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Journal Abstract Search

137 related items for PubMed ID: 22961456

  • 1. Employing functional interactions for characterisation and detection of sparse complexes from yeast PPI networks.
    Srihari S, Leong HW.
    Int J Bioinform Res Appl; 2012; 8(3-4):286-304. PubMed ID: 22961456
    [Abstract] [Full Text] [Related]

  • 2. MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure.
    Srihari S, Ning K, Leong HW.
    BMC Bioinformatics; 2010 Oct 12; 11():504. PubMed ID: 20939868
    [Abstract] [Full Text] [Related]

  • 3. Identifying conserved protein complexes between species by constructing interolog networks.
    Nguyen PV, Srihari S, Leong HW.
    BMC Bioinformatics; 2013 Oct 12; 14 Suppl 16(Suppl 16):S8. PubMed ID: 24564762
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. Protein complex prediction via dense subgraphs and false positive analysis.
    Hernandez C, Mella C, Navarro G, Olivera-Nappa A, Araya J.
    PLoS One; 2017 Dec 01; 12(9):e0183460. PubMed ID: 28937982
    [Abstract] [Full Text] [Related]

  • 6. 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
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  • 8. 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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  • 10. Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data.
    You ZH, Lei YK, Gui J, Huang DS, Zhou X.
    Bioinformatics; 2010 Nov 01; 26(21):2744-51. PubMed ID: 20817744
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  • 13. Identification of protein complexes by integrating multiple alignment of protein interaction networks.
    Ma CY, Chen YP, Berger B, Liao CS.
    Bioinformatics; 2017 Jun 01; 33(11):1681-1688. PubMed ID: 28130237
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  • 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 01; 63(3):181-9. PubMed ID: 25765008
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  • 15. 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
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  • 17. 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 Mar 14; 12(1):179-92. PubMed ID: 26357088
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  • 19. 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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