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Predicting drug side effects based on link prediction in bipartite network

机译:基于二分网络链路预测预测药物副作用

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To pursue a new approach for discovering new side effects of drugs, we construct a drug-side effect network based on the SIDER2 database, and introducing link prediction methods in the network. We develop and evaluate the framework for drug side effect prediction based on link prediction in bipartite network. Integrating side effect appearance frequency has also been proved to be of value in improving the performance of drug side effect prediction.
机译:为了追求发现药物新副作用的新方法,我们基于Sider2数据库构建一种药物侧效网络,并在网络中引入链路预测方法。基于二分网络中的链路预测,我们开发和评估药物副作用预测框架。整合副作用外观频率也被证明是改善药物侧效应预测性能的价值。

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