使用FALS方法从有机化合物的化学结构预测其对啮齿动物的致癌性。
Prediction of the rodent carcinogenicity of organic compounds from their chemical structures using the FALS method.
作者信息
Moriguchi I, Hirano H, Hirono S
机构信息
School of Pharmaceutical Sciences, Kitasato University, Tokyo, Japan.
出版信息
Environ Health Perspect. 1996 Oct;104 Suppl 5(Suppl 5):1051-8. doi: 10.1289/ehp.96104s51051.
Abstract
Fuzzy adaptive least-squares (FALS), a pattern recognition method recently developed in our laboratory for correlating structure with activity rating, was used to generate quantitative structure-activity relationship (QSAR) models on the carcinogenicity of organic compounds of several chemical classes. Using the predictive models obtained from the chemical class-based FALS QSAR approach, the rodent carcinogenicity or noncarcinogenicity of a group of organic chemicals currently being tested by the U.S. National Toxicology Program was estimated from their chemical structures.
摘要
模糊自适应最小二乘法（FALS）是我们实验室最近开发的一种用于将结构与活性评级相关联的模式识别方法，用于生成关于几类化学物质有机化合物致癌性的定量构效关系（QSAR）模型。利用基于化学类别的FALS QSAR方法获得的预测模型，根据一组目前正在由美国国家毒理学计划测试的有机化学品的化学结构，估算了它们在啮齿动物中的致癌性或非致癌性。
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