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Journal Abstract Search

122 related items for PubMed ID: 21155019

  • 1. A method based on local density and random walks for complexes detection in protein interaction networks.
    Yu L, Gao L, Li K.
    J Bioinform Comput Biol; 2010 Dec; 8 Suppl 1():47-62. PubMed ID: 21155019
    [Abstract] [Full Text] [Related]

  • 2. 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]

  • 3. A core-attachment based method to detect protein complexes in PPI networks.
    Wu M, Li X, Kwoh CK, Ng SK.
    BMC Bioinformatics; 2009 Jun 02; 10():169. PubMed ID: 19486541
    [Abstract] [Full Text] [Related]

  • 4. Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure.
    Peng W, Wang J, Zhao B, Wang L.
    IEEE/ACM Trans Comput Biol Bioinform; 2015 Jun 02; 12(1):179-92. PubMed ID: 26357088
    [Abstract] [Full Text] [Related]

  • 5. Neighbor Affinity-Based Core-Attachment Method to Detect Protein Complexes in Dynamic PPI Networks.
    Lei X, Liang J.
    Molecules; 2017 Jul 24; 22(7):. PubMed ID: 28737728
    [Abstract] [Full Text] [Related]

  • 6. Protein Complexes Prediction Method Based on Core-Attachment Structure and Functional Annotations.
    Li B, Liao B.
    Int J Mol Sci; 2017 Sep 06; 18(9):. PubMed ID: 28878201
    [Abstract] [Full Text] [Related]

  • 7. Identifying protein complexes and functional modules--from static PPI networks to dynamic PPI networks.
    Chen B, Fan W, Liu J, Wu FX.
    Brief Bioinform; 2014 Mar 06; 15(2):177-94. PubMed ID: 23780996
    [Abstract] [Full Text] [Related]

  • 8. From Function to Interaction: A New Paradigm for Accurately Predicting Protein Complexes Based on Protein-to-Protein Interaction Networks.
    Xu B, Guan J.
    IEEE/ACM Trans Comput Biol Bioinform; 2014 Mar 06; 11(4):616-27. PubMed ID: 26356332
    [Abstract] [Full Text] [Related]

  • 9. Identification of core-attachment complexes based on maximal frequent patterns in protein-protein interaction networks.
    Yu L, Gao L, Kong C.
    Proteomics; 2011 Oct 06; 11(19):3826-34. PubMed ID: 21761565
    [Abstract] [Full Text] [Related]

  • 10. Interaction graph mining for protein complexes using local clique merging.
    Li XL, Tan SH, Foo CS, Ng SK.
    Genome Inform; 2005 Oct 06; 16(2):260-9. PubMed ID: 16901108
    [Abstract] [Full Text] [Related]

  • 11. 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 06; 17(1):1950001. PubMed ID: 30803297
    [Abstract] [Full Text] [Related]

  • 12. RRW: repeated random walks on genome-scale protein networks for local cluster discovery.
    Macropol K, Can T, Singh AK.
    BMC Bioinformatics; 2009 Sep 09; 10():283. PubMed ID: 19740439
    [Abstract] [Full Text] [Related]

  • 13. Identification of Protein Complexes Based on Core-Attachment Structure and Combination of Centrality Measures and Biological Properties in PPI Weighted Networks.
    Elahi A, Babamir SM.
    Protein J; 2020 Dec 09; 39(6):681-702. PubMed ID: 33040223
    [Abstract] [Full Text] [Related]

  • 14. 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 09; 63(3):181-9. PubMed ID: 25765008
    [Abstract] [Full Text] [Related]

  • 15. Protein complexes identification based on go attributed network embedding.
    Xu B, Li K, Zheng W, Liu X, Zhang Y, Zhao Z, He Z.
    BMC Bioinformatics; 2018 Dec 20; 19(1):535. PubMed ID: 30572820
    [Abstract] [Full Text] [Related]

  • 16. Impact of low-confidence interactions on computational identification of protein complexes.
    Paul M, Anand A.
    J Bioinform Comput Biol; 2020 Aug 20; 18(4):2050025. PubMed ID: 32757809
    [Abstract] [Full Text] [Related]

  • 17. A Novel Core-Attachment-Based Method to Identify Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks.
    Xiao Q, Luo P, Li M, Wang J, Wu FX.
    Proteomics; 2019 Mar 20; 19(5):e1800129. PubMed ID: 30650262
    [Abstract] [Full Text] [Related]

  • 18. PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation.
    Cao B, Luo J, Liang C, Wang S, Ding P.
    IEEE Trans Nanobioscience; 2016 Oct 20; 15(7):728-738. PubMed ID: 27662678
    [Abstract] [Full Text] [Related]

  • 19. Learning the structure of protein-protein interaction networks.
    Kuchaiev O, Przulj N.
    Pac Symp Biocomput; 2009 Oct 20; ():39-50. PubMed ID: 19209694
    [Abstract] [Full Text] [Related]

  • 20. Finding low-conductance sets with dense interactions (FLCD) for better protein complex prediction.
    Wang Y, Qian X.
    BMC Syst Biol; 2017 Mar 14; 11(Suppl 3):22. PubMed ID: 28361714
    [Abstract] [Full Text] [Related]

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