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Bioinformatics Advance Access originally published online on June 29, 2006
Bioinformatics 2006 22(18):2210-2216; doi:10.1093/bioinformatics/btl329
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-{alpha}

Lang Li 1,*, Alfred S. L. Cheng 2, Victor X. Jin 2, Henry H. Paik 3, Meiyun Fan 3, Xiaoman Li 1, Wei Zhang 1, Jason Robarge 1, Curtis Balch 3, Ramana V. Davuluri 2, Sun Kim 3, Tim H.-M. Huang 2 and Kenneth P. Nephew 3

1 Division of Biostatistics, Department of Medicine, Indiana University School of Medicine Indianapolis, IN 47405, USA
2 Division of Human Cancer Genetics, Department of Molecular Virology, Immunology, and Medical Genetics, Comprehensive Cancer Center, Ohio State University Columbus, OH 43210, USA
3 Medical Sciences, Indiana University School of Medicine Bloomington, IN 47405, USA

*To whom correspondence should be addressed.

Motivation: To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-{alpha} (ER{alpha}), we developed an innovative mixture model-based discriminate analysis for identifying ordered TFBS pairs.

Results: Biologically, our proposed new algorithm clearly suggests that TFBSs are not randomly distributed within ER{alpha} target promoters (P-value < 0.001). The up-regulated targets significantly (P-value < 0.01) possess TFBS pairs, (DBP, MYC), (DBP, MYC/MAX heterodimer), (DBP, USF2) and (DBP, MYOGENIN); and down-regulated ER{alpha} target genes significantly (P-value < 0.01) possess TFBS pairs, such as (DBP, c-ETS1-68), (DBP, USF2) and (DBP, MYOGENIN). Statistically, our proposed mixture model-based discriminate analysis can simultaneously perform TFBS pattern recognition, TFBS pattern selection, and target class prediction; such integrative power cannot be achieved by current methods.

Availability: The software is available on request from the authors.

Contact: lali{at}iupui.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Received on April 13, 2006; revised on May 24, 2006; accepted on June 9, 2006

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