BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

244 related articles for article (PubMed ID: 18950860)

  • 1. Rapid toxicity prediction of organic chemicals to Chlorella vulgaris using quantitative structure-activity relationships methods.
    Xia B; Liu K; Gong Z; Zheng B; Zhang X; Fan B
    Ecotoxicol Environ Saf; 2009 Mar; 72(3):787-94. PubMed ID: 18950860
    [TBL] [Abstract][Full Text] [Related]  

  • 2. QSTR with extended topochemical atom (ETA) indices. 9. Comparative QSAR for the toxicity of diverse functional organic compounds to Chlorella vulgaris using chemometric tools.
    Roy K; Ghosh G
    Chemosphere; 2007 Nov; 70(1):1-12. PubMed ID: 17765287
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Quantitative structure-activity relationship models for prediction of sensory irritants (logRD50) of volatile organic chemicals.
    Luan F; Ma W; Zhang X; Zhang H; Liu M; Hu Z; Fan BT
    Chemosphere; 2006 May; 63(7):1142-53. PubMed ID: 16307788
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of fathead minnow acute toxicity of organic compounds from molecular structure.
    Eldred DV; Weikel CL; Jurs PC; Kaiser KL
    Chem Res Toxicol; 1999 Jul; 12(7):670-8. PubMed ID: 10409408
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Quantitative structure-retention relationships for organic pollutants in biopartitioning micellar chromatography.
    Xia B; Ma W; Zhang X; Fan B
    Anal Chim Acta; 2007 Aug; 598(1):12-8. PubMed ID: 17693301
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).
    Papa E; Villa F; Gramatica P
    J Chem Inf Model; 2005; 45(5):1256-66. PubMed ID: 16180902
    [TBL] [Abstract][Full Text] [Related]  

  • 7. QSAR analysis of the toxicity of aromatic compounds to Chlorella vulgaris in a novel short-term assay.
    Netzeva TI; Dearden JC; Edwards R; Worgan AD; Cronin MT
    J Chem Inf Comput Sci; 2004; 44(1):258-65. PubMed ID: 14741035
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Creation of predictive models of aquatic toxicity of environmental pollutants with different mechanisms of action on the basis of molecular similarity and HYBOT descriptors.
    Raevsky OA; Dearden JC
    SAR QSAR Environ Res; 2004; 15(5-6):433-48. PubMed ID: 15669700
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Ranking of aquatic toxicity of esters modelled by QSAR.
    Papa E; Battaini F; Gramatica P
    Chemosphere; 2005 Feb; 58(5):559-70. PubMed ID: 15620749
    [TBL] [Abstract][Full Text] [Related]  

  • 10. QSAR modeling of anti-invasive activity of organic compounds using structural descriptors.
    Katritzky AR; Kuanar M; Dobchev DA; Vanhoecke BW; Karelson M; Parmar VS; Stevens CV; Bracke ME
    Bioorg Med Chem; 2006 Oct; 14(20):6933-9. PubMed ID: 16908166
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Linear QSAR regression models for the prediction of bioconcentration factors by physicochemical properties and structural theoretical molecular descriptors.
    Papa E; Dearden JC; Gramatica P
    Chemosphere; 2007 Feb; 67(2):351-8. PubMed ID: 17109926
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The accurate QSPR models to predict the bioconcentration factors of nonionic organic compounds based on the heuristic method and support vector machine.
    Liu H; Yao X; Zhang R; Liu M; Hu Z; Fan B
    Chemosphere; 2006 May; 63(5):722-33. PubMed ID: 16226786
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Quantitative structure-property relationship study for estimation of quantitative calibration factors of some organic compounds in gas chromatography.
    Luan F; Liu HT; Wen Y; Zhang X
    Anal Chim Acta; 2008 Apr; 612(2):126-35. PubMed ID: 18358857
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Tuning neural and fuzzy-neural networks for toxicity modeling.
    Mazzatorta P; Benfenati E; Neagu CD; Gini G
    J Chem Inf Comput Sci; 2003; 43(2):513-8. PubMed ID: 12653515
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Assessing the reliability of a QSAR model's predictions.
    He L; Jurs PC
    J Mol Graph Model; 2005 Jun; 23(6):503-23. PubMed ID: 15896992
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Validation of a QSAR model for acute toxicity.
    Pavan M; Netzeva TI; Worth AP
    SAR QSAR Environ Res; 2006 Apr; 17(2):147-71. PubMed ID: 16644555
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: general principles and application to reactive toxicity.
    Aptula AO; Roberts DW
    Chem Res Toxicol; 2006 Aug; 19(8):1097-105. PubMed ID: 16918251
    [TBL] [Abstract][Full Text] [Related]  

  • 18. QSAR prediction of estrogen activity for a large set of diverse chemicals under the guidance of OECD principles.
    Liu H; Papa E; Gramatica P
    Chem Res Toxicol; 2006 Nov; 19(11):1540-8. PubMed ID: 17112243
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of the aqueous solvation free energy of organic compounds by using autocorrelation of molecular electrostatic potential surface properties combined with response surface analysis.
    Michielan L; Bacilieri M; Kaseda C; Moro S
    Bioorg Med Chem; 2008 May; 16(10):5733-42. PubMed ID: 18406153
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Toxicological evaluation and QSAR modelling of aromatic amines to Chlorella vulgaris.
    Netzeva TI; Dearden JC; Edwards R; Worgan AD; Cronin MT
    Bull Environ Contam Toxicol; 2004 Aug; 73(2):385-91. PubMed ID: 15386056
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 13.