Open Access Methodology article

Learning contextual gene set interaction networks of cancer with condition specificity

Sungwon Jung1, Michael Verdicchio2, Jeff Kiefer3, Daniel Von Hoff4, Michael Berens5, Michael Bittner6 and Seungchan Kim1*

Author Affiliations

1 Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, Arizona, USA

2 School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, USA

3 Pharmaceutical Genomics Division, Translational Genomics Research Institute, Phoenix, Arizona, USA

4 Clinical Translational Research Division, Translational Genomics Research Institute, Phoenix, Arizona, USA

5 Cancer and Cell Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA

6 Computational Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA

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BMC Genomics 2013, 14:110  doi:10.1186/1471-2164-14-110

Published: 19 February 2013

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Additional file 1:

supplementary_information.pdf, 507K.

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Additional file 2:

Figure S1. The summarized gene set expression data of refractory cancer patients.

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Additional file 3:

supplementary_data.xls, 3406K.

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Additional file 4:

Figure S2. The heat maps of cancer-generic region and tissue specific regions from the refractory cancer contextual gene set interaction network.

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Additional file 5:

Figure S3. The summarized gene set expression data of GBM samples from TCGA.

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Additional file 6:

Figure S4. The heat maps of GBM-generic region and GBM subtype-specific regions from the TCGA-GBM contextual gene set interaction network.

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