摘要
定量构效关系(QSAR)对药物设计和新药研制、环境毒物的毒性评价与预测有着显著的作用,本文简单介绍了几种QSAR建模方法:多元线性回归(MLR)、主成分分析(PCA)、偏最小二乘法(PLS)、人工神经网络(ANN)和支持向量机(SVM),并对这几种不同的建模方法在实际中的应用进行举例。可以看出PLS和ANNS是优秀的建模方法,预测能力强,SVM通过结构风险最小化原则建模,有效将期望风险降至最低,模型预测力得到显著提高,在环境毒物评价中具有广阔的应用前景。
Quantitative structure - activity relationship of the design and ：levelopment of new drugs, toxicity evaluation and prediction of toxic environment plays a role. This paper briefly described several QSAR modeling methods ： multiple linear regression, principal component analysis, partial least squares, artificial neural network and support vector machine, and that several different modeling methods for the application in practice. It showed that the PLS and ANN were excellent modeling methods, predictive capability was very good, SVM modeling through structural risk minimization principle, to effectively minimized the risks expectations that the model prediction had improved significantly, and the environmental toxicology evaluation and prediction had broad application prospects.
出处
《农业环境科学学报》
CAS
CSCD
北大核心
2007年第B10期651-655,共5页
Journal of Agro-Environment Science
关键词
定量构效关系
多元线性回归
偏最小二乘法
支持向量机
人工神经网络
quantitative structure activity relationship
multiple linear regression
partial least squares
support vector machines
artificial neural networks
