Inferring candidate regulatory networks in human breast cancer cells

Abstract

Human cell regulatory mechanism is one of suspicious problems among biologists. Here we tried to uncover the human breast cancer cell regulatory mechanism from gene expression data (Marc J. Van de vijver, et.al.,2002) using a module network algorithm which is suggested by Segal, et. al.(2003) Finally, we derived a module network which consists of 50 modules and 10 tree depths. Moreover, to validate this candidate network, we applied a GO enrichment test and known transcription factor-target relationships from Transfac® (V. Matys, et.al, 2006) and HPRD database (Peri, S. et al. ,2003).