Rai Aparna, Menon A Vipin, Jalan Sarika
Centre for Bio-Science and Bio-Medical Engineering, Indian Institute of Technology Indore, M-Block, IET-DAVV Campus, Khandwa Road, Indore 452017, India.
Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, M-Block, IET-DAVV Campus, Khandwa Road, Indore 452017, India.
Sci Rep. 2014 Sep 15;4:6368. doi: 10.1038/srep06368.
Breast cancer has been reported to account for the maximum cases among all female cancers till date. In order to gain a deeper insight into the complexities of the disease, we analyze the breast cancer network and its normal counterpart at the proteomic level. While the short range correlations in the eigenvalues exhibiting universality provide an evidence towards the importance of random connections in the underlying networks, the long range correlations along with the localization properties reveal insightful structural patterns involving functionally important proteins. The analysis provides a benchmark for designing drugs which can target a subgraph instead of individual proteins.
据报道，迄今为止，乳腺癌在所有女性癌症中占比最高。为了更深入地了解该疾病的复杂性，我们在蛋白质组学水平上分析了乳腺癌网络及其正常对应物。虽然特征值中的短程相关性表现出普遍性，这为潜在网络中随机连接的重要性提供了证据，但长程相关性以及定位特性揭示了涉及功能重要蛋白质的有洞察力的结构模式。该分析为设计能够靶向子图而非单个蛋白质的药物提供了基准。
