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

Lang Li, 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 Nephew

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Motivation: To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-α (ERα), we developed an innovative mixture model-based discriminate analysis for identifying ordered TFBS pairs. Results: Biologically, our proposed new algorithm clearly suggesTFBSs are not randomly distributed within ERα 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 ERα 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.

Original languageEnglish
Pages (from-to)2210-2216
Number of pages7
JournalBioinformatics
Volume22
Issue number18
DOIs
StatePublished - Sep 15 2006

Fingerprint

Estrogen Receptor
Transcription factors
Binding sites
Transcription Factor
Mixture Model
Promoter
Estrogen Receptors
Transcription Factors
Genes
Binding Sites
Model-based
Gene
Target
Pattern Recognition
Pattern recognition
Estrogens
Prediction

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-α. / Li, Lang; Cheng, Alfred S L; Jin, Victor X.; Paik, Henry H.; Fan, Meiyun; Li, Xiaoman; Zhang, Wei; Robarge, Jason; Balch, Curtis; Davuluri, Ramana V.; Kim, Sun; Huang, Tim H M; Nephew, Kenneth.

In: Bioinformatics, Vol. 22, No. 18, 15.09.2006, p. 2210-2216.

Research output: Contribution to journalArticle

Li, L, Cheng, ASL, Jin, VX, Paik, HH, Fan, M, Li, X, Zhang, W, Robarge, J, Balch, C, Davuluri, RV, Kim, S, Huang, THM & Nephew, K 2006, 'A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-α', Bioinformatics, vol. 22, no. 18, pp. 2210-2216. https://doi.org/10.1093/bioinformatics/btl329
Li, Lang ; Cheng, Alfred S L ; Jin, Victor X. ; Paik, Henry H. ; Fan, Meiyun ; Li, Xiaoman ; Zhang, Wei ; Robarge, Jason ; Balch, Curtis ; Davuluri, Ramana V. ; Kim, Sun ; Huang, Tim H M ; Nephew, Kenneth. / A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-α. In: Bioinformatics. 2006 ; Vol. 22, No. 18. pp. 2210-2216.
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