Identifying protein complexes and functional modules-from static PPI networks to dynamic PPI networks
Identifying protein complexes and functional modules-from static PPI networks to dynamic PPI networks
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DOI：
10.1093/bib/bbt039
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发表时间：
2014-03-01
影响因子：
9.5
通讯作者：
Wu, Fang-Xiang
中科院分区：
文献类型：
--
作者：
Chen, Bolin;Fan, Weiwei;Wu, Fang-Xiang
细胞过程通常由蛋白质复合物和功能模块进行。识别它们对于我们试图揭示细胞组织和功能的原理起着重要作用。在这篇文章中，我们回顾了从蛋白质-蛋白质相互作用（PPI）网络中识别蛋白质复合物和/或功能模块的计算算法。我们首先描述解释PPI网络时的问题和陷阱。然后根据所使用的数据类型和所涉及的主要思想，我们简要描述了蛋白质复合物和/或功能模块识别算法分为四类：（i）基于未加权PPI网络拓扑结构的算法;（ii）基于加权PPI网络特征的算法;（iii）基于多数据集成的算法;和（iv）基于动态PPI网络的算法。当整合更多类型的数据时，PPI网络的建模越来越精确，蛋白质复合物的研究将从静态PPI网络转向动态PPI网络。
Cellular processes are typically carried out by protein complexes and functional modules. Identifying them plays an important role for our attempt to reveal principles of cellular organizations and functions. In this article, we review computational algorithms for identifying protein complexes and/or functional modules from protein-protein interaction (PPI) networks. We first describe issues and pitfalls when interpreting PPI networks. Then based on types of data used and main ideas involved, we briefly describe protein complex and/or functional module identification algorithms in four categories: (i) those based on topological structures of unweighted PPI networks; (ii) those based on characters of weighted PPI networks; (iii) those based on multiple data integrations; and (iv) those based on dynamic PPI networks. The PPI networks are modelled increasingly precise when integrating more types of data, and the study of protein complexes would benefit by shifting from static to dynamic PPI networks.