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Predicting effective drug combinations via network propagation

机译:通过网络传播预测有效药物组合

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Drug combinations are frequently used in treating complex diseases including cancer, diabetes, arthritis and hypertension. Most drug combinations were found in empirical ways so there is a need of efficient computational methods. Here we present a novel method based on network analysis which estimates the efficacy of drug combinations from a perturbation analysis performed on a protein-protein association network. The results suggest that those drugs are likely to form effective combinations that perturb a large number of proteins in common, even if the original targets are found in seemingly unrelated pathways.
机译:药物组合经常用于治疗复杂的疾病,包括癌症,糖尿病,关节炎和高血压。大多数药物组合都是通过经验发现的,因此需要有效的计算方法。在这里,我们提出了一种基于网络分析的新方法,该方法通过对蛋白质-蛋白质缔合网络进行扰动分析来估计药物组合的功效。结果表明,即使在看似无关的途径中发现了最初的靶标,这些药物也可能形成干扰大量共同蛋白质的有效组合。

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