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370 related items for PubMed ID: 22305895

  • 1. Identification of human protein complexes from local sub-graphs of protein-protein interaction network based on random forest with topological structure features.
    Li ZC, Lai YH, Chen LL, Zhou X, Dai Z, Zou XY.
    Anal Chim Acta; 2012 Mar 09; 718():32-41. PubMed ID: 22305895
    [Abstract] [Full Text] [Related]

  • 2. Identifying subcellular localizations of mammalian protein complexes based on graph theory with a random forest algorithm.
    Li ZC, Lai YH, Chen LL, Chen C, Xie Y, Dai Z, Zou XY.
    Mol Biosyst; 2013 Apr 05; 9(4):658-67. PubMed ID: 23429850
    [Abstract] [Full Text] [Related]

  • 3. Identifying protein complexes using hybrid properties.
    Chen L, Shi X, Kong X, Zeng Z, Cai YD.
    J Proteome Res; 2009 Nov 05; 8(11):5212-8. PubMed ID: 19764809
    [Abstract] [Full Text] [Related]

  • 4. Fitting a geometric graph to a protein-protein interaction network.
    Higham DJ, Rasajski M, Przulj N.
    Bioinformatics; 2008 Apr 15; 24(8):1093-9. PubMed ID: 18344248
    [Abstract] [Full Text] [Related]

  • 5. Combining functional and topological properties to identify core modules in protein interaction networks.
    Lubovac Z, Gamalielsson J, Olsson B.
    Proteins; 2006 Sep 01; 64(4):948-59. PubMed ID: 16794996
    [Abstract] [Full Text] [Related]

  • 6. Identifying functions of protein complexes based on topology similarity with random forest.
    Li ZC, Lai YH, Chen LL, Xie Y, Dai Z, Zou XY.
    Mol Biosyst; 2014 Mar 04; 10(3):514-25. PubMed ID: 24389559
    [Abstract] [Full Text] [Related]

  • 7. Protein complex prediction with RNSC.
    King AD, Pržulj N, Jurisica I.
    Methods Mol Biol; 2012 Mar 04; 804():297-312. PubMed ID: 22144160
    [Abstract] [Full Text] [Related]

  • 8. Systematic computational prediction of protein interaction networks.
    Lees JG, Heriche JK, Morilla I, Ranea JA, Orengo CA.
    Phys Biol; 2011 Jun 04; 8(3):035008. PubMed ID: 21572181
    [Abstract] [Full Text] [Related]

  • 9. [The study on the characters of membrane protein interaction and its network based on integrated intelligence method].
    Shen Y, Ding Y, Hao K.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Aug 04; 28(4):658-62. PubMed ID: 21936357
    [Abstract] [Full Text] [Related]

  • 10. Assessment of protein domain fusions in human protein interaction networks prediction: application to the human kinetochore model.
    Morilla I, Lees JG, Reid AJ, Orengo C, Ranea JA.
    N Biotechnol; 2010 Dec 31; 27(6):755-65. PubMed ID: 20851221
    [Abstract] [Full Text] [Related]

  • 11. Protein complex prediction via cost-based clustering.
    King AD, Przulj N, Jurisica I.
    Bioinformatics; 2004 Nov 22; 20(17):3013-20. PubMed ID: 15180928
    [Abstract] [Full Text] [Related]

  • 12. Identifying components of complexes.
    Goffard N, Weiller G.
    Methods Mol Biol; 2008 Nov 22; 453():257-65. PubMed ID: 18712308
    [Abstract] [Full Text] [Related]

  • 13. Discovering functional interdependence relationship in PPI networks for protein complex identification.
    Lam WW, Chan KC.
    IEEE Trans Biomed Eng; 2012 Apr 22; 59(4):899-908. PubMed ID: 21095855
    [Abstract] [Full Text] [Related]

  • 14. Large-scale identification of human protein function using topological features of interaction network.
    Li Z, Liu Z, Zhong W, Huang M, Wu N, Xie Y, Dai Z, Zou X.
    Sci Rep; 2016 Nov 16; 6():37179. PubMed ID: 27849060
    [Abstract] [Full Text] [Related]

  • 15. 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 16; 8(11):3036-48. PubMed ID: 22990765
    [Abstract] [Full Text] [Related]

  • 16. From pull-down data to protein interaction networks and complexes with biological relevance.
    Zhang B, Park BH, Karpinets T, Samatova NF.
    Bioinformatics; 2008 Apr 01; 24(7):979-86. PubMed ID: 18304937
    [Abstract] [Full Text] [Related]

  • 17. Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.
    Theofilatos K, Pavlopoulou N, Papasavvas C, Likothanassis S, Dimitrakopoulos C, Georgopoulos E, Moschopoulos C, Mavroudi S.
    Artif Intell Med; 2015 Mar 01; 63(3):181-9. PubMed ID: 25765008
    [Abstract] [Full Text] [Related]

  • 18. A degree-distribution based hierarchical agglomerative clustering algorithm for protein complexes identification.
    Yu L, Gao L, Li K, Zhao Y, Chiu DK.
    Comput Biol Chem; 2011 Oct 12; 35(5):298-307. PubMed ID: 22000801
    [Abstract] [Full Text] [Related]

  • 19. Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps.
    Nabieva E, Jim K, Agarwal A, Chazelle B, Singh M.
    Bioinformatics; 2005 Jun 12; 21 Suppl 1():i302-10. PubMed ID: 15961472
    [Abstract] [Full Text] [Related]

  • 20. Identifying protein complexes based on multiple topological structures in PPI networks.
    Chen B, Wu FX.
    IEEE Trans Nanobioscience; 2013 Sep 12; 12(3):165-72. PubMed ID: 23974659
    [Abstract] [Full Text] [Related]

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