BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

249 related articles for article (PubMed ID: 37040559)

  • 1. Data-Driven Quantitative Structure-Activity Relationship Modeling for Human Carcinogenicity by Chronic Oral Exposure.
    Chung E; Russo DP; Ciallella HL; Wang YT; Wu M; Aleksunes LM; Zhu H
    Environ Sci Technol; 2023 Apr; 57(16):6573-6588. PubMed ID: 37040559
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling.
    Valerio LG; Arvidson KB; Chanderbhan RF; Contrera JF
    Toxicol Appl Pharmacol; 2007 Jul; 222(1):1-16. PubMed ID: 17482223
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Combining machine learning models of in vitro and in vivo bioassays improves rat carcinogenicity prediction.
    Guan D; Fan K; Spence I; Matthews S
    Regul Toxicol Pharmacol; 2018 Apr; 94():8-15. PubMed ID: 29337192
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids.
    Jia X; Ciallella HL; Russo DP; Zhao L; James MH; Zhu H
    ACS Sustain Chem Eng; 2021 Mar; 9(10):3909-3919. PubMed ID: 34239782
    [TBL] [Abstract][Full Text] [Related]  

  • 6. In Silico Study of In Vitro GPCR Assays by QSAR Modeling.
    Mansouri K; Judson RS
    Methods Mol Biol; 2016; 1425():361-81. PubMed ID: 27311474
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling.
    Wang W; Kim MT; Sedykh A; Zhu H
    Pharm Res; 2015 Sep; 32(9):3055-65. PubMed ID: 25862462
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening.
    Hsieh JH; Wang XS; Teotico D; Golbraikh A; Tropsha A
    J Comput Aided Mol Des; 2008 Sep; 22(9):593-609. PubMed ID: 18338225
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices.
    Contrera JF; Matthews EJ; Daniel Benz R
    Regul Toxicol Pharmacol; 2003 Dec; 38(3):243-59. PubMed ID: 14623477
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Development of classification and regression based QSAR models to predict rodent carcinogenic potency using oral slope factor.
    Kar S; Deeb O; Roy K
    Ecotoxicol Environ Saf; 2012 Aug; 82():85-95. PubMed ID: 22698880
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prioritization of mycotoxins based on mutagenicity and carcinogenicity evaluation using combined in silico QSAR methods.
    Lemée P; Fessard V; Habauzit D
    Environ Pollut; 2023 Apr; 323():121284. PubMed ID: 36804886
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.
    Ribay K; Kim MT; Wang W; Pinolini D; Zhu H
    Front Environ Sci; 2016 Mar; 4():. PubMed ID: 27642585
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Use of cell viability assay data improves the prediction accuracy of conventional quantitative structure-activity relationship models of animal carcinogenicity.
    Zhu H; Rusyn I; Richard A; Tropsha A
    Environ Health Perspect; 2008 Apr; 116(4):506-13. PubMed ID: 18414635
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID study of the species differences in the carcinogenicity of benzene derivatives chemicals.
    Fratev F; Benfenati E
    J Mol Graph Model; 2008 Sep; 27(2):147-60. PubMed ID: 18495507
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.
    Kim MT; Huang R; Sedykh A; Wang W; Xia M; Zhu H
    Environ Health Perspect; 2016 May; 124(5):634-41. PubMed ID: 26383846
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay.
    Jia X; Wen X; Russo DP; Aleksunes LM; Zhu H
    J Hazard Mater; 2022 Aug; 436():129193. PubMed ID: 35739723
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 13.