Minxi Rong1, Yong Li1,*, Xiaoli Guo1,*, Tao Zong2, Zhiyuan Ma2, Penglei Li2
Oncologie, Vol.24, No.2, pp. 309-327, 2022, DOI:10.32604/oncologie.2022.021256
Abstract Objectives: The ERα biological activity prediction model is constructed by the compound molecular data of the
anti-breast cancer therapeutic target ERα and its biological activity data, which improves the screening efficiency
of anti-breast cancer drug candidates and saves the time and cost of drug development. Methods: In this paper,
Ridge model is used to screen out molecular descriptors with a high degree of influence on the biological activity
of Erα and divide datasets with different numbers of the molecular descriptors by screening results. Random
Forest (RF) is trained by Root Mean Square Error (RMSE) and Coefficient of determination (R2) to… More >
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