A study on the pattern recognition of thermophilic and mesophilic proteins.
- Author:
Guang-Ya ZHANG
1
;
Bai-Shan FANG
Author Information
1. Institute of Industrial Biotechnology, Huaqiao University, Quanzhou 362021, China.
- Publication Type:Journal Article
- MeSH:
Amino Acids;
chemistry;
metabolism;
Discriminant Analysis;
Hot Temperature;
Least-Squares Analysis;
Models, Theoretical;
Neural Networks (Computer);
Pattern Recognition, Automated;
Principal Component Analysis;
Proteins;
chemistry;
genetics
- From:
Chinese Journal of Biotechnology
2005;21(6):960-964
- CountryChina
- Language:Chinese
-
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.
