TOXICITY PREDICTION MODEL FOR PREDICTING ACUTE ORAL TOXICITY BASED ON QUANTITATIVE STRUCTURE-TOXICITY RELATIONSHIP BY USING NON-LINEAR LEARNING METHOD

• 1. 一种通过定量构效关系模型预测有机磷农药对水生生物急性毒性的方法 [P] . 中国专利： CN103778483A . 2014-05-07
• 2. 一种通过量子化学方法构建定量构效关系模型来预测有机化合物急性毒性的方法 [P] . 中国专利： CN103646180A . 2014-03-19
• 3. PHYSICAL PROPERTY PREDICTION MODEL FOR PREDICTING MELTING POINT BASED ON QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP USING LINEAR AND NONLINEAR MACHINE LEARNING METHODS [P] . 韩国专利： KR20160127486A . 2016-11-04

  机译： 基于线性和非线性机器学习方法的定量结构-活动关系预测熔化点的物理性能预测模型

• 4. PHYSICAL PROPERTY PREDICTION MODEL FOR PREDICTING BOILING POINT BASED ON QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP USING LINEAR AND NONLINEAR MACHINE LEARNING METHODS [P] . 韩国专利： KR20160127487A . 2016-11-04

  机译： 基于线性和非线性机器学习方法的定量结构-活度关系预测沸点的物理属性预测模型

• 5. TOXICITY LEARNING DEVICE, TOXICITY LEARNING METHOD, LEARNED MODEL, TOXICITY PREDICTION DEVICE, AND PROGRAM [P] . 日本专利： JP2020025471A . 2020-02-20

  机译： 毒性学习装置，毒性学习方法，学习模型，毒性预测装置和程序

• 1. Quantitative structure-toxicity relationships (QSTRs): a comparative study of various non linear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- a [J] . Panaye A, Fan BT, Doucet JP, SAR and QSAR in Environmental Research . 2006,第1期
• 2. Prediction of nitrobenzene toxicity to the algae (Scenedesmus obliguus) by quantitative structure-toxicity relationship (QSTR) models with quantum chemical descriptors [J] . Yueping Bao, Qiuying Huang, Yangyang li, Environmental toxicology and pharmacology . 2012,第1期
• 3. Quantitative structure-toxicity relationship model for acute toxicity of organophosphates via multiple administration routes in rats and mice [J] . Wang Liang-Liang, Ding Jun-Jie, Pan Li, Journal of Hazardous Materials . 2021,第Pta2期
• 4. Quantitative Structure-Toxicity Relationship for Predicting Acute Toxicity of Phenols [C] . Zhi-Xiang ZHOU, Meng-Nan QIN, Yang-Hua LIU, International Conference on Biological Sciences and Technology . 2016
• 5. Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles. [D] . Pu, Dongqiuye. 2012
• 6. A Novel Approach for a Toxicity Prediction Model of Environmental Pollutants by Using a Quantitative Structure-Activity Relationship Method Based on Toxicogenomics [O] . Junichi Hosoya, Kumiko Tamura, Naomi Muraki, 2011
• 7. Quantitative Structure-Toxicity Relationship for Predicting Acute Toxicity of Phenols [O] . Zhi-Xiang Zhou, Meng-Nan Qin, Yang-Hua Liu, 2016

• 1. Study on the Quantitative Structure-toxicity Relationships for the Selected Esters by Using Molecular Electronegativity Interaction Vector （MEIV） [J] . LI Jian-Feng ,LIAO Li-Min ,WANG Bi . 结构化学 . 2011,第009期
• 2. Surface Electrostatic Potentials of Polychlorinated Dibenzofurans and Their Applications in Quantitative Structure-toxicity Relationships [J] . ZOU Jian-Wei ,HU Gui-Xiang ,JIANG Yong-Jun . 结构化学 . 2005,第004期
• 3. Holographic quantitative structure-activity relationship for prediction acute toxicity of benzene derivatives to the guppy(poecilia reticulata) [J] . HUANGHong WANGXiao-dong DAIXuan-li YUYa-juan WANGLian-sheng . 环境科学学报：英文版 . 2004,第3期
• 4. Studies on the Quantitative Structure-activity Relationship of Toxicity of Chlorophenol Serial Compounds in the ab initio Methods and Substitutive Position of Chlorine Atom (NPCS) [J] . ZHENG Qing ,WANG Lian-Sheng . 结构化学 . 2007,第008期
• 5. Predicting the Acute Toxicity of Aromatic Amines by Linear and Nonlinear Regression Methods [J] . ZHANG Xiao-Long ,ZHOU Zhi-Xiang ,LIU Yang-Hua . 结构化学 . 2014,第002期
• 6. 铜锌植物急性毒性的预测模型-生物配体模型研究 [C] . 王学东 ,马义兵 ,华珞 . 第六届全国环境化学学术大会 . 2011
• 7. 铜对斜生栅藻急性毒性预测模型—生物配体模型的建立与验证 [A] . 徐潇 . 2019