Abstract
Breast cancer has become the focus of the pathological gene screening research. In this paper, logistic regression and multiple hypothesis testing are used to screen the pathological gene based on the existing breast cancer genetic data. Then referencing the confidence level, the p-value of logistic regression is used to screen the pathological gene initially. Furthermore, by considering the Type I error, the multiple hypothesis testing is used to make the result accurate. In addition, SVM is used to test the reliability of this paper’s methods. In order to illustrate the feasibility of this method, each gene which screened by this method is tested and verified by the literature of breast cancer.
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This work was supported by the National Natural Science Foundation of China (Grand No. 11371174 and 11271163).
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Zhao, Y., Tang, XQ. (2018). Screening of Pathological Gene in Breast Cancer Based on Logistic Regression. In: Huang, DS., Jo, KH., Zhang, XL. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10955. Springer, Cham. https://doi.org/10.1007/978-3-319-95933-7_33
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DOI: https://doi.org/10.1007/978-3-319-95933-7_33
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