Abstract
The aim of this paper is to provide a snapshot of functional networks with central nodes (hubs) relying on the behavior of genes linked to a specific interaction network. Utilizing a ‘breast cancer signature’, a Bayesian approach is applied for the construction of gene interaction networks from different populations. We demonstrate that the hub genes of the differentiating network between cancer and control states can be regarded as potential markers for breast cancer. Furthermore, the differentiating subnetworks can be informative of the phenotype and provide new knowledge about the functional interactions and molecular pathways involved in breast cancer.
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Notes
- 1.
GEO: Gene Expression Omnibus; available at https://www.ncbi.nlm.nih.gov/geo/.
- 2.
KEGG: Kyoto Encyclopedia of Genes and Genomes; available at http://www.genome.jp/kegg/.
- 3.
Wikipathways; available at http://wikipathways.org/index.php/WikiPathways.
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Chalepakis Ntellis, D.A., S. Bei, E., Kafetzopoulos, D., Zervakis, M. (2017). Assembly of Gene Expression Networks Based on a Breast Cancer Signature. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_7
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