Bo Tian, Lin Hu, Ruo Jia
College of Communications Engineering, Army Engineering University, Nanjing, 210007, China
Breast cancer is one of the most common and fatal cancers in the world. Therefore, this paper uses data mining and prediction technology, which is of great significance. In this paper, firstly, the relevant data were collected, and the Pearson correlation coefficients of 729 molecular descriptors in 1974 compounds were calculated respectively, and the correlation coefficient distribution map was obtained. Through observation, all the molecular descriptors were 0 elements. Then the grey correlation analysis method was used to analyze the correlation degree, and the grey correlation value between the information of 729 molecular descriptors and the bioactivity value of ER α was obtained. Then, making use of the advantage of canonical correlation analysis in feature extraction, according to the feature selection of linear combination coefficient, the molecular descriptors with the most significant effect on biological activity were selected.
Breast cancer, Canonical correlation analysis, Gray correlation analysis
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