BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

146 related articles for article (PubMed ID: 34213534)

  • 1. Linear functional organization of the omic embedding space.
    Xenos A; Malod-Dognin N; Milinković S; Pržulj N
    Bioinformatics; 2021 Nov; 37(21):3839-3847. PubMed ID: 34213534
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A functional analysis of omic network embedding spaces reveals key altered functions in cancer.
    Doria-Belenguer S; Xenos A; Ceddia G; Malod-Dognin N; Pržulj N
    Bioinformatics; 2023 May; 39(5):. PubMed ID: 37084262
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Text mining-based word representations for biomedical data analysis and protein-protein interaction networks in machine learning tasks.
    Alachram H; Chereda H; Beißbarth T; Wingender E; Stegmaier P
    PLoS One; 2021; 16(10):e0258623. PubMed ID: 34653224
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Identifying cellular cancer mechanisms through pathway-driven data integration.
    Windels SFL; Malod-Dognin N; Pržulj N
    Bioinformatics; 2022 Sep; 38(18):4344-4351. PubMed ID: 35916710
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding.
    Cannistraci CV; Alanis-Lobato G; Ravasi T
    Bioinformatics; 2013 Jul; 29(13):i199-209. PubMed ID: 23812985
    [TBL] [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; 19(3):1592-1602. PubMed ID: 33417563
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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; 19(1):535. PubMed ID: 30572820
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases.
    Scherer P; Trębacz M; Simidjievski N; Viñas R; Shams Z; Terre HA; Jamnik M; Liò P
    Bioinformatics; 2022 Feb; 38(5):1320-1327. PubMed ID: 34888618
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. Fitting a geometric graph to a protein-protein interaction network.
    Higham DJ; Rasajski M; Przulj N
    Bioinformatics; 2008 Apr; 24(8):1093-9. PubMed ID: 18344248
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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; 96():107-115. PubMed ID: 31164203
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Mining hidden knowledge: embedding models of cause-effect relationships curated from the biomedical literature.
    Krämer A; Green J; Billaud JN; Pasare NA; Jones M; Tugendreich S
    Bioinform Adv; 2022; 2(1):vbac022. PubMed ID: 36699407
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The axes of biology: a novel axes-based network embedding paradigm to decipher the functional mechanisms of the cell.
    Doria-Belenguer S; Xenos A; Ceddia G; Malod-Dognin N; Pržulj N
    Bioinform Adv; 2024; 4(1):vbae075. PubMed ID: 38827411
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Adversarial deconfounding autoencoder for learning robust gene expression embeddings.
    Dincer AB; Janizek JD; Lee SI
    Bioinformatics; 2020 Dec; 36(Suppl_2):i573-i582. PubMed ID: 33381842
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Integration of molecular network data reconstructs Gene Ontology.
    Gligorijević V; Janjić V; Pržulj N
    Bioinformatics; 2014 Sep; 30(17):i594-600. PubMed ID: 25161252
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. iSOM-GSN: an integrative approach for transforming multi-omic data into gene similarity networks via self-organizing maps.
    Fatima N; Rueda L
    Bioinformatics; 2020 Aug; 36(15):4248-4254. PubMed ID: 32407457
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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; 26(21):2744-51. PubMed ID: 20817744
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.