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Prediction method of drug susceptibility using the factor is selected and the selection method specified drug sensitivity factor

机译:选择使用该因子的药物敏感性预测方法,并选择指定药物敏感性因子的方法

摘要

Based on drug sensitivity data and extensive gene expression data, a model was constructed by multivariate analysis with the partial least squares method type 1. Further, the model was optimized using modeling power and genetic algorithm. Thereby, the degree of contribution of the respective genes to drug sensitivity was determined to select genes with a high degree of contribution. In addition, the levels of gene expression in specimens were analyzed, and then the drug sensitivity was predicted based on the model. The predicted values agreed well with those drug sensitivity values determined experimentally. The drug sensitivity-predicting method provided by the present invention enables assessment of the effectiveness of a drug prior to administration using small quantities of specimens associated with diseases such as cancer. Since this enables the selection of the most suitable drug for each patient, the present invention is very useful in improving a patient's quality of life (QOL).
机译:基于药物敏感性数据和广泛的基因表达数据,通过偏最小二乘法1型进行多变量分析构建模型。此外,使用建模能力和遗传算法对模型进行了优化。由此,确定各个基因对药物敏感性的贡献度以选择具有高度贡献度的基因。此外,分析样本中的基因表达水平,然后基于该模型预测药物敏感性。预测值与实验确定的药物敏感性值非常吻合。本发明提供的药物敏感性预测方法能够使用少量与疾病如癌症有关的样品在给药前评估药物的有效性。由于这使得能够为每个患者选择最合适的药物,因此本发明在改善患者的生活质量(QOL)方面非常有用。

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