CPL: Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network

被引:0
作者
Qi-Guo Dai
Mao-Zu Guo
Xiao-Yan Liu
Zhi-Xia Teng
Chun-Yu Wang
机构
[1] Harbin Institute of Technology,School of Computer Science and Technology
[2] Northeast Forestry University,School of Information and Computer Engineering
来源
Journal of Computer Science and Technology | 2014年 / 29卷
关键词
protein complex detection; label propagation; protein-protein interaction; graph clustering; bioinformatics;
D O I
暂无
中图分类号
学科分类号
摘要
Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.
引用
收藏
页码:1083 / 1093
页数:10
相关论文
共 93 条
  • [11] Li X(2006)-connected subgraphs in protein interaction network Journal of Proteome Research 5 801-1584
  • [12] Wu M(2006)Fast and accurate method for identifying high-quality protein-interaction modules by clique merging and its application to yeast BMC Bioinformatics 7 207-730
  • [13] Kwoh CK(2003)Development and implementation of an algorithm for detection of protein complexes in large interaction networks BMC Bioinformatics 4 2-3048
  • [14] Wang J(2009)An automated method for finding molecular complexes in large protein interaction networks BMC Bioinformatics 10 169-2468
  • [15] Li M(2006)A core-attachment based method to detect protein complexes in PPI networks Bioinformatics 22 1021-93
  • [16] Deng Y(2005)CFinder: Locating cliques and overlapping modules in biological networks Nature 435 814-D539
  • [17] Nepusz T(2013)Uncovering the overlapping community structure of complex networks in nature and society Proteome Science 11 S18-D451
  • [18] Yu H(2002)Detecting overlapping protein complexes in PPI networks based on robustness Nucleic Acids Research 30 1575-D44
  • [19] Paccanaro A(2012)An e±cient algorithm for large-scale detection of protein families IEEE/ACM Transactions on Computational Biology and Bioinformatics 9 717-831
  • [20] Becker E(2012)A co-clustering approach for mining largeprotein-protein interaction networks Molecular BioSystems 8 3036-479