Rai Aparna, Shinde Pramod, Jalan Sarika
1Aushadhi Open Innovation Programme, Indian Institute of Technology Guwahati, Guwahati, 781039 India.
2Discipline of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552 India.
Appl Netw Sci. 2018;3(1):51. doi: 10.1007/s41109-018-0107-y. Epub 2018 Dec 17.
The fundamental understanding of altered complex molecular interactions in a diseased condition is the key to its cure. The overall functioning of these molecules is kind of jugglers play in the cell orchestra and to anticipate these relationships among the molecules is one of the greatest challenges in modern biology and medicine. Network science turned out to be providing a successful and simple platform to understand complex interactions among healthy and diseased tissues. Furthermore, much information about the structure and dynamics of a network is concealed in the eigenvalues of its adjacency matrix. In this review, we illustrate rapid advancements in the field of network science in combination with spectral graph theory that enables us to uncover the complexities of various diseases. Interpretations laid by network science approach have solicited insights into molecular relationships and have reported novel drug targets and biomarkers in various complex diseases.
对疾病状态下复杂分子相互作用改变的基本理解是治愈疾病的关键。这些分子的整体功能就像是细胞管弦乐队中的杂耍表演，预测分子间的这些关系是现代生物学和医学面临的最大挑战之一。事实证明，网络科学为理解健康组织和患病组织之间的复杂相互作用提供了一个成功且简单的平台。此外，关于网络结构和动态的许多信息隐藏在其邻接矩阵的特征值中。在本综述中，我们阐述了网络科学领域与谱图理论相结合的快速进展，这使我们能够揭示各种疾病的复杂性。网络科学方法所做的解释引发了对分子关系的深入了解，并报道了各种复杂疾病中的新型药物靶点和生物标志物。
