Genetic Network of Breast Cancer Metastasis in Lymph Nodes via Information Theory Algorithms

Breast cancer is a public health challenge because its high rate of growth around the world in recent decades. Breast cancer induces metastasis on diverse organs, quite hard to bound and inhibit. Metastasis is the main whatfor to cancer-associated deaths in patients. This paper introduces the matrix of gene expressions, algorithmically inferred, with data on biopsis of (GEO database) breast cancer metastasis in lymph nodes. The matrix grants for generating the gene network (GN) with each node per gene and the weighted links between genes the interaction intensity. On the base of GN structural analysis we identify the importance rank of each gene through the set of biopsis. This result is by applying information-theory-based algorithms for ranking the gene importance –in breast cancer metastasis. A brief and basic analysis focus on the higher rank genes-nodes says that, both the gene-node degree and the correlation values with the other genes support the every gene relevance.