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Journal Abstract Search

375 related items for PubMed ID: 30572820

  • 1. 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]

  • 2. 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]

  • 3. Identification of core-attachment complexes based on maximal frequent patterns in protein-protein interaction networks.
    Yu L, Gao L, Kong C.
    Proteomics; 2011 Oct 24; 11(19):3826-34. PubMed ID: 21761565
    [Abstract] [Full Text] [Related]

  • 4. Detection of protein complexes from multiple protein interaction networks using graph embedding.
    Liu X, Yang Z, Sang S, Lin H, Wang J, Xu B.
    Artif Intell Med; 2019 May 24; 96():107-115. PubMed ID: 31164203
    [Abstract] [Full Text] [Related]

  • 5. Identifying protein complexes based on brainstorming strategy.
    Shen X, Zhou J, Yi L, Hu X, He T, Yang J.
    Methods; 2016 Nov 01; 110():44-53. PubMed ID: 27405005
    [Abstract] [Full Text] [Related]

  • 6. DPCMNE: Detecting Protein Complexes From Protein-Protein Interaction Networks Via Multi-Level Network Embedding.
    Meng X, Xiang J, Zheng R, Wu FX, Li M.
    IEEE/ACM Trans Comput Biol Bioinform; 2022 Nov 01; 19(3):1592-1602. PubMed ID: 33417563
    [Abstract] [Full Text] [Related]

  • 7. Protein complex prediction in large ontology attributed protein-protein interaction networks.
    Zhang Y, Lin H, Yang Z, Wang J, Li Y, Xu B.
    IEEE/ACM Trans Comput Biol Bioinform; 2013 Nov 01; 10(3):729-41. PubMed ID: 24091405
    [Abstract] [Full Text] [Related]

  • 8. Discovering protein complexes in protein interaction networks via exploring the weak ties effect.
    Ma X, Gao L.
    BMC Syst Biol; 2012 Nov 01; 6 Suppl 1(Suppl 1):S6. PubMed ID: 23046740
    [Abstract] [Full Text] [Related]

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

  • 10. 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 01; 19(5):e1800129. PubMed ID: 30650262
    [Abstract] [Full Text] [Related]

  • 11. 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 01; 12(1):179-92. PubMed ID: 26357088
    [Abstract] [Full Text] [Related]

  • 12. An efficient protein complex mining algorithm based on Multistage Kernel Extension.
    Shen X, Zhao Y, Li Y, He T, Yang J, Hu X.
    BMC Bioinformatics; 2014 Mar 01; 15 Suppl 12(Suppl 12):S7. PubMed ID: 25474367
    [Abstract] [Full Text] [Related]

  • 13. MOEPGA: A novel method to detect protein complexes in yeast protein-protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm.
    Cao B, Luo J, Liang C, Wang S, Song D.
    Comput Biol Chem; 2015 Oct 01; 58():173-81. PubMed ID: 26298638
    [Abstract] [Full Text] [Related]

  • 14. 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]

  • 15. 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]

  • 16. Identification of protein complexes from multi-relationship protein interaction networks.
    Li X, Wang J, Zhao B, Wu FX, Pan Y.
    Hum Genomics; 2016 Jul 25; 10 Suppl 2(Suppl 2):17. PubMed ID: 27461193
    [Abstract] [Full Text] [Related]

  • 17. 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
    [Abstract] [Full Text] [Related]

  • 18. Improving protein complex prediction by reconstructing a high-confidence protein-protein interaction network of Escherichia coli from different physical interaction data sources.
    Taghipour S, Zarrineh P, Ganjtabesh M, Nowzari-Dalini A.
    BMC Bioinformatics; 2017 Jan 03; 18(1):10. PubMed ID: 28049415
    [Abstract] [Full Text] [Related]

  • 19. Detecting protein complexes in a PPI network: a gene ontology based multi-objective evolutionary approach.
    Mukhopadhyay A, Ray S, De M.
    Mol Biosyst; 2012 Nov 03; 8(11):3036-48. PubMed ID: 22990765
    [Abstract] [Full Text] [Related]

  • 20. 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 03; 71():62-9. PubMed ID: 27506132
    [Abstract] [Full Text] [Related]

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