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Journal Abstract Search

185 related items for PubMed ID: 17125188

  • 1. Substructure-based support vector machine classifiers for prediction of adverse effects in diverse classes of drugs.
    Bhavani S, Nagargadde A, Thawani A, Sridhar V, Chandra N.
    J Chem Inf Model; 2006; 46(6):2478-86. PubMed ID: 17125188
    [Abstract] [Full Text] [Related]

  • 2. Prediction of torsade-causing potential of drugs by support vector machine approach.
    Yap CW, Cai CZ, Xue Y, Chen YZ.
    Toxicol Sci; 2004 May; 79(1):170-7. PubMed ID: 14976348
    [Abstract] [Full Text] [Related]

  • 3. Melting point prediction employing k-nearest neighbor algorithms and genetic parameter optimization.
    Nigsch F, Bender A, van Buuren B, Tissen J, Nigsch E, Mitchell JB.
    J Chem Inf Model; 2006 May; 46(6):2412-22. PubMed ID: 17125183
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  • 5. Comparison of support vector machine and artificial neural network systems for drug/nondrug classification.
    Byvatov E, Fechner U, Sadowski J, Schneider G.
    J Chem Inf Comput Sci; 2003 May; 43(6):1882-9. PubMed ID: 14632437
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  • 6. In silico prediction of mitochondrial toxicity by using GA-CG-SVM approach.
    Zhang H, Chen QY, Xiang ML, Ma CY, Huang Q, Yang SY.
    Toxicol In Vitro; 2009 Feb; 23(1):134-40. PubMed ID: 18940245
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  • 7. Fragment-based prediction of the clinical occurrence of long QT syndrome and torsade de pointes.
    Clark M, Wiseman JS.
    J Chem Inf Model; 2009 Nov; 49(11):2617-26. PubMed ID: 19894674
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  • 8. Prediction of P-glycoprotein substrates by a support vector machine approach.
    Xue Y, Yap CW, Sun LZ, Cao ZW, Wang JF, Chen YZ.
    J Chem Inf Comput Sci; 2004 Nov; 44(4):1497-505. PubMed ID: 15272858
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  • 9. Prediction of chemical carcinogenicity by machine learning approaches.
    Tan NX, Rao HB, Li ZR, Li XY.
    SAR QSAR Environ Res; 2009 Nov; 20(1-2):27-75. PubMed ID: 19343583
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  • 11. Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine.
    Craig RA, Liao L.
    Ann N Y Acad Sci; 2007 Dec; 1115():154-67. PubMed ID: 17925357
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  • 12. Vector-G: multi-modular SVM-based heterotrimeric G protein prediction.
    Jain P, Wadhwa P, Aygun R, Podila G.
    In Silico Biol; 2008 Dec; 8(2):141-55. PubMed ID: 18928202
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  • 13. Accurate prediction of enzyme mutant activity based on a multibody statistical potential.
    Masso M, Vaisman II.
    Bioinformatics; 2007 Dec 01; 23(23):3155-61. PubMed ID: 17977887
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  • 15. Predicting protein structural class by SVM with class-wise optimized features and decision probabilities.
    Anand A, Pugalenthi G, Suganthan PN.
    J Theor Biol; 2008 Jul 21; 253(2):375-80. PubMed ID: 18423492
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  • 18. Assessing the proarrhythmic potential of drugs: current status of models and surrogate parameters of torsades de pointes arrhythmias.
    Thomsen MB, Matz J, Volders PG, Vos MA.
    Pharmacol Ther; 2006 Oct 21; 112(1):150-70. PubMed ID: 16714061
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  • 19. Preclinical assessment of drug-induced proarrhythmias: role of the arterially perfused rabbit left ventricular wedge preparation.
    Wang D, Patel C, Cui C, Yan GX.
    Pharmacol Ther; 2008 Aug 21; 119(2):141-51. PubMed ID: 18423604
    [Abstract] [Full Text] [Related]

  • 20. Preclinical cardio-safety assessment of torsadogenic risk and alternative methods to animal experimentation: the inseparable twins.
    Dumotier BM, Georgieva AV.
    Cell Biol Toxicol; 2007 Jul 21; 23(4):293-302. PubMed ID: 17216548
    [Abstract] [Full Text] [Related]

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