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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

113 related items for PubMed ID: 15962942

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  • 3. Effect of selection of molecular descriptors on the prediction of blood-brain barrier penetrating and nonpenetrating agents by statistical learning methods.
    Li H, Yap CW, Ung CY, Xue Y, Cao ZW, Chen YZ.
    J Chem Inf Model; 2005; 45(5):1376-84. PubMed ID: 16180914
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  • 5. 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; 44(4):1497-505. PubMed ID: 15272858
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  • 9. Prediction of antibacterial compounds by machine learning approaches.
    Yang XG, Chen D, Wang M, Xue Y, Chen YZ.
    J Comput Chem; 2009 Jun; 30(8):1202-11. PubMed ID: 18988254
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  • 10. 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
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  • 11. Three new consensus QSAR models for the prediction of Ames genotoxicity.
    Votano JR, Parham M, Hall LH, Kier LB, Oloff S, Tropsha A, Xie Q, Tong W.
    Mutagenesis; 2004 Sep; 19(5):365-77. PubMed ID: 15388809
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  • 12. Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods.
    Yap CW, Li ZR, Chen YZ.
    J Mol Graph Model; 2006 Mar; 24(5):383-95. PubMed ID: 16290201
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  • 14. Predicting the genotoxicity of thiophene derivatives from molecular structure.
    Mosier PD, Jurs PC, Custer LL, Durham SK, Pearl GM.
    Chem Res Toxicol; 2003 Jun; 16(6):721-32. PubMed ID: 12807355
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  • 17. Strategy for genotoxicity testing: hazard identification and risk assessment in relation to in vitro testing.
    Thybaud V, Aardema M, Clements J, Dearfield K, Galloway S, Hayashi M, Jacobson-Kram D, Kirkland D, MacGregor JT, Marzin D, Ohyama W, Schuler M, Suzuki H, Zeiger E, Expert Working Group on Hazard Identification and Risk Assessment in Relation to In Vitro Testing.
    Mutat Res; 2007 Feb 03; 627(1):41-58. PubMed ID: 17126066
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  • 18. Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries.
    Kumar P, Ma X, Liu X, Jia J, Bucong H, Xue Y, Li ZR, Yang SY, Wei YQ, Chen YZ.
    J Comput Aided Mol Des; 2011 May 03; 25(5):455-67. PubMed ID: 21556903
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  • 19. Prediction of novel and selective TNF-alpha converting enzyme (TACE) inhibitors and characterization of correlative molecular descriptors by machine learning approaches.
    Cong Y, Yang XG, Lv W, Xue Y.
    J Mol Graph Model; 2009 Oct 03; 28(3):236-44. PubMed ID: 19729328
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  • 20. 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 03; 23(1):134-40. PubMed ID: 18940245
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