TITLE:
Identification of Inference Genes in Breast Cancer Network
AUTHORS:
Keilash Chirom, Shahnawaz Ali, Md. Zubbair Malik, Romana Ishrat, R. K. Brojen Singh
KEYWORDS:
Breast Cancer, Network Theory, Inference Genes, Topological Propreties, Centrality
JOURNAL NAME:
Journal of Biosciences and Medicines,
Vol.5 No.9,
August
29,
2017
ABSTRACT: Complex breast cancer network constructed from experimentally verified seventy genes, by coordinating standard seven human protein and genome databases, follows hierarchical scale free features. Centrality based method of identification of inferred genes is implemented to this network and has predicted forty nine breast cancer genes, and nineteen non-breast cancer genes. As predicting good candidate genes before experimental analysis will save time and effort both. Fourteen genes out of nineteen are found to involve in various types of cancer and diseases, and five genes are engaged in non-cancer diseases. Some of the inferred genes need proper experimental investigation to understand fundamental roles of these genes in regulating breast cancer network.