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26 May 2023 Application of machine learning in anti-pancreatic cancer drugs
Li Yue
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Proceedings Volume 12700, International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023); 127003C (2023) https://doi.org/10.1117/12.2682341
Event: International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023), 2023, Nanchang, China
Abstract
Estrogen Receptor is closely linked to the growth of breast cancer, and breast tumor cells significantly depend on Estrogen Receptor. Therefore, it is of great practical significance to find compounds that can antagonize ERα activity as candidate drugs for the treatment of breast cancer. In drug research, the method of establishing compound activity prediction model is usually used to screen potential active compounds. In this paper, according to the provided ERα antagonist information, based on the screened biologically active compounds, the ADMET properties of the compounds were predicted by three different classification models. Predictive modeling studies were carried out; finally, the value range of each element in ADMET properties was imprecisely optimized to better guide the selection of anti-breast cancer drug candidates.
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Li Yue "Application of machine learning in anti-pancreatic cancer drugs", Proc. SPIE 12700, International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023), 127003C (26 May 2023); https://doi.org/10.1117/12.2682341
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KEYWORDS
Data modeling
Machine learning
Random forests
Education and training
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