title: Using Frequent Co-expression Network to Identify Gene Clusters for Breast Cancer Prognosis.
abstract: In this paper, we investigated the use of gene co-expression network analyses to identify potential biomarkers for breast carcinoma prognosis. The network mining algorithm CODENSE is used to identify highly connected genome-wide gene co-expression networks among a variety of cancer types, and the resulted gene clusters are applied to a series of breast cancer microarray sets to categorize the patients into different groups. As a result, we have identified a set of genes that are potential biomarkers for breast cancer prognosis which can categorize the patients into two groups with distinct prognosis. We also compared the gene clusters we discovered with gene subsets identified from similar studies using other clustering algorithms.
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.forename: Kun
authors.initials: K
authors.lastname: Huang
authors.forename: Yang
authors.initials: Y
authors.lastname: Xiang
authors.forename: Ruoming
authors.initials: R
authors.lastname: Jin
keywords: CODENSE; breast cancer prognosis; co-expression network; gene cluster