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Journal Abstract Search

133 related items for PubMed ID: 23566214

  • 1. Improved method for protein complex detection using bottleneck proteins.
    Ahn J, Lee DH, Yoon Y, Yeu Y, Park S.
    BMC Med Inform Decis Mak; 2013; 13 Suppl 1(Suppl 1):S5. PubMed ID: 23566214
    [Abstract] [Full Text] [Related]

  • 2. A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks.
    Ou-Yang L, Yan H, Zhang XF.
    BMC Bioinformatics; 2017 Dec 01; 18(Suppl 13):463. PubMed ID: 29219066
    [Abstract] [Full Text] [Related]

  • 3. Protein complex prediction in interaction network based on network motif.
    Patra S, Mohapatra A.
    Comput Biol Chem; 2020 Dec 01; 89():107399. PubMed ID: 33152665
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  • 5. Development and implementation of an algorithm for detection of protein complexes in large interaction networks.
    Altaf-Ul-Amin M, Shinbo Y, Mihara K, Kurokawa K, Kanaya S.
    BMC Bioinformatics; 2006 Apr 14; 7():207. PubMed ID: 16613608
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  • 6. Detection of protein complexes using a protein ranking algorithm.
    Zaki N, Berengueres J, Efimov D.
    Proteins; 2012 Oct 14; 80(10):2459-68. PubMed ID: 22685080
    [Abstract] [Full Text] [Related]

  • 7. 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 Oct 14; 11(4):616-27. PubMed ID: 26356332
    [Abstract] [Full Text] [Related]

  • 8. C-element: a new clustering algorithm to find high quality functional modules in PPI networks.
    Ghasemi M, Rahgozar M, Bidkhori G, Masoudi-Nejad A.
    PLoS One; 2013 Oct 14; 8(9):e72366. PubMed ID: 24039752
    [Abstract] [Full Text] [Related]

  • 9. Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.
    He J, Li C, Ye B, Zhong W.
    BMC Bioinformatics; 2012 Jun 25; 13 Suppl 10(Suppl 10):S19. PubMed ID: 22759424
    [Abstract] [Full Text] [Related]

  • 10. 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 25; 63(3):181-9. PubMed ID: 25765008
    [Abstract] [Full Text] [Related]

  • 11. Protein complex prediction via dense subgraphs and false positive analysis.
    Hernandez C, Mella C, Navarro G, Olivera-Nappa A, Araya J.
    PLoS One; 2017 Mar 25; 12(9):e0183460. PubMed ID: 28937982
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  • 14. 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
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  • 16. 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
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  • 17. An effective approach to detecting both small and large complexes from protein-protein interaction networks.
    Xu B, Wang Y, Wang Z, Zhou J, Zhou S, Guan J.
    BMC Bioinformatics; 2017 Oct 16; 18(Suppl 12):419. PubMed ID: 29072136
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  • 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. Using indirect protein-protein interactions for protein complex prediction.
    Chua HN, Ning K, Sung WK, Leong HW, Wong L.
    J Bioinform Comput Biol; 2008 Jun 12; 6(3):435-66. PubMed ID: 18574858
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  • 20. Protein complex prediction via cost-based clustering.
    King AD, Przulj N, Jurisica I.
    Bioinformatics; 2004 Nov 22; 20(17):3013-20. PubMed ID: 15180928
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