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SAR and QSAR in Environmental Research Volume 26, 2015 - Issue 10: 8th International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources (CMTPI-2015) - Part 2. Guest Editor: A. Geronikaki
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Original Articles

Prediction of the endocrine disruption profile of pesticidesFootnote

J. DevillersCTIS, Rillieux La Pape, FranceCorrespondence[email protected]
,
E. BroResearch Department, National Game and Wildlife Institute (ONCFS), Le Perray en Yvelines, France
&
F. MillotResearch Department, National Game and Wildlife Institute (ONCFS), Le Perray en Yvelines, France
Pages 831-852 | Received 17 Jul 2015, Accepted 15 Sep 2015, Published online: 07 Nov 2015

Citations (15)

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J. Devillers & H. Devillers. (2019) Toxicity profiling and prioritization of plant-derived antimalarial agents. SAR and QSAR in Environmental Research 30:11, pages 801-824.
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J. Devillers, H. Devillers, E. Bro & F. Millot. (2017) Expert judgment based multicriteria decision models to assess the risk of pesticides on reproduction failures of grey partridge. SAR and QSAR in Environmental Research 28:11, pages 889-911.
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Yannick Djoumbou-Feunang, Jeremy Wilmot, John Kinney, Pritam Chanda, Pulan Yu, Avery Sader, Max Sharifi, Scott Smith, Junjun Ou, Jie Hu, Elizabeth Shipp, Dirk Tomandl & Siva P. Kumpatla. (2023) Cheminformatics and artificial intelligence for accelerating agrochemical discovery. Frontiers in Chemistry 11.
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Said Kinani, Salma Achawi, Sylvaine Ronga-Pezeret, Aleksandra Piotrowski, Christine Gauthey-Lapize, Ilse Tonk, Mira Wenker & Fabrice Nesslany. (2023) Examination of the endocrine-disrupting properties of “active chlorine generated from seawater by electrolysis” in response to the European Biocidal Products Regulation: current knowledge and methodological challenges. Environmental Sciences Europe 35:1.
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J. Ren, T. Jin, R. Li, Y.Y. Zhong, Y.X. Xuan, Y.L. Wang, W. Yao, S.L. Yu & J.T. Yuan. (2023) Priority list of potential endocrine-disrupting chemicals in food chemical contaminants: a docking study and in vitro/epidemiological evidence integration. SAR and QSAR in Environmental Research 34:10, pages 847-866.
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Shuling Yu, Jing Ren, Zhenxia Lv, Rui Li, Yuyan Zhong, Wu Yao & Jintao Yuan. (2022) Prediction of the endocrine-disrupting ability of 49 per- and polyfluoroalkyl substances: In silico and epidemiological evidence. Chemosphere 290, pages 133366.
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Xinwen Zhang & Changqing Wu. (2022) In Silico , In Vitro , and In Vivo Evaluation of the Developmental Toxicity, Estrogenic Activity, and Mutagenicity of Four Natural Phenolic Flavonoids at Low Exposure Levels . ACS Omega 7:6, pages 4757-4768.
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C Song, Q Wu, J Sun, R Zhang, J Chen, X Wang, L Fang, Z Liu, X Shan & Y Yin. (2021) In silico evaluation of interactions between antibiotics in aquaculture and nuclear hormone receptors. Aquaculture Environment Interactions 13, pages 389-397.
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Nadia Coronado‐Posada, Jairo Mercado‐Camargo & Jesus Olivero‐Verbel. (2021) In Silico Analysis to Identify Molecular Targets for Chemicals of Concern: The Case Study of Flocoumafen, an Anticoagulant Pesticide. Environmental Toxicology and Chemistry 40:7, pages 2032-2041.
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Xinwen Zhang, Ying Peng & Changqing Wu. (2021) Chicken embryonic toxicity and potential in vitro estrogenic and mutagenic activity of carvacrol and thymol in low dose/concentration. Food and Chemical Toxicology 150, pages 112038.
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P. Ruiz, A. Sack, M. Wampole, S. Bobst & M. Vracko. (2017) Integration of in silico methods and computational systems biology to explore endocrine-disrupting chemical binding with nuclear hormone receptors. Chemosphere 178, pages 99-109.
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Paola Gramatica. 2017. Handbook of Computational Chemistry. Handbook of Computational Chemistry 2231 2263 .
Huixiao Hong, Jie Shen, Hui Ng, Sugunadevi Sakkiah, Hao Ye, Weigong Ge, Ping Gong, Wenming Xiao & Weida Tong. (2016) A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals. International Journal of Environmental Research and Public Health 13:4, pages 372.
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Nicola Porta, Aless ra Roncaglioni, Marco Marzo & Emilio Benfenati. (2016) QSAR Methods to Screen Endocrine Disruptors. Nuclear Receptor Research 3.
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Paola Gramatica. 2016. Handbook of Computational Chemistry. Handbook of Computational Chemistry 1 33 .

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