BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

272 related articles for article (PubMed ID: 22659232)

  • 21. QSPR studies on soot-water partition coefficients of persistent organic pollutants by using artificial neural network.
    Jiao L
    Chemosphere; 2010 Jul; 80(6):671-5. PubMed ID: 20452639
    [TBL] [Abstract][Full Text] [Related]  

  • 22. 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]  

  • 23. In-silico prediction of blood-brain barrier permeability.
    Yan A; Liang H; Chong Y; Nie X; Yu C
    SAR QSAR Environ Res; 2013 Jan; 24(1):61-74. PubMed ID: 23092117
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Prediction of gas chromatographic retention indices of some amino acids and carboxylic acids from their structural descriptors.
    Fatemi MH; Elyasi M
    J Sep Sci; 2011 Nov; 34(22):3216-20. PubMed ID: 22012944
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Development of liposome/water partition coefficients predictive models for neutral and ionogenic organic chemicals.
    Lin S; Yang X; Liu H
    Ecotoxicol Environ Saf; 2019 Sep; 179():40-49. PubMed ID: 31026749
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.
    Golmohammadi H
    J Comput Chem; 2009 Nov; 30(15):2455-65. PubMed ID: 19360793
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Prediction of air-to-blood partition coefficients of volatile organic compounds using genetic algorithm and artificial neural network.
    Konoz E; Golmohammadi H
    Anal Chim Acta; 2008 Jul; 619(2):157-64. PubMed ID: 18558108
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Use of self-training artificial neural networks in modeling of gas chromatographic relative retention times of a variety of organic compounds.
    Jalali-Heravi M; Garkani-Nejad Z
    J Chromatogr A; 2002 Feb; 945(1-2):173-84. PubMed ID: 11860134
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Quantitative structure-diastereoselectivity relationships for arylsulfoxide derivatives in radical chemistry.
    Zahouily M; Rayadh A; Aadil M; Zakarya D
    J Mol Model; 2003 Aug; 9(4):242-7. PubMed ID: 12768446
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Exploring QSPR models for predicting PUF-air partition coefficients of organic compounds with linear and nonlinear approaches.
    Zhu T; Gu L; Chen M; Sun F
    Chemosphere; 2021 Mar; 266():128962. PubMed ID: 33218721
    [TBL] [Abstract][Full Text] [Related]  

  • 31. 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]  

  • 32. Predicting hERG activities of compounds from their 3D structures: development and evaluation of a global descriptors based QSAR model.
    Sinha N; Sen S
    Eur J Med Chem; 2011 Feb; 46(2):618-30. PubMed ID: 21185626
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Predictive QSAR Models for the Toxicity of Disinfection Byproducts.
    Qin L; Zhang X; Chen Y; Mo L; Zeng H; Liang Y
    Molecules; 2017 Oct; 22(10):. PubMed ID: 28991213
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Comparison of QSAR models based on combinations of genetic algorithm, stepwise multiple linear regression, and artificial neural network methods to predict Kd of some derivatives of aromatic sulfonamides as carbonic anhydrase II inhibitors.
    Maleki A; Daraei H; Alaei L; Faraji A
    Bioorg Khim; 2014; 40(1):70-84. PubMed ID: 25898725
    [TBL] [Abstract][Full Text] [Related]  

  • 35. QSAR prediction of D2 receptor antagonistic activity of 6-methoxy benzamides.
    Fatemi MH; Dorostkar F
    Eur J Med Chem; 2010 Nov; 45(11):4856-62. PubMed ID: 20728966
    [TBL] [Abstract][Full Text] [Related]  

  • 36. 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]  

  • 37. QSPR modeling of bioconcentration factor of nonionic compounds using Gaussian processes and theoretical descriptors derived from electrostatic potentials on molecular surface.
    Peng S; Jian-Wei Z; Peng Z; Lin X
    Chemosphere; 2011 May; 83(8):1045-52. PubMed ID: 21339002
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A novel QSAR model for prediction of apoptosis-inducing activity of 4-aryl-4-H-chromenes based on support vector machine.
    Fatemi MH; Gharaghani S
    Bioorg Med Chem; 2007 Dec; 15(24):7746-54. PubMed ID: 17870538
    [TBL] [Abstract][Full Text] [Related]  

  • 39. QSPR modeling of soil sorption coefficients (K(OC)) of pesticides using SPA-ANN and SPA-MLR.
    Goudarzi N; Goodarzi M; Araujo MC; Galvão RK
    J Agric Food Chem; 2009 Aug; 57(15):7153-8. PubMed ID: 19722589
    [TBL] [Abstract][Full Text] [Related]  

  • 40. 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]  

    [Previous]   [Next]    [New Search]
    of 14.