A prediction model of substrates and non-substrates of breast cancer resistance protein (BCRP) developed by GA–CG–SVM method
| العنوان: | A prediction model of substrates and non-substrates of breast cancer resistance protein (BCRP) developed by GA–CG–SVM method |
|---|---|
| المؤلفون: | Lin-Li Li, Shengyong Yang, Hui Zhang, Chang-Ying Ma, Hua-Lin Wan, Qing-Qing Xie, Lei Zhong, Li-Jun Yang |
| المصدر: | Computers in Biology and Medicine. 41:1006-1013 |
| بيانات النشر: | Elsevier BV, 2011. |
| سنة النشر: | 2011 |
| مصطلحات موضوعية: | Support Vector Machine, Abcg2, information science, Antineoplastic Agents, Breast Neoplasms, Health Informatics, Computational biology, computer.software_genre, Models, Biological, Predictive Value of Tests, ATP Binding Cassette Transporter, Subfamily G, Member 2, Animals, Humans, Screening tool, Mathematics, Training set, biology, Drug discovery, Neoplasm Proteins, Computer Science Applications, Support vector machine, Drug Resistance, Neoplasm, biology.protein, ATP-Binding Cassette Transporters, Female, Data mining, computer |
| الوصف: | Breast cancer resistance protein (BCRP) is one of the key multi-drug resistance proteins, which significantly influences the therapeutic effects of many drugs, particularly anti-cancer drugs. Thus, distinguishing between substrates and non-substrates of BCRP is important not only for clinical use but also for drug discovery and development. In this study, a prediction model of the substrates and non-substrates of BCRP was developed using a modified support vector machine (SVM) method, namely GA-CG-SVM. The overall prediction accuracy of the established GA-CG-SVM model is 91.3% for the training set and 85.0% for an independent validation set. For comparison, two other machine learning methods, namely, C4.5 DT and k-NN, were also adopted to build prediction models. The results show that the GA-CG-SVM model is significantly superior to C4.5 DT and k-NN models in terms of the prediction accuracy. To sum up, the prediction model of BCRP substrates and non-substrates generated by the GA-CG-SVM method is sufficiently good and could be used as a screening tool for identifying the substrates and non-substrates of BCRP. |
| تدمد: | 0010-4825 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::167c795e28a75b8643d2051d3c760355Test https://doi.org/10.1016/j.compbiomed.2011.08.009Test |
| حقوق: | CLOSED |
| رقم الانضمام: | edsair.doi.dedup.....167c795e28a75b8643d2051d3c760355 |
| قاعدة البيانات: | OpenAIRE |
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