Open Access Highly Accessed Research article

Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma

Siyuan Zheng1, William P Tansey246, Scott W Hiebert345 and Zhongming Zhao134*

Author Affiliations

1 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA

2 Department of Cell and Developmental Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA

3 Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA

4 Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA

5 Department of Biochemistry, Vanderbilt University Medical Center, Nashville, TN 37232, USA

6 Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA

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BMC Medical Genomics 2011, 4:62  doi:10.1186/1755-8794-4-62

Published: 8 August 2011

Additional files

Additional file 1:

Relationship of stepwise γ values and network scores. Red node is selected as cut-off for network identification. A, Normal-Cirrhosis Network; B, Cirrhosis-Dysplasia Network; C, Dysplasia-Early HCC Network; D, Early-Advanced HCC Network.

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Additional file 2:

Stage specific networks. Nodes represent gene products and edges represent their interactions. Colour is scaled according to gene expression fold change between two consecutive stages.

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Open Data