Literature DB >> 16809387

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

Lang Li1, Alfred S L Cheng, Victor X Jin, Henry H Paik, Meiyun Fan, Xiaoman Li, Wei Zhang, Jason Robarge, Curtis Balch, Ramana V Davuluri, Sun Kim, Tim H-M Huang, Kenneth P Nephew.   

Abstract

MOTIVATION: To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-alpha (ERalpha), 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 ERalpha 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 ERalpha 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@iupui.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2006        PMID: 16809387     DOI: 10.1093/bioinformatics/btl329

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

Review 1.  Methods for analysis in pharmacogenomics: lessons from the Pharmacogenetics Research Network Analysis Group.

Authors:  Balaji S Srinivasan; Jinbo Chen; Cheng Cheng; David Conti; Shiwei Duan; Brooke L Fridley; Xiangjun Gu; Jonathan L Haines; Eric Jorgenson; Aldi Kraja; Jessica Lasky-Su; Lang Li; Andrei Rodin; Dai Wang; Mike Province; Marylyn D Ritchie
Journal:  Pharmacogenomics       Date:  2009-02       Impact factor: 2.533

2.  A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer.

Authors:  Changyu Shen; Yiwen Huang; Yunlong Liu; Guohua Wang; Yuming Zhao; Zhiping Wang; Mingxiang Teng; Yadong Wang; David A Flockhart; Todd C Skaar; Pearlly Yan; Kenneth P Nephew; Tim Hm Huang; Lang Li
Journal:  BMC Syst Biol       Date:  2011-05-09

3.  The influence of cis-regulatory elements on DNA methylation fidelity.

Authors:  Mingxiang Teng; Curt Balch; Yunlong Liu; Meng Li; Tim H M Huang; Yadong Wang; Kenneth P Nephew; Lang Li
Journal:  PLoS One       Date:  2012-03-06       Impact factor: 3.240

4.  A systematic study of motif pairs that may facilitate enhancer-promoter interactions.

Authors:  Saidi Wang; Haiyan Hu; Xiaoman Li
Journal:  J Integr Bioinform       Date:  2022-02-07

5.  MBBC: an efficient approach for metagenomic binning based on clustering.

Authors:  Ying Wang; Haiyan Hu; Xiaoman Li
Journal:  BMC Bioinformatics       Date:  2015-02-05       Impact factor: 3.169

6.  Measuring spatial preferences at fine-scale resolution identifies known and novel cis-regulatory element candidates and functional motif-pair relationships.

Authors:  Ken Daigoro Yokoyama; Uwe Ohler; Gregory A Wray
Journal:  Nucleic Acids Res       Date:  2009-05-29       Impact factor: 16.971

7.  A Poisson mixture model to identify changes in RNA polymerase II binding quantity using high-throughput sequencing technology.

Authors:  Weixing Feng; Yunlong Liu; Jiejun Wu; Kenneth P Nephew; Tim H M Huang; Lang Li
Journal:  BMC Genomics       Date:  2008-09-16       Impact factor: 3.969

  7 in total

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