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223 related items for PubMed ID: 20958996
21. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network. Shen X, Yi L, Jiang X, He T, Yang J, Xie W, Hu P, Hu X. PLoS One; 2017; 12(10):e0186134. PubMed ID: 29045465 [Abstract] [Full Text] [Related]
22. An integrated approach to identify protein complex based on best neighbour and modularity increment. Shen X, Zhao Y, Li Y, Yi Y, He T, Yang J. Int J Data Min Bioinform; 2015; 11(4):458-73. PubMed ID: 26336669 [Abstract] [Full Text] [Related]
23. Protein complex prediction via dense subgraphs and false positive analysis. Hernandez C, Mella C, Navarro G, Olivera-Nappa A, Araya J. PLoS One; 2017; 12(9):e0183460. PubMed ID: 28937982 [Abstract] [Full Text] [Related]
24. Identifying protein complexes from interactome based on essential proteins and local fitness method. Wang J, Chen G, Liu B, Li M, Pan Y. IEEE Trans Nanobioscience; 2012 Dec; 11(4):324-35. PubMed ID: 22711784 [Abstract] [Full Text] [Related]
25. Large-scale mapping of human protein interactome using structural complexes. Tyagi M, Hashimoto K, Shoemaker BA, Wuchty S, Panchenko AR. EMBO Rep; 2012 Mar 01; 13(3):266-71. PubMed ID: 22261719 [Abstract] [Full Text] [Related]
26. Protein complexes predictions within protein interaction networks using genetic algorithms. Ramadan E, Naef A, Ahmed M. BMC Bioinformatics; 2016 Jul 25; 17 Suppl 7(Suppl 7):269. PubMed ID: 27454228 [Abstract] [Full Text] [Related]
27. A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection. Mehranfar A, Ghadiri N, Kouhsar M, Golshani A. Comput Biol Med; 2017 Sep 01; 88():18-31. PubMed ID: 28672176 [Abstract] [Full Text] [Related]
28. Identifying protein complexes based on node embeddings obtained from protein-protein interaction networks. Liu X, Yang Z, Sang S, Zhou Z, Wang L, Zhang Y, Lin H, Wang J, Xu B. BMC Bioinformatics; 2018 Sep 21; 19(1):332. PubMed ID: 30241459 [Abstract] [Full Text] [Related]
29. AVID: an integrative framework for discovering functional relationships among proteins. Jiang T, Keating AE. BMC Bioinformatics; 2005 Jun 01; 6():136. PubMed ID: 15929793 [Abstract] [Full Text] [Related]
30. Visualization and analysis of the complexome network of Saccharomyces cerevisiae. Li SS, Xu K, Wilkins MR. J Proteome Res; 2011 Oct 07; 10(10):4744-56. PubMed ID: 21842913 [Abstract] [Full Text] [Related]
31. Detecting Protein Complexes Based on Uncertain Graph Model. Zhao B, Wang J, Li M, Wu FX, Pan Y. IEEE/ACM Trans Comput Biol Bioinform; 2014 Oct 07; 11(3):486-97. PubMed ID: 26356017 [Abstract] [Full Text] [Related]
32. A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality. Hart GT, Lee I, Marcotte ER. BMC Bioinformatics; 2007 Jul 02; 8():236. PubMed ID: 17605818 [Abstract] [Full Text] [Related]
33. LePrimAlign: local entropy-based alignment of PPI networks to predict conserved modules. Maskey S, Cho YR. BMC Genomics; 2019 Dec 24; 20(Suppl 9):964. PubMed ID: 31874635 [Abstract] [Full Text] [Related]
34. A Seed Expansion Graph Clustering Method for Protein Complexes Detection in Protein Interaction Networks. Wang J, Zheng W, Qian Y, Liang J. Molecules; 2017 Dec 08; 22(12):. PubMed ID: 29292776 [Abstract] [Full Text] [Related]
35. Markov clustering versus affinity propagation for the partitioning of protein interaction graphs. Vlasblom J, Wodak SJ. BMC Bioinformatics; 2009 Mar 30; 10():99. PubMed ID: 19331680 [Abstract] [Full Text] [Related]
36. Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme. Kritikos GD, Moschopoulos C, Vazirgiannis M, Kossida S. BMC Bioinformatics; 2011 Jun 16; 12():239. PubMed ID: 21679454 [Abstract] [Full Text] [Related]
37. Identifying protein complexes based on density and modularity in protein-protein interaction network. Ren J, Wang J, Li M, Wang L. BMC Syst Biol; 2013 Jun 16; 7 Suppl 4(Suppl 4):S12. PubMed ID: 24565048 [Abstract] [Full Text] [Related]
38. Identifying protein complexes from interaction networks based on clique percolation and distance restriction. Wang J, Liu B, Li M, Pan Y. BMC Genomics; 2010 Nov 02; 11 Suppl 2(Suppl 2):S10. PubMed ID: 21047377 [Abstract] [Full Text] [Related]
39. HKC: an algorithm to predict protein complexes in protein-protein interaction networks. Wang X, Wang Z, Ye J. J Biomed Biotechnol; 2011 Nov 02; 2011():480294. PubMed ID: 22174556 [Abstract] [Full Text] [Related]
40. NETAL: a new graph-based method for global alignment of protein-protein interaction networks. Neyshabur B, Khadem A, Hashemifar S, Arab SS. Bioinformatics; 2013 Jul 01; 29(13):1654-62. PubMed ID: 23696650 [Abstract] [Full Text] [Related] Page: [Previous] [Next] [New Search]