BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 30821317)

  • 1. Functional geometry of protein interactomes.
    Malod-Dognin N; Pržulj N
    Bioinformatics; 2019 Oct; 35(19):3727-3734. PubMed ID: 30821317
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Higher-order molecular organization as a source of biological function.
    Gaudelet T; Malod-Dognin N; Pržulj N
    Bioinformatics; 2018 Sep; 34(17):i944-i953. PubMed ID: 30423061
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Graphlet Laplacians for topology-function and topology-disease relationships.
    Windels SFL; Malod-Dognin N; Pržulj N
    Bioinformatics; 2019 Dec; 35(24):5226-5234. PubMed ID: 31192358
    [TBL] [Abstract][Full Text] [Related]  

  • 4. L-GRAAL: Lagrangian graphlet-based network aligner.
    Malod-Dognin N; Pržulj N
    Bioinformatics; 2015 Jul; 31(13):2182-9. PubMed ID: 25725498
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fuse: multiple network alignment via data fusion.
    Gligorijević V; Malod-Dognin N; Pržulj N
    Bioinformatics; 2016 Apr; 32(8):1195-203. PubMed ID: 26668003
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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; 63(3):181-9. PubMed ID: 25765008
    [TBL] [Abstract][Full Text] [Related]  

  • 7. How and when should interactome-derived clusters be used to predict functional modules and protein function?
    Song J; Singh M
    Bioinformatics; 2009 Dec; 25(23):3143-50. PubMed ID: 19770263
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks.
    Ou-Yang L; Yan H; Zhang XF
    BMC Bioinformatics; 2017 Dec; 18(Suppl 13):463. PubMed ID: 29219066
    [TBL] [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; 12(9):e0183460. PubMed ID: 28937982
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Graphlet-based edge clustering reveals pathogen-interacting proteins.
    Solava RW; Michaels RP; Milenkovic T
    Bioinformatics; 2012 Sep; 28(18):i480-i486. PubMed ID: 22962470
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Efficient estimation of graphlet frequency distributions in protein-protein interaction networks.
    Przulj N; Corneil DG; Jurisica I
    Bioinformatics; 2006 Apr; 22(8):974-80. PubMed ID: 16452112
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Centralities in simplicial complexes. Applications to protein interaction networks.
    Estrada E; Ross GJ
    J Theor Biol; 2018 Feb; 438():46-60. PubMed ID: 29128505
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Probabilistic graphlets capture biological function in probabilistic molecular networks.
    Doria-Belenguer S; Youssef MK; Böttcher R; Malod-Dognin N; Pržulj N
    Bioinformatics; 2020 Dec; 36(Suppl_2):i804-i812. PubMed ID: 33381834
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Modeling interactome: scale-free or geometric?
    Przulj N; Corneil DG; Jurisica I
    Bioinformatics; 2004 Dec; 20(18):3508-15. PubMed ID: 15284103
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computational probing protein-protein interactions targeting small molecules.
    Wang YC; Chen SL; Deng NY; Wang Y
    Bioinformatics; 2016 Jan; 32(2):226-34. PubMed ID: 26415726
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identifying functional modules in interaction networks through overlapping Markov clustering.
    Shih YK; Parthasarathy S
    Bioinformatics; 2012 Sep; 28(18):i473-i479. PubMed ID: 22962469
    [TBL] [Abstract][Full Text] [Related]  

  • 17. GLIDE: combining local methods and diffusion state embeddings to predict missing interactions in biological networks.
    Devkota K; Murphy JM; Cowen LJ
    Bioinformatics; 2020 Jul; 36(Suppl_1):i464-i473. PubMed ID: 32657369
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identifying protein complexes by reducing noise in interaction networks.
    Liao B; Fu X; Cai L; Chen H
    Protein Pept Lett; 2014 Jul; 21(7):688-95. PubMed ID: 24654850
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Proper evaluation of alignment-free network comparison methods.
    Yaveroğlu ÖN; Milenković T; Pržulj N
    Bioinformatics; 2015 Aug; 31(16):2697-704. PubMed ID: 25810431
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.