BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

251 related articles for article (PubMed ID: 16414170)

  • 21. Prediction of the rodent carcinogenicity of 60 pesticides by the DEREKfW expert system.
    Crettaz P; Benigni R
    J Chem Inf Model; 2005; 45(6):1864-73. PubMed ID: 16309294
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Development of QSAR models for predicting hepatocarcinogenic toxicity of chemicals.
    Massarelli I; Imbriani M; Coi A; Saraceno M; Carli N; Bianucci AM
    Eur J Med Chem; 2009 Sep; 44(9):3658-64. PubMed ID: 19272677
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Development of quantitative structure-activity relationship (QSAR) models to predict the carcinogenic potency of chemicals. II. Using oral slope factor as a measure of carcinogenic potency.
    Wang NC; Venkatapathy R; Bruce RM; Moudgal C
    Regul Toxicol Pharmacol; 2011 Mar; 59(2):215-26. PubMed ID: 20951756
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Carcinogenicity of the aromatic amines: from structure-activity relationships to mechanisms of action and risk assessment.
    Benigni R; Passerini L
    Mutat Res; 2002 Jul; 511(3):191-206. PubMed ID: 12088717
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Mechanistic QSAR of aromatic amines: new models for discriminating between homocyclic mutagens and nonmutagens, and validation of models for carcinogens.
    Benigni R; Bossa C; Netzeva T; Rodomonte A; Tsakovska I
    Environ Mol Mutagen; 2007 Dec; 48(9):754-71. PubMed ID: 18008355
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.
    Liu Z; Kelly R; Fang H; Ding D; Tong W
    Chem Res Toxicol; 2011 Jul; 24(7):1062-70. PubMed ID: 21627106
    [TBL] [Abstract][Full Text] [Related]  

  • 27. In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.
    Pasha FA; Neaz MM; Cho SJ; Ansari M; Mishra SK; Tiwari S
    Chem Biol Drug Des; 2009 May; 73(5):537-44. PubMed ID: 19323655
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Structure-activity relationship analysis tools: validation and applicability in predicting carcinogens.
    Mayer J; Cheeseman MA; Twaroski ML
    Regul Toxicol Pharmacol; 2008 Feb; 50(1):50-8. PubMed ID: 18023949
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Comparative QSTR studies for predicting mutagenicity of nitro compounds.
    Nair PC; Sobhia ME
    J Mol Graph Model; 2008 Feb; 26(6):916-34. PubMed ID: 17689994
    [TBL] [Abstract][Full Text] [Related]  

  • 30. An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: II. Identification of genotoxicants, reprotoxicants, and carcinogens using in silico methods.
    Matthews EJ; Kruhlak NL; Cimino MC; Benz RD; Contrera JF
    Regul Toxicol Pharmacol; 2006 Mar; 44(2):97-110. PubMed ID: 16352383
    [TBL] [Abstract][Full Text] [Related]  

  • 31. QSARs of aromatic amines: identification of potent carcinogens.
    Franke R; Gruska A; Bossa C; Benigni R
    Mutat Res; 2010 Sep; 691(1-2):27-40. PubMed ID: 20600167
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Liver specificity of the carcinogenicity of NOCs: a chemical-molecular perspective.
    Yuan J; Pu Y; Yin L
    Chem Res Toxicol; 2012 Nov; 25(11):2432-42. PubMed ID: 23043541
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Comparison between rodent carcinogenicity test results of 44 chemicals and a number of predictive systems.
    Lewis DF
    Regul Toxicol Pharmacol; 1994 Dec; 20(3 Pt 1):215-22. PubMed ID: 7724831
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Prediction of rodent carcinogenicity of aromatic amines: a quantitative structure-activity relationships model.
    Franke R; Gruska A; Giuliani A; Benigni R
    Carcinogenesis; 2001 Sep; 22(9):1561-71. PubMed ID: 11532881
    [TBL] [Abstract][Full Text] [Related]  

  • 35. SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes.
    Toropov AA; Toropova AP; Benfenati E
    Eur J Med Chem; 2010 Sep; 45(9):3581-7. PubMed ID: 20570021
    [TBL] [Abstract][Full Text] [Related]  

  • 36. In Silico Methods for Carcinogenicity Assessment.
    Golbamaki A; Benfenati E
    Methods Mol Biol; 2016; 1425():107-19. PubMed ID: 27311464
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Computer-aided analysis of mutagenicity and cell transformation data for assessing their relationship with carcinogenicity.
    Taningher M; Malacarne D; Perrotta A; Parodi S
    Environ Mol Mutagen; 1999; 33(3):226-39. PubMed ID: 10334625
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Structural motifs modulating the carcinogenic risk of aromatic amines.
    Benigni R; Worth A; Netzeva T; Jeliazkova N; Bossa C; Gruska A; Franke R
    Environ Mol Mutagen; 2009 Mar; 50(2):152-61. PubMed ID: 19152383
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Predictivity of QSAR.
    Benigni R; Bossa C
    J Chem Inf Model; 2008 May; 48(5):971-80. PubMed ID: 18426198
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Radial Distribution Function descriptors for predicting affinity for vitamin D receptor.
    González MP; Gándara Z; Fall Y; Gómez G
    Eur J Med Chem; 2008 Jul; 43(7):1360-5. PubMed ID: 18068275
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 13.