Identification of novel 17β-estradiol (E2) target genes using cross-experiment gene expression datasets

Won Cheol Yim, Changwon Keum, Saehwan Kim, Yeojeong Cho, Byung Moo Lee, Yongeun Kwon

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

17β-estradiol (E2) is an environmental estrogen-like chemicals that is known to affect mainly reproductive functions of exposed targets. Although microarray based toxicogenomics approach allows the investigation of the potential risks of E2 in DNA level, the underling mechanisms related to their toxic effect is not fully understood. In this work, we identified genes responding toE2 by analyzing cross-experiment public gene expression datasets that studied on E2 using RankProd algorithm. We have identified 348 DEGs which play important roles in fatty acid metabolism, infection, and DNA repair. This result was also compared with conventional PubMed data mining analysis.

Original languageEnglish
Pages (from-to)25-38
Number of pages14
JournalToxicology and Environmental Health Sciences
Volume2
Issue number1
DOIs
StatePublished - 2010

Keywords

  • 17β-estradiol
  • Cross-experiment
  • DNA microarray
  • E2
  • in-silico analysis
  • Rank-Prod Algorithm
  • Risk assessment

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