Predicting skin sensitizers with confidence - Using conformal prediction to determine applicability domain of GARD.

[1]  Grace Patlewicz,et al.  Non‐animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated? , 2018, Journal of applied toxicology : JAT.

[2]  Aakash Chawade,et al.  The GARD platform for potency assessment of skin sensitizing chemicals. , 2017, ALTEX.

[3]  Erwin van Vliet,et al.  Evaluation of the GARD assay in a blind Cosmetics Europe study. , 2017, ALTEX.

[4]  Silvia Casati,et al.  Can currently available non-animal methods detect pre and pro-haptens relevant for skin sensitization? , 2016, Regulatory toxicology and pharmacology : RTP.

[5]  Janine Ezendam,et al.  State of the art in non-animal approaches for skin sensitization testing: from individual test methods towards testing strategies , 2016, Archives of Toxicology.

[6]  Scott Boyer,et al.  Conformal Prediction Classification of a Large Data Set of Environmental Chemicals from ToxCast and Tox21 Estrogen Receptor Assays. , 2016, Chemical research in toxicology.

[7]  Judy Strickland,et al.  Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy , 2015, Archives of Toxicology.

[8]  Takao Ashikaga,et al.  In silico risk assessment for skin sensitization using artificial neural network analysis. , 2015, The Journal of toxicological sciences.

[9]  Lars Carlsson,et al.  Aggregated Conformal Prediction , 2014, AIAI Workshops.

[10]  Andreas Schepky,et al.  Genomic allergen rapid detection in-house validation--a proof of concept. , 2014, Toxicological sciences : an official journal of the Society of Toxicology.

[11]  Setsuya Aiba,et al.  Skin sensitization risk assessment model using artificial neural network analysis of data from multiple in vitro assays. , 2014, Toxicology in vitro : an international journal published in association with BIBRA.

[12]  Scott Boyer,et al.  Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination , 2014, J. Chem. Inf. Model..

[13]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[14]  Petra Kern,et al.  A dataset on 145 chemicals tested in alternative assays for skin sensitization undergoing prevalidation , 2013, Journal of applied toxicology : JAT.

[15]  Malin Lindstedt,et al.  The GARD assay for assessment of chemical skin sensitizers. , 2013, Toxicology in vitro : an international journal published in association with BIBRA.

[16]  Stephen R. Piccolo,et al.  A single-sample microarray normalization method to facilitate personalized-medicine workflows. , 2012, Genomics.

[17]  Robert Landsiedel,et al.  Putting the parts together: combining in vitro methods to test for skin sensitizing potentials. , 2012, Regulatory toxicology and pharmacology : RTP.

[18]  Andrew E. Jaffe,et al.  Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .

[19]  Takao Ashikaga,et al.  Predictive performance for human skin sensitizing potential of the human cell line activation test (h‐CLAT) , 2011, Contact dermatitis.

[20]  Malin Lindstedt,et al.  A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests , 2011, BMC Genomics.

[21]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[22]  J. Bailar,et al.  Toxicity Testing in the 21st Century: A Vision and a Strategy , 2010, Journal of toxicology and environmental health. Part B, Critical reviews.

[23]  Donald Y M Leung,et al.  Allergic skin diseases. , 2010, The Journal of allergy and clinical immunology.

[24]  Andreas Natsch,et al.  The Nrf2-Keap1-ARE toxicity pathway as a cellular sensor for skin sensitizers--functional relevance and a hypothesis on innate reactions to skin sensitizers. , 2010, Toxicological sciences : an official journal of the Society of Toxicology.

[25]  S. Enoch,et al.  Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach , 2008, SAR and QSAR in environmental research.

[26]  Mehryar Mohri,et al.  Sample Selection Bias Correction Theory , 2008, ALT.

[27]  Kristina Luthman,et al.  Allergic contact dermatitis--formation, structural requirements, and reactivity of skin sensitizers. , 2008, Chemical research in toxicology.

[28]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[29]  H. Sakaguchi,et al.  Development of an in vitro skin sensitization test using human cell lines: the human Cell Line Activation Test (h-CLAT). I. Optimization of the h-CLAT protocol. , 2006, Toxicology in vitro : an international journal published in association with BIBRA.

[30]  David W Roberts,et al.  Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: general principles and application to reactive toxicity. , 2006, Chemical research in toxicology.

[31]  G. Shafer,et al.  Algorithmic Learning in a Random World , 2005 .

[32]  G Frank Gerberick,et al.  Development of a peptide reactivity assay for screening contact allergens. , 2004, Toxicological sciences : an official journal of the Society of Toxicology.

[33]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[34]  Steven R. Cohen,et al.  The relationship between atopic dermatitis and contact dermatitis. , 2003, Clinics in dermatology.