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This article is part of the supplement: The 2010 International Conference on Bioinformatics and Computational Biology (BIOCOMP 2010): Systems Biology

Open Access Research article

Integration of breast cancer gene signatures based on graph centrality

Jianxin Wang1*, Gang Chen1, Min Li12 and Yi Pan12*

Author Affiliations

1 School of Information Science and Engineering, Central South University, Changsha, 410083, China

2 Department of Computer Science, Georgia State University, Atlanta, GA30303, USA

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BMC Systems Biology 2011, 5(Suppl 3):S10  doi:10.1186/1752-0509-5-S3-S10

Published: 23 December 2011

Additional files

Additional file 1:

Graph centrality of genes in the context-constrained PIN. In this study, graph centrality of each gene in the context-constrained PIN is calculated and used to quantify the relationship between genes and the breast cancer. The calculation results are provided in this additional file.

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Open Data

Additional file 2:

SC-based gene signature based hierarchical clustering analysis of breast cancer microarray dataset by using SC-based gene signature. According to the gene signature identified by SC, hierarchical clustering analysis is performed on the breast cancer microarray dataset, GSE7390, which include 198 breast cancer patients with various pathologic parameters.

Format: PDF Size: 65KB Download file

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Open Data