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Journal Abstract Search

141 related items for PubMed ID: 28885159

  • 21. A density-based clustering approach for identifying overlapping protein complexes with functional preferences.
    Hu L, Chan KC.
    BMC Bioinformatics; 2015 May 27; 16():174. PubMed ID: 26013799
    [Abstract] [Full Text] [Related]

  • 22. 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 27; 63(3):181-9. PubMed ID: 25765008
    [Abstract] [Full Text] [Related]

  • 23. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.
    Shen X, Yi L, Jiang X, He T, Yang J, Xie W, Hu P, Hu X.
    PLoS One; 2017 Mar 27; 12(10):e0186134. PubMed ID: 29045465
    [Abstract] [Full Text] [Related]

  • 24. 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
    [Abstract] [Full Text] [Related]

  • 25. Temporal Protein Complex Identification Based on Dynamic Heterogeneous Protein Information Network Representation Learning.
    Li Z, Zhang Y, Zhou P.
    IEEE/ACM Trans Comput Biol Bioinform; 2024 Dec 08; 21(5):1154-1164. PubMed ID: 38190662
    [Abstract] [Full Text] [Related]

  • 26. A novel essential protein identification method based on PPI networks and gene expression data.
    Zhong J, Tang C, Peng W, Xie M, Sun Y, Tang Q, Xiao Q, Yang J.
    BMC Bioinformatics; 2021 May 13; 22(1):248. PubMed ID: 33985429
    [Abstract] [Full Text] [Related]

  • 27. 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]

  • 28. Identifying hierarchical and overlapping protein complexes based on essential protein-protein interactions and "seed-expanding" method.
    Ren J, Zhou W, Wang J.
    Biomed Res Int; 2014 Dec 01; 2014():838714. PubMed ID: 25143945
    [Abstract] [Full Text] [Related]

  • 29. Dynamic protein interaction network construction and applications.
    Wang J, Peng X, Peng W, Wu FX.
    Proteomics; 2014 Mar 01; 14(4-5):338-52. PubMed ID: 24339054
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  • 30. Identifying essential proteins from active PPI networks constructed with dynamic gene expression.
    Xiao Q, Wang J, Peng X, Wu FX, Pan Y.
    BMC Genomics; 2015 Mar 01; 16 Suppl 3(Suppl 3):S1. PubMed ID: 25707432
    [Abstract] [Full Text] [Related]

  • 31. A method for identifying protein complexes with the features of joint co-localization and joint co-expression in static PPI networks.
    Zhang J, Zhong C, Huang Y, Lin HX, Wang M.
    Comput Biol Med; 2019 Aug 01; 111():103333. PubMed ID: 31376777
    [Abstract] [Full Text] [Related]

  • 32. iOPTICS-GSO for identifying protein complexes from dynamic PPI networks.
    Lei X, Li H, Zhang A, Wu FX.
    BMC Med Genomics; 2017 Dec 28; 10(Suppl 5):80. PubMed ID: 29297344
    [Abstract] [Full Text] [Related]

  • 33. Exploiting locational and topological overlap model to identify modules in protein interaction networks.
    Cheng L, Liu P, Wang D, Leung KS.
    BMC Bioinformatics; 2019 Jan 14; 20(1):23. PubMed ID: 30642247
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  • 34. Predicting Essential Proteins by Integrating Network Topology, Subcellular Localization Information, Gene Expression Profile and GO Annotation Data.
    Zhang W, Xu J, Zou X.
    IEEE/ACM Trans Comput Biol Bioinform; 2020 Jan 14; 17(6):2053-2061. PubMed ID: 31095490
    [Abstract] [Full Text] [Related]

  • 35. 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]

  • 36. A Construction Method of Dynamic Protein Interaction Networks by Using Relevant Features of Gene Expression Data.
    Sun J, Pan L, Li B, Wang H, Yang B, Li W.
    IEEE/ACM Trans Comput Biol Bioinform; 2023 Oct 12; 20(5):2790-2801. PubMed ID: 37030714
    [Abstract] [Full Text] [Related]

  • 37. CPredictor3.0: detecting protein complexes from PPI networks with expression data and functional annotations.
    Xu Y, Zhou J, Zhou S, Guan J.
    BMC Syst Biol; 2017 Dec 21; 11(Suppl 7):135. PubMed ID: 29322927
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  • 38. Predicting overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods.
    Dimitrakopoulos C, Theofilatos K, Pegkas A, Likothanassis S, Mavroudi S.
    Artif Intell Med; 2016 Jul 21; 71():62-9. PubMed ID: 27506132
    [Abstract] [Full Text] [Related]

  • 39. Protein complexes predictions within protein interaction networks using genetic algorithms.
    Ramadan E, Naef A, Ahmed M.
    BMC Bioinformatics; 2016 Jul 25; 17 Suppl 7(Suppl 7):269. PubMed ID: 27454228
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  • 40. A method for predicting protein complex in dynamic PPI networks.
    Zhang Y, Lin H, Yang Z, Wang J, Liu Y, Sang S.
    BMC Bioinformatics; 2016 Jul 25; 17 Suppl 7(Suppl 7):229. PubMed ID: 27454775
    [Abstract] [Full Text] [Related]

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