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首页> 外文期刊>Briefings in bioinformatics >Identifying protein complexes and functional modules?from static PPI networks to dynamic PPI networks
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Identifying protein complexes and functional modules?from static PPI networks to dynamic PPI networks

机译:识别蛋白质复合物和功能模块-从静态PPI网络到动态PPI网络

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摘要

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.
机译:细胞过程通常通过蛋白质复合物和功能模块来进行。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,我们回顾了用于从蛋白质-蛋白质相互作用(PPI)网络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,我们将蛋白质复杂和/或功能模块识别算法简要描述为四类:(i)基于未加权PPI网络的拓扑结构的算法; (ii)基于加权PPI网络特征的那些; (iii)基于多个数据集成的数据; (iv)基于动态PPI网络的网络。当整合更多类型的数据时,PPI网络的建模将越来越精确,蛋白质复合物的研究将从静态PPI网络向动态PPI网络的转变中受益。

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