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

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.