Chen Bolin, Fan Weiwei, Liu Juan, Wu Fang-Xiang
School of Computer, Wuhan University, Wuhan 430072, China. Tel.: +86-27-6877-5711; Fax: +86-27-6877-5711;
Brief Bioinform. 2014 Mar;15(2):177-94. doi: 10.1093/bib/bbt039. Epub 2013 Jun 18.
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.
细胞过程通常由蛋白质复合物和功能模块来执行。识别它们对于我们揭示细胞组织和功能原理的尝试起着重要作用。在本文中，我们综述了从蛋白质 - 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。然后基于所使用的数据类型和涉及的主要思想，我们简要描述四类蛋白质复合物和/或功能模块识别算法：（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）基于多数据整合的算法；以及（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，并且蛋白质复合物的研究将通过从静态PPI网络转向动态PPI网络而受益。
