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Journal Abstract Search
155 related items for PubMed ID: 24818139
41. Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data. Li M, Wu X, Wang J, Pan Y. BMC Bioinformatics; 2012 May 23; 13():109. PubMed ID: 22621308 [Abstract] [Full Text] [Related]
42. A novel subgradient-based optimization algorithm for blockmodel functional module identification. Wang Y, Qian X. BMC Bioinformatics; 2013 May 23; 14 Suppl 2(Suppl 2):S23. PubMed ID: 23368964 [Abstract] [Full Text] [Related]
43. An efficient protein complex mining algorithm based on Multistage Kernel Extension. Shen X, Zhao Y, Li Y, He T, Yang J, Hu X. BMC Bioinformatics; 2014 May 23; 15 Suppl 12(Suppl 12):S7. PubMed ID: 25474367 [Abstract] [Full Text] [Related]
44. A New Method for Detecting Protein Complexes based on the Three Node Cliques. Zhang W, Zou X. IEEE/ACM Trans Comput Biol Bioinform; 2015 May 23; 12(4):879-86. PubMed ID: 26357329 [Abstract] [Full Text] [Related]
45. Identifying protein complexes based on an edge weight algorithm and core-attachment structure. Wang R, Liu G, Wang C. BMC Bioinformatics; 2019 Sep 14; 20(1):471. PubMed ID: 31521132 [Abstract] [Full Text] [Related]
46. From the static interactome to dynamic protein complexes: Three challenges. Yong CH, Wong L. J Bioinform Comput Biol; 2015 Apr 14; 13(2):1571001. PubMed ID: 25653145 [Abstract] [Full Text] [Related]
47. A max-flow-based approach to the identification of protein complexes using protein interaction and microarray data. Feng J, Jiang R, Jiang T. IEEE/ACM Trans Comput Biol Bioinform; 2011 Apr 14; 8(3):621-34. PubMed ID: 20733237 [Abstract] [Full Text] [Related]
48. The relative vertex clustering value--a new criterion for the fast discovery of functional modules in protein interaction networks. Ibrahim ZM, Ngom A. BMC Bioinformatics; 2015 Apr 14; 16 Suppl 4(Suppl 4):S3. PubMed ID: 25734691 [Abstract] [Full Text] [Related]
49. Detecting protein complexes in a PPI network: a gene ontology based multi-objective evolutionary approach. Mukhopadhyay A, Ray S, De M. Mol Biosyst; 2012 Nov 14; 8(11):3036-48. PubMed ID: 22990765 [Abstract] [Full Text] [Related]
50. Identifying protein complexes based on the integration of PPI network and gene expression data. Chen W, Li M, Wu X, Wang J. Int J Bioinform Res Appl; 2015 Nov 14; 11(1):30-44. PubMed ID: 25667384 [Abstract] [Full Text] [Related]
51. Development of an in silico method for the identification of subcomplexes involved in the biogenesis of multiprotein complexes in Saccharomyces cerevisiae. Glatigny A, Gambette P, Bourand-Plantefol A, Dujardin G, Mucchielli-Giorgi MH. BMC Syst Biol; 2017 Jul 11; 11(1):67. PubMed ID: 28693620 [Abstract] [Full Text] [Related]
52. A new algorithm for essential proteins identification based on the integration of protein complex co-expression information and edge clustering coefficient. Luo J, Wu J. Int J Data Min Bioinform; 2015 Jul 11; 12(3):257-74. PubMed ID: 26510286 [Abstract] [Full Text] [Related]
53. 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]
55. A fast hierarchical clustering algorithm for functional modules discovery in protein interaction networks. Wang J, Li M, Chen J, Pan Y. IEEE/ACM Trans Comput Biol Bioinform; 2011 Jul 02; 8(3):607-20. PubMed ID: 20733244 [Abstract] [Full Text] [Related]
59. Integrating network topology, gene expression data and GO annotation information for protein complex prediction. Zhang W, Xu J, Li Y, Zou X. J Bioinform Comput Biol; 2019 Feb 02; 17(1):1950001. PubMed ID: 30803297 [Abstract] [Full Text] [Related]
60. Predicting physical interactions between protein complexes. Clancy T, Rødland EA, Nygard S, Hovig E. Mol Cell Proteomics; 2013 Jun 02; 12(6):1723-34. PubMed ID: 23438732 [Abstract] [Full Text] [Related] Page: [Previous] [Next] [New Search]