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Chemical QSAR recognition by using fuzzy min-max neural-network / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 449-451, 2002.
Article in Chinese | WPRIM | ID: wpr-357005
ABSTRACT
By using the fuzzy min-max neural network, the quantitative structure-activity relationship (QSAR) of mutagenicity is studied. With the established QSAR model, the mutagenicity is predicted and the results showed that QASR is superior to linear-regression model. Further discussion on the models and the results is presented in this paper.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Cluster Analysis / Neural Networks, Computer / Fuzzy Logic / Quantitative Structure-Activity Relationship / Models, Chemical Type of study: Prognostic study Language: Chinese Journal: Journal of Biomedical Engineering Year: 2002 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Cluster Analysis / Neural Networks, Computer / Fuzzy Logic / Quantitative Structure-Activity Relationship / Models, Chemical Type of study: Prognostic study Language: Chinese Journal: Journal of Biomedical Engineering Year: 2002 Type: Article