Aparna Rai
Indian Institute of Technology-Indore , India
Title: Randomness and preserved patterns in cancer network
Biography
Biography: Aparna Rai
Abstract
Breast cancer has been reported to account for the maximum cases among all female cancers till date. Complexity as well as variations at every stage of the cancer renders designing drug targets very difficult. The ample availability of data in functional genomic and proteomic information and the development of high-throughput data-collection techniques have resulted from basic gene-based traditional molecular biology to a systems approach of network biology. In this approach, biological processes are considered as complex networks of interactions between numerous components of the cell rather than as independent interactions involving only a few molecules. We analyze the breast cancer network and its normal counterpart at the proteomic level. The spectral analysis reflects that robustness of the overall system is decreased in the disease but the interactions of the important proteins involved in promoting the disease are preserved and might be one of the reasons behind making those pathways involved with the important proteins highly resistant to various treatments. Detection of important proteins involved in breast cancer using random matrix theory platform provides a time efficient and cost effective approach for those diseases, which lack in-depth information about important genes. The analysis provides a benchmark for designing drugs, which can target a sub graph instead of individual proteins.