Inference of dynamic networks using time-course data
Inference of dynamic networks using time-course data
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DOI：
10.1093/bib/bbt028
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发表时间：
2014-03-01
影响因子：
9.5
通讯作者：
Hwang, Daehee
中科院分区：
文献类型：
--
作者：
Kim, Yongsoo;Han, Seungmin;Hwang, Daehee
细胞通过生物网络的动态运作来执行它们的功能。动态网络根据节点（蛋白质和rna）的丰度或活性的时间变化，以及新边缘的形成和现有边缘的消失来描述生物网络的运作。全球基因组学和蛋白质组学技术可用于解码动态网络。然而，使用这些实验方法，识别节点和边缘的时间转移仍然具有挑战性。因此，介绍了几种估计网络动态拓扑和功能特征的计算方法。本文综述了这些计算方法在推断动态网络中的概念和应用，并进一步总结了估计生物网络空间转移的方法。
Cells execute their functions through dynamic operations of biological networks. Dynamic networks delineate the operation of biological networks in terms of temporal changes of abundances or activities of nodes (proteins and RNAs), as well as formation of new edges and disappearance of existing edges over time. Global genomic and proteomic technologies can be used to decode dynamic networks. However, using these experimental methods, it is still challenging to identify temporal transition of nodes and edges. Thus, several computational methods for estimating dynamic topological and functional characteristics of networks have been introduced. In this review, we summarize concepts and applications of these computational methods for inferring dynamic networks and further summarize methods for estimating spatial transition of biological networks.