BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

168 related articles for article (PubMed ID: 30251555)

  • 1. Evaluation and improvement of QSAR predictions of skin sensitization for pesticides.
    Braeuning C; Braeuning A; Mielke H; Holzwarth A; Peiser M
    SAR QSAR Environ Res; 2018 Oct; 29(10):823-846. PubMed ID: 30251555
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Computer models versus reality: how well do in silico models currently predict the sensitization potential of a substance.
    Teubner W; Mehling A; Schuster PX; Guth K; Worth A; Burton J; van Ravenzwaay B; Landsiedel R
    Regul Toxicol Pharmacol; 2013 Dec; 67(3):468-85. PubMed ID: 24090701
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Review of the state of science and evaluation of currently available in silico prediction models for reproductive and developmental toxicity: A case study on pesticides.
    Weyrich A; Joel M; Lewin G; Hofmann T; Frericks M
    Birth Defects Res; 2022 Aug; 114(14):812-842. PubMed ID: 35748219
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Computational approaches for skin sensitization prediction.
    Wilm A; Kühnl J; Kirchmair J
    Crit Rev Toxicol; 2018 Oct; 48(9):738-760. PubMed ID: 30488745
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of in silico tools to predict the skin sensitization potential of chemicals.
    Verheyen GR; Braeken E; Van Deun K; Van Miert S
    SAR QSAR Environ Res; 2017 Jan; 28(1):59-73. PubMed ID: 28105856
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development of an artificial neural network model for risk assessment of skin sensitization using human cell line activation test, direct peptide reactivity assay, KeratinoSens™ and in silico structure alert parameter.
    Hirota M; Ashikaga T; Kouzuki H
    J Appl Toxicol; 2018 Apr; 38(4):514-526. PubMed ID: 29226339
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization.
    Alves VM; Muratov E; Fourches D; Strickland J; Kleinstreuer N; Andrade CH; Tropsha A
    Toxicol Appl Pharmacol; 2015 Apr; 284(2):273-80. PubMed ID: 25560673
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals.
    Contrera JF
    Regul Toxicol Pharmacol; 2013 Nov; 67(2):285-93. PubMed ID: 23969001
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Non-animal methods to predict skin sensitization (II): an assessment of defined approaches
    Kleinstreuer NC; Hoffmann S; Alépée N; Allen D; Ashikaga T; Casey W; Clouet E; Cluzel M; Desprez B; Gellatly N; Göbel C; Kern PS; Klaric M; Kühnl J; Martinozzi-Teissier S; Mewes K; Miyazawa M; Strickland J; van Vliet E; Zang Q; Petersohn D
    Crit Rev Toxicol; 2018 May; 48(5):359-374. PubMed ID: 29474122
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles.
    Toropova AP; Toropov AA
    Toxicol Lett; 2017 Jun; 275():57-66. PubMed ID: 28359801
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.
    Alves VM; Muratov E; Fourches D; Strickland J; Kleinstreuer N; Andrade CH; Tropsha A
    Toxicol Appl Pharmacol; 2015 Apr; 284(2):262-72. PubMed ID: 25560674
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The Good, The Bad, and The Perplexing: Structural Alerts and Read-Across for Predicting Skin Sensitization Using Human Data.
    Golden E; Ukaegbu DC; Ranslow P; Brown RH; Hartung T; Maertens A
    Chem Res Toxicol; 2023 May; 36(5):734-746. PubMed ID: 37126467
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A data-based exploration of the adverse outcome pathway for skin sensitization points to the necessary requirements for its prediction with alternative methods.
    Benigni R; Bossa C; Tcheremenskaia O
    Regul Toxicol Pharmacol; 2016 Jul; 78():45-52. PubMed ID: 27090483
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Structure-activity models for contact sensitization.
    Fedorowicz A; Singh H; Soderholm S; Demchuk E
    Chem Res Toxicol; 2005 Jun; 18(6):954-69. PubMed ID: 15962930
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A quantitative in silico model for predicting skin sensitization using a nearest neighbours approach within expert-derived structure-activity alert spaces.
    Canipa SJ; Chilton ML; Hemingway R; Macmillan DS; Myden A; Plante JP; Tennant RE; Vessey JD; Steger-Hartmann T; Gould J; Hillegass J; Etter S; Smith BPC; White A; Sterchele P; De Smedt A; O'Brien D; Parakhia R
    J Appl Toxicol; 2017 Aug; 37(8):985-995. PubMed ID: 28244128
    [TBL] [Abstract][Full Text] [Related]  

  • 16. (Q)SAR tools for the prediction of mutagenic properties: Are they ready for application in pesticide regulation?
    Herrmann K; Holzwarth A; Rime S; Fischer BC; Kneuer C
    Pest Manag Sci; 2020 Oct; 76(10):3316-3325. PubMed ID: 32223060
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Non-animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?
    Roberts DW; Patlewicz G
    J Appl Toxicol; 2018 Jan; 38(1):41-50. PubMed ID: 28543848
    [TBL] [Abstract][Full Text] [Related]  

  • 18. SkinSensPred as a Promising in Silico Tool for Integrated Testing Strategy on Skin Sensitization.
    Wang SS; Wang CC; Tung CW
    Int J Environ Res Public Health; 2022 Oct; 19(19):. PubMed ID: 36232156
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Putting the parts together: combining in vitro methods to test for skin sensitizing potentials.
    Bauch C; Kolle SN; Ramirez T; Eltze T; Fabian E; Mehling A; Teubner W; van Ravenzwaay B; Landsiedel R
    Regul Toxicol Pharmacol; 2012 Aug; 63(3):489-504. PubMed ID: 22659254
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluation of the global performance of eight in silico skin sensitization models using human data.
    Golden E; Macmillan DS; Dameron G; Kern P; Hartung T; Maertens A
    ALTEX; 2021; 38(1):33-48. PubMed ID: 32388570
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.