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Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization

机译:使用矩阵正则化和相似性正则化改进细胞系中抗癌药物反应的预测

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摘要

BackgroundHuman cancer cell lines are used in research to study the biology of cancer and to test cancer treatments. Recently there are already some large panels of several hundred human cancer cell lines which are characterized with genomic and pharmacological data. The ability to predict drug responses using these pharmacogenomics data can facilitate the development of precision cancer medicines. Although several methods have been developed to address the drug response prediction, there are many challenges in obtaining accurate prediction.
机译:背景技术人类癌细胞系用于研究癌症的生物学和测试癌症的治疗方法。最近,已经有几百个由基因组和药理学数据表征的数百个人类癌细胞系的大型面板。使用这些药物基因组学数据预测药物反应的能力可以促进精密癌症药物的开发。尽管已经开发了几种方法来解决药物反应的预测问题,但是在获得准确的预测结果时仍然存在许多挑战。

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