microarray data

Hisanori Kiryu 1,2,*, Taku Oshima 1 and Kiyoshi Asai 1,2,3

1Graduate School of Information Sciences, Nara Institute of Science and Technology 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
2Computational Biology Research Center, The National Institute of Advanced Industrial Science and Technology Aomi Frontier Building 2-43 Aomi, 17F, Koto-ku, Tokyo 135-0064, Japan
3Department of Computational Biology, Faculty of Frontier Science, The University of Tokyo 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan

*To whom correspondence should be addressed.

Motivation: The relations between the promoter sequences and their strengths were extensively studied in the 1980s. Although these studies uncovered strong sequence-strength correlations, the cost of their elaborate experimental methods have been too high to be applied to a large number of promoters. On the contrary, a recent increase in the microarray data allows us to compare thousands of gene expressions with their DNA sequences.

Results: We studied the relations between the promoter sequences and their strengths using the Escherichia coli microarray data. We modeled those relations using a simple weight matrix, which was optimized with a novel support vector regression method. It was observed that several non-consensus bases in the ‘–35’ and ‘–10’ regions of promoter sequences act positively on the promoter strength and that certain consensus bases have a minor effect on the strength. We analyzed outliers for which the observed gene expressions deviate from the promoter strength predictions, and identified several genes with enhanced expressions due to multiple promoters and genes under strong regulation by transcription factors. Our method is applicable to other procaryotes for which both the promoter sequences and the microarray data are available.

Contact: hisano-k{at}is.aist-nara.ac.jp


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