Prediction of skin sensitization potency using machine learning approaches-Reference-Cited by-同舟云学术

Prediction of skin sensitization potency using machine learning approaches

Published:2017-01-10 Issue:7 Volume:37 Page:792-805
ISSN:0260-437X
Container-title:Journal of Applied Toxicology
language:en
Short-container-title:J. Appl. Toxicol.

Author:

Zang Qingda¹,Paris Michael¹,Lehmann David M.²,Bell Shannon¹,Kleinstreuer Nicole³,Allen David¹,Matheson Joanna⁴,Jacobs Abigail⁵,Casey Warren³,Strickland Judy¹

Affiliation:

1. ILS; Research Triangle Park; NC 27709 USA

2. EPA/NHEERL/EPHD/CIB; Research Triangle Park; NC 27709 USA

3. NIH/NIEHS/DNTP/NICEATM; Research Triangle Park; NC 27709 USA

4. US Consumer Product Safety Commission; Bethesda MD 20814 USA

5. FDA/CDER; Silver Spring MD 20993 USA

Publisher

Wiley

Subject

Toxicology

Reference90 articles.

1. The LLNA: A brief review of recent advances and limitations;Anderson;J. Allergy,2011

2. Correlation between experimental human and murine skin sensitization induction thresholds;Api;Cutan. Ocul. Toxicol.,2015

3. 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;Ashikaga;Toxicol. in Vitro,2006

4. A comparative evaluation of in vitro skin sensitisation tests: the human cell-line activation test (h-CLAT) versus the local lymph node assay (LLNA);Ashikaga;Altern. Lab. Anim,2010

5. Evaluating the sensitization potential of surfactants: Integrating data from the local lymph node assay, guinea pig maximization test, and in vitro methods in a weight-of-evidence approach;Ball;Regul. Toxicol. Pharmacol.,2011

Cited by 51 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advantages and Disadvantages of Using AI in Dermatology;Dermatological Reviews;2024-08

2. In Silico Prediction of Skin Sensitization for Compounds via Flexible Evidence Combination Based on Machine Learning and Dempster–Shafer Theory;Chemical Research in Toxicology;2024-05-16

3. Use of in vitro methods combined with in silico analysis to identify potential skin sensitizers in the Tox21 10K compound library;Frontiers in Toxicology;2024-02-28

4. Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers;Toxics;2024-02-16

5. Immunotoxicity Studies;Reference Module in Biomedical Sciences;2024