Recommanded Product: 385-00-2. Chen, XM; Dang, LM; Yang, H; Huang, XW; Yu, XL in [Chen, Xingmei; Dang, Limin; Yang, Hai; Huang, Xianwei; Yu, Xinliang] Hunan Inst Engn, Coll Mat & Chem Engn, Hunan Prov Key Lab Environm Catalysis & Waste Reg, Xiangtan 411104, Hunan, Peoples R China; [Yu, Xinliang] Donghu Rd 18, Xiangtan 411104, Hunan, Peoples R China published Machine learning-based prediction of toxicity of organic compounds towards fathead minnow in 2020, Cited 30. The Name is 2,6-Difluorobenzoic acid. Through research, I have a further understanding and discovery of 385-00-2.
Predicting the acute toxicity of a large dataset of diverse chemicals against fathead minnows (Pimephales promelas) is challenging. In this paper, 963 organic compounds with acute toxicity towards fathead minnows were split into a training set (482 compounds) and a test set (481 compounds) with an approximate ratio of 1 : 1. Only six molecular descriptors were used to establish the quantitative structure-activity/toxicity relationship (QSAR/QSTR) model for 96 hourpLC(50)through a support vector machine (SVM) along with genetic algorithm. The optimal SVM model (R-2= 0.756) was verified using both internal (leave-one-out cross-validation) and external validations. The validation results (q(int)(2)= 0.699 andq(ext)(2)= 0.744) were satisfactory in predicting acute toxicity in fathead minnows compared with other models reported in the literature, although our SVM model has only six molecular descriptors and a large data set for the test set consisting of 481 compounds.
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Reference:
Isothiazole – Wikipedia,
,Isothiazole – ScienceDirect.com