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Research Article

基于多个异构网络的HeteSim评分预测疾病合并症

卷 19, 期 4, 2019

页: [232 - 241] 页: 10

弟呕挨: 10.2174/1566523219666190917155959

价格: $65

摘要

背景：越来越多的实验研究表明，与单一疾病的患者相比，疾病合并症给患者带来更多痛苦，并导致标准治疗失败。因此，准确预测潜在合并症对于设计更有效的治疗策略至关重要。然而，在临床中仅发现了少数疾病合并症。 目的：在这项工作中，我们提出PCHS，一种预测疾病合并症的有效计算方法。 材料和方法：我们使用HeteSim度量来计算全球异构网络中不同疾病对的相关性得分，该得分基于生物学信息整合了六个网络，包括疾病-疾病关联，药物-药物相互作用，蛋白质-蛋白质相互作用和关联其中。我们基于HeteSim得分使用支持向量机（SVM）构建了预测模型。 结果与结论：结果表明，PCHS的性能明显优于以前的最新方法，并且在10倍交叉验证中的AUC得分为0.90。此外，我们的一些预测已在文献中得到验证，表明了我们方法的有效性。

关键词: 疾病合并症，HoteSim量度，异构网络，疾病基因，疾病药物，蛋白质相互作用。

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