Identification of protein complexes by overlapping community detection algorithms: A comparative study

Milica Jaguzović, Milana Grbić, Marko Ðukanović, Dragan Matic
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引用次数: 1

Abstract

Community detection is of a major interest in network analysis. In this study several overlapping community detection algorithms are applied on different protein-protein interactions (PPIs) networks (BioGRID, String and WI-PHI) in order to examine their capability to identify protein complexes. Several community detection algorithms implemented in CDLIB Python library are examined. Obtained communities are further evaluated against four different gold standards of protein complexes from literature. The accuracy of the methods applied on the PPIs networks is examined by statistical measures designed to cope with overlapping partitions. The experimental results indicate that the community detection algorithms are more successful on BioGRID and WI-PHI networks, obtaining a relatively high accuracy in several cases.
用重叠群落检测算法鉴定蛋白质复合体:比较研究
社区检测是网络分析中的一个重要问题。在这项研究中,几种重叠社区检测算法应用于不同的蛋白质-蛋白质相互作用(PPIs)网络(BioGRID, String和WI-PHI),以检查它们识别蛋白质复合物的能力。研究了在CDLIB Python库中实现的几种社区检测算法。根据文献中的四种不同的蛋白质复合物金标准进一步评估获得的群落。应用于PPIs网络的方法的准确性通过设计用于处理重叠分区的统计措施进行检查。实验结果表明,社区检测算法在BioGRID和WI-PHI网络上更成功,在一些情况下获得了较高的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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