Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data

Binhua Tang, Fei Gu, Victor X Jin

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The primary goal of modeling gene regulatory networks in human cancer is to reveal pathways governing the cancer cellular to specific phenotypes. Knowledge of cancer-specific gene regulatory networks could potentially aid to design effective intervention strategies such as introduction of a factor or drug for altering the network to avoid undesirable cancerous cellular states. This chapter presents two computational approaches to infer the underlying regulatory architecture by integrating different high-throughput experiment data in human cancer. Our gene regulatory network analysis strongly suggested that a rewired estrogen receptor α (ERα) regulated network in breast cancer cells and a rewired SMAD4 regulated network in ovarian cancer cells.

Original languageEnglish (US)
Title of host publicationStatistical Diagnostics for Cancer
Subtitle of host publicationAnalyzing High-Dimensional Data
PublisherWiley-VCH
Pages153-171
Number of pages19
Volume3
ISBN (Print)9783527332625
DOIs
StatePublished - Apr 8 2013
Externally publishedYes

Fingerprint

Gene Regulatory Networks
Ovarian Neoplasms
Genes
Breast Neoplasms
Cells
Neoplasms
Neoplasm Genes
Electric network analysis
Estrogen Receptors
Throughput
Phenotype
Pharmaceutical Preparations
Experiments

Keywords

  • Estrogen receptor α (ERα)
  • Estrogen response element (ERE)
  • Gene regulatory networks
  • Immortalized ovarian surface epithelial cell (IOSE)
  • Position weight matrices (PWM)
  • Transcription factors (TF)

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Tang, B., Gu, F., & Jin, V. X. (2013). Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data. In Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data (Vol. 3, pp. 153-171). Wiley-VCH. https://doi.org/10.1002/9783527665471.ch9

Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data. / Tang, Binhua; Gu, Fei; Jin, Victor X.

Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data. Vol. 3 Wiley-VCH, 2013. p. 153-171.

Research output: Chapter in Book/Report/Conference proceedingChapter

Tang, B, Gu, F & Jin, VX 2013, Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data. in Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data. vol. 3, Wiley-VCH, pp. 153-171. https://doi.org/10.1002/9783527665471.ch9
Tang B, Gu F, Jin VX. Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data. In Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data. Vol. 3. Wiley-VCH. 2013. p. 153-171 https://doi.org/10.1002/9783527665471.ch9
Tang, Binhua ; Gu, Fei ; Jin, Victor X. / Inference of Gene Regulatory Networks in Breast and Ovarian Cancer by Integrating Different Genomic Data. Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data. Vol. 3 Wiley-VCH, 2013. pp. 153-171
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