Identifying the Mechanism of Toxic Action of Selected Compounds by Artificial Neural Networks

摘要：

In this study, classifying and predicting the nonpolar narcosis, polar narcosis and reactive toxicity mechanism for 150 selected organic compounds were investigated using Artificial Neural Networks (ANNs). The variables used were the logarithm of octanolwater partition coefficients (logKow) and 10 quantum chemical parameters including the descriptors of energy, charge, and volume, which calculated with Gaussian 98. The 150 selected organic compounds were divided into two sets: training set (135 compounds) and test set (15 compounds). Supervised learning with backpropagation (BP) arithmetic was used. The results showed that the training error of network was smaller than 10-13, and 100％ correct classification was achieved for test set.

关键词： Mechanism of toxic action Quantum chemical descriptors Artificial Neural Networks BP paradigm

作者: Li Zhang Yulong Lou

作者单位: School of Chemical and environmental engineering Jianghan University Wuhan,China Peoples Liberation Army Communication Command Academy Wuhan,China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronic & Mechanical Engineering and Information Technology(EMEIT 2011)(2011年机电工程与信息技术国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 1935-1938

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）