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Journal Abstract Search

164 related items for PubMed ID: 26329886

  • 41. 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; 11(4):616-27. PubMed ID: 26356332
    [Abstract] [Full Text] [Related]

  • 42. Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.
    Wang J, Xie D, Lin H, Yang Z, Zhang Y.
    Proteome Sci; 2012 Jun 21; 10 Suppl 1(Suppl 1):S18. PubMed ID: 22759576
    [Abstract] [Full Text] [Related]

  • 43. Learning the structure of protein-protein interaction networks.
    Kuchaiev O, Przulj N.
    Pac Symp Biocomput; 2009 Jun 21; ():39-50. PubMed ID: 19209694
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  • 45. A supervised protein complex prediction method with network representation learning and gene ontology knowledge.
    Wang X, Zhang Y, Zhou P, Liu X.
    BMC Bioinformatics; 2022 Jul 25; 23(1):300. PubMed ID: 35879648
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  • 47. Effective identification of essential proteins based on priori knowledge, network topology and gene expressions.
    Li M, Zheng R, Zhang H, Wang J, Pan Y.
    Methods; 2014 Jun 01; 67(3):325-33. PubMed ID: 24565748
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  • 49. 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]

  • 50. Predicting protein complex in protein interaction network - a supervised learning based method.
    Yu F, Yang Z, Tang N, Lin H, Wang J, Yang Z.
    BMC Syst Biol; 2014 Sep 14; 8 Suppl 3(Suppl 3):S4. PubMed ID: 25349902
    [Abstract] [Full Text] [Related]

  • 51. Identifying Protein Complexes With Clear Module Structure Using Pairwise Constraints in Protein Interaction Networks.
    Liu G, Liu B, Li A, Wang X, Yu J, Zhou X.
    Front Genet; 2021 Sep 14; 12():664786. PubMed ID: 34512712
    [Abstract] [Full Text] [Related]

  • 52. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.
    An JY, You ZH, Meng FR, Xu SJ, Wang Y.
    Int J Mol Sci; 2016 May 18; 17(5):. PubMed ID: 27213337
    [Abstract] [Full Text] [Related]

  • 53. Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.
    Luo J, Qi Y.
    PLoS One; 2015 May 18; 10(6):e0131418. PubMed ID: 26125187
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  • 54. Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks.
    Palukuri MV, Marcotte EM.
    PLoS One; 2021 May 18; 16(12):e0262056. PubMed ID: 34972161
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  • 56. A density-based approach for detecting complexes in weighted PPI networks by semantic similarity.
    Zhou H, Liu J, Li J, Duan W.
    PLoS One; 2017 May 18; 12(7):e0180570. PubMed ID: 28704455
    [Abstract] [Full Text] [Related]

  • 57. Protein complex identification based on weighted PPI network with multi-source information.
    Yu Y, Zheng Z.
    J Theor Biol; 2019 Sep 21; 477():77-83. PubMed ID: 31199958
    [Abstract] [Full Text] [Related]

  • 58. Predicting protein complexes using a supervised learning method combined with local structural information.
    Dong Y, Sun Y, Qin C.
    PLoS One; 2018 Sep 21; 13(3):e0194124. PubMed ID: 29554120
    [Abstract] [Full Text] [Related]

  • 59. Detecting Protein Complexes Based on Uncertain Graph Model.
    Zhao B, Wang J, Li M, Wu FX, Pan Y.
    IEEE/ACM Trans Comput Biol Bioinform; 2014 Sep 21; 11(3):486-97. PubMed ID: 26356017
    [Abstract] [Full Text] [Related]

  • 60. United Complex Centrality for Identification of Essential Proteins from PPI Networks.
    Li M, Lu Y, Niu Z, Wu FX.
    IEEE/ACM Trans Comput Biol Bioinform; 2017 Sep 21; 14(2):370-380. PubMed ID: 28368815
    [Abstract] [Full Text] [Related]

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