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Journal Abstract Search

203 related items for PubMed ID: 17261034

  • 1. A novel approach using pharmacophore ensemble/support vector machine (PhE/SVM) for prediction of hERG liability.
    Leong MK.
    Chem Res Toxicol; 2007 Feb; 20(2):217-26. PubMed ID: 17261034
    [Abstract] [Full Text] [Related]

  • 2. Combined receptor and ligand-based approach to the universal pharmacophore model development for studies of drug blockade to the hERG1 pore domain.
    Durdagi S, Duff HJ, Noskov SY.
    J Chem Inf Model; 2011 Feb 28; 51(2):463-74. PubMed ID: 21241063
    [Abstract] [Full Text] [Related]

  • 3. Insights for human ether-a-go-go-related gene potassium channel inhibition using recursive partitioning and Kohonen and Sammon mapping techniques.
    Ekins S, Balakin KV, Savchuk N, Ivanenkov Y.
    J Med Chem; 2006 Aug 24; 49(17):5059-71. PubMed ID: 16913696
    [Abstract] [Full Text] [Related]

  • 4. A comprehensive support vector machine binary hERG classification model based on extensive but biased end point hERG data sets.
    Shen MY, Su BH, Esposito EX, Hopfinger AJ, Tseng YJ.
    Chem Res Toxicol; 2011 Jun 20; 24(6):934-49. PubMed ID: 21504223
    [Abstract] [Full Text] [Related]

  • 5. hERG classification model based on a combination of support vector machine method and GRIND descriptors.
    Li Q, Jørgensen FS, Oprea T, Brunak S, Taboureau O.
    Mol Pharm; 2008 Jun 20; 5(1):117-27. PubMed ID: 18197627
    [Abstract] [Full Text] [Related]

  • 6. Classification models for HERG inhibitors by counter-propagation neural networks.
    Thai KM, Ecker GF.
    Chem Biol Drug Des; 2008 Oct 20; 72(4):279-89. PubMed ID: 18844674
    [Abstract] [Full Text] [Related]

  • 7. Combining cluster analysis, feature selection and multiple support vector machine models for the identification of human ether-a-go-go related gene channel blocking compounds.
    Nisius B, Göller AH, Bajorath J.
    Chem Biol Drug Des; 2009 Jan 20; 73(1):17-25. PubMed ID: 19152631
    [Abstract] [Full Text] [Related]

  • 8. A composite model for HERG blockade.
    Kramer C, Beck B, Kriegl JM, Clark T.
    ChemMedChem; 2008 Feb 20; 3(2):254-65. PubMed ID: 18061919
    [Abstract] [Full Text] [Related]

  • 9. A novel structure-based virtual screening model for the hERG channel blockers.
    Du L, Li M, You Q, Xia L.
    Biochem Biophys Res Commun; 2007 Apr 20; 355(4):889-94. PubMed ID: 17331468
    [Abstract] [Full Text] [Related]

  • 10. Prospective validation of a comprehensive in silico hERG model and its applications to commercial compound and drug databases.
    Doddareddy MR, Klaasse EC, Shagufta, Ijzerman AP, Bender A.
    ChemMedChem; 2010 May 03; 5(5):716-29. PubMed ID: 20349498
    [Abstract] [Full Text] [Related]

  • 11. Application of support vector machine (SVM) for prediction toxic activity of different data sets.
    Zhao CY, Zhang HX, Zhang XY, Liu MC, Hu ZD, Fan BT.
    Toxicology; 2006 Jan 16; 217(2-3):105-19. PubMed ID: 16213080
    [Abstract] [Full Text] [Related]

  • 12. Bias-correction of regression models: a case study on hERG inhibition.
    Hansen K, Rathke F, Schroeter T, Rast G, Fox T, Kriegl JM, Mika S.
    J Chem Inf Model; 2009 Jun 16; 49(6):1486-96. PubMed ID: 19435326
    [Abstract] [Full Text] [Related]

  • 13. Prediction of hERG potassium channel affinity by the CODESSA approach.
    Coi A, Massarelli I, Murgia L, Saraceno M, Calderone V, Bianucci AM.
    Bioorg Med Chem; 2006 May 01; 14(9):3153-9. PubMed ID: 16426850
    [Abstract] [Full Text] [Related]

  • 14. In silico binary classification QSAR models based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage.
    Su BH, Shen MY, Esposito EX, Hopfinger AJ, Tseng YJ.
    J Chem Inf Model; 2010 Jul 26; 50(7):1304-18. PubMed ID: 20565102
    [Abstract] [Full Text] [Related]

  • 15. Quantitative structure-activity relationship models for predicting biological properties, developed by combining structure- and ligand-based approaches: an application to the human ether-a-go-go-related gene potassium channel inhibition.
    Coi A, Massarelli I, Saraceno M, Carli N, Testai L, Calderone V, Bianucci AM.
    Chem Biol Drug Des; 2009 Oct 26; 74(4):416-33. PubMed ID: 19751420
    [Abstract] [Full Text] [Related]

  • 16. A binary QSAR model for classification of hERG potassium channel blockers.
    Thai KM, Ecker GF.
    Bioorg Med Chem; 2008 Apr 01; 16(7):4107-19. PubMed ID: 18243713
    [Abstract] [Full Text] [Related]

  • 17. Side chain flexibilities in the human ether-a-go-go related gene potassium channel (hERG) together with matched-pair binding studies suggest a new binding mode for channel blockers.
    Zachariae U, Giordanetto F, Leach AG.
    J Med Chem; 2009 Jul 23; 52(14):4266-76. PubMed ID: 19534531
    [Abstract] [Full Text] [Related]

  • 18. A QSAR model of HERG binding using a large, diverse, and internally consistent training set.
    Seierstad M, Agrafiotis DK.
    Chem Biol Drug Des; 2006 Apr 23; 67(4):284-96. PubMed ID: 16629826
    [Abstract] [Full Text] [Related]

  • 19. Towards in silico identification of the human ether-a-go-go-related gene channel blockers: discriminative vs. generative classification models.
    Kireeva N, Kuznetsov SL, Bykov AA, Tsivadze AY.
    SAR QSAR Environ Res; 2013 Apr 23; 24(2):103-17. PubMed ID: 23152964
    [Abstract] [Full Text] [Related]

  • 20. Determination of hERG channel blockers using a decision tree.
    Gepp MM, Hutter MC.
    Bioorg Med Chem; 2006 Aug 01; 14(15):5325-32. PubMed ID: 16616507
    [Abstract] [Full Text] [Related]

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