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A study on the pattern recognition of thermophilic and mesophilic proteins / 生物工程学报
Chinese Journal of Biotechnology ; (12): 960-964, 2005.
Article in Chinese | WPRIM | ID: wpr-237043
ABSTRACT
Pattern recognition of thermophilic and mesophilic proteins were studied through principle component analysis, partial least-square regression and BP neural network. The results showed that the fitting accuracy of the three methods was 92%, 95% and 98%, respectively. And the forecasting accuracy was 60%, 72.5% and 72.5%, respectively. The best forecasting accuracy for thermophilic proteins was 75%, and for mesophilic proteins was 85%. A mathematical model was established and the biological meaning of it was expatiated on, a new method to discriminate the thermophilic and mesophilic proteins based on their sequences was established here.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Pattern Recognition, Automated / Proteins / Discriminant Analysis / Least-Squares Analysis / Chemistry / Neural Networks, Computer / Principal Component Analysis / Genetics / Amino Acids / Hot Temperature Language: Chinese Journal: Chinese Journal of Biotechnology Year: 2005 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Pattern Recognition, Automated / Proteins / Discriminant Analysis / Least-Squares Analysis / Chemistry / Neural Networks, Computer / Principal Component Analysis / Genetics / Amino Acids / Hot Temperature Language: Chinese Journal: Chinese Journal of Biotechnology Year: 2005 Type: Article