BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

541 related articles for article (PubMed ID: 18586719)

  • 1. Prediction of drug-target interaction networks from the integration of chemical and genomic spaces.
    Yamanishi Y; Araki M; Gutteridge A; Honda W; Kanehisa M
    Bioinformatics; 2008 Jul; 24(13):i232-40. PubMed ID: 18586719
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework.
    Yamanishi Y; Kotera M; Kanehisa M; Goto S
    Bioinformatics; 2010 Jun; 26(12):i246-54. PubMed ID: 20529913
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Supervised prediction of drug-target interactions using bipartite local models.
    Bleakley K; Yamanishi Y
    Bioinformatics; 2009 Sep; 25(18):2397-403. PubMed ID: 19605421
    [TBL] [Abstract][Full Text] [Related]  

  • 4. [Prediction of network drug target based on improved model of bipartite graph valuation].
    Liu X; Lu P; Zuo X; Chen J; Yang H; Yang Y; Gao Y
    Zhongguo Zhong Yao Za Zhi; 2012 Jan; 37(2):125-9. PubMed ID: 22737836
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Virtual screening of GPCRs: an in silico chemogenomics approach.
    Jacob L; Hoffmann B; Stoven V; Vert JP
    BMC Bioinformatics; 2008 Sep; 9():363. PubMed ID: 18775075
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Using feature selection technique for drug-target interaction networks prediction.
    Yu W; Jiang Z; Wang J; Tao R
    Curr Med Chem; 2011; 18(36):5687-93. PubMed ID: 22172073
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Protein network inference from multiple genomic data: a supervised approach.
    Yamanishi Y; Vert JP; Kanehisa M
    Bioinformatics; 2004 Aug; 20 Suppl 1():i363-70. PubMed ID: 15262821
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Supervised enzyme network inference from the integration of genomic data and chemical information.
    Yamanishi Y; Vert JP; Kanehisa M
    Bioinformatics; 2005 Jun; 21 Suppl 1():i468-77. PubMed ID: 15961492
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting drug-target interactions from chemical and genomic kernels using Bayesian matrix factorization.
    Gönen M
    Bioinformatics; 2012 Sep; 28(18):2304-10. PubMed ID: 22730431
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Drug target prediction using adverse event report systems: a pharmacogenomic approach.
    Takarabe M; Kotera M; Nishimura Y; Goto S; Yamanishi Y
    Bioinformatics; 2012 Sep; 28(18):i611-i618. PubMed ID: 22962489
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Large-scale prediction of drug-target interactions using protein sequences and drug topological structures.
    Cao DS; Liu S; Xu QS; Lu HM; Huang JH; Hu QN; Liang YZ
    Anal Chim Acta; 2012 Nov; 752():1-10. PubMed ID: 23101647
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Genome scale enzyme-metabolite and drug-target interaction predictions using the signature molecular descriptor.
    Faulon JL; Misra M; Martin S; Sale K; Sapra R
    Bioinformatics; 2008 Jan; 24(2):225-33. PubMed ID: 18037612
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers.
    Tabei Y; Pauwels E; Stoven V; Takemoto K; Yamanishi Y
    Bioinformatics; 2012 Sep; 28(18):i487-i494. PubMed ID: 22962471
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The topology of drug-target interaction networks: implicit dependence on drug properties and target families.
    Mestres J; Gregori-Puigjané E; Valverde S; Solé RV
    Mol Biosyst; 2009 Sep; 5(9):1051-7. PubMed ID: 19668871
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DINIES: drug-target interaction network inference engine based on supervised analysis.
    Yamanishi Y; Kotera M; Moriya Y; Sawada R; Kanehisa M; Goto S
    Nucleic Acids Res; 2014 Jul; 42(Web Server issue):W39-45. PubMed ID: 24838565
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.
    Xia Z; Wu LY; Zhou X; Wong ST
    BMC Syst Biol; 2010 Sep; 4 Suppl 2(Suppl 2):S6. PubMed ID: 20840733
    [TBL] [Abstract][Full Text] [Related]  

  • 18. RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.
    Wang L; You ZH; Chen X; Yan X; Liu G; Zhang W
    Curr Protein Pept Sci; 2018; 19(5):445-454. PubMed ID: 27842479
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Relating drug-protein interaction network with drug side effects.
    Mizutani S; Pauwels E; Stoven V; Goto S; Yamanishi Y
    Bioinformatics; 2012 Sep; 28(18):i522-i528. PubMed ID: 22962476
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of drug-target interactions and drug repositioning via network-based inference.
    Cheng F; Liu C; Jiang J; Lu W; Li W; Liu G; Zhou W; Huang J; Tang Y
    PLoS Comput Biol; 2012; 8(5):e1002503. PubMed ID: 22589709
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 28.