Data integration of non-animal tests for the development of a test battery to predict the skin sensitizing potential and potency of chemicals.
about
Integrated decision strategies for skin sensitization hazardIntegrated Computational Solution for Predicting Skin Sensitization Potential of MoleculesMultivariate Models for Prediction of Human Skin Sensitization HazardBiology-inspired microphysiological system approaches to solve the prediction dilemma of substance testingAnchoring molecular mechanisms to the adverse outcome pathway for skin sensitization: Analysis of existing data.Test battery with the human cell line activation test, direct peptide reactivity assay and DEREK based on a 139 chemical data set for predicting skin sensitizing potential and potency of chemicals.Sensitization potential of dental resins: 2-hydroxyethyl methacrylate and its water-soluble oligomers have immunostimulatory effectsProbabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence.Prediction of skin sensitization potency using machine learning approaches.State of the art in non-animal approaches for skin sensitization testing: from individual test methods towards testing strategies.Development of novel in vitro photosafety assays focused on the Keap1-Nrf2-ARE pathway.Evaluation of combinations of in vitro sensitization test descriptors for the artificial neural network-based risk assessment model of skin sensitization.Integrated Approaches to Testing and Assessment.Increasing the repeating units of ethylene glycol-based dimethacrylates directed toward reduced oxidative stress and co-stimulatory factors expression in human monocytic cells.Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy.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.Respiratory sensitization: toxicological point of view on the available assays.
P2860
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P2860
Data integration of non-animal tests for the development of a test battery to predict the skin sensitizing potential and potency of chemicals.
description
2012 nî lūn-bûn
@nan
2012 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Data integration of non-animal ...... tial and potency of chemicals.
@ast
Data integration of non-animal ...... tial and potency of chemicals.
@en
Data integration of non-animal ...... tial and potency of chemicals.
@nl
type
label
Data integration of non-animal ...... tial and potency of chemicals.
@ast
Data integration of non-animal ...... tial and potency of chemicals.
@en
Data integration of non-animal ...... tial and potency of chemicals.
@nl
prefLabel
Data integration of non-animal ...... tial and potency of chemicals.
@ast
Data integration of non-animal ...... tial and potency of chemicals.
@en
Data integration of non-animal ...... tial and potency of chemicals.
@nl
P2093
P1433
P1476
Data integration of non-animal ...... tial and potency of chemicals.
@en
P2093
Hitoshi Sakaguchi
Masaaki Miyazawa
Naohiro Nishiyama
Saitou Kazutoshi
Yuko Nukada
P304
P356
10.1016/J.TIV.2012.11.006
P577
2012-11-10T00:00:00Z