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Drug repositioning by integrating target information through a heterogeneous network model

机译:通过异构网络模型整合目标信息来进行药物重新定位

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摘要

>Motivation: The emergence of network medicine not only offers more opportunities for better and more complete understanding of the molecular complexities of diseases, but also serves as a promising tool for identifying new drug targets and establishing new relationships among diseases that enable drug repositioning. Computational approaches for drug repositioning by integrating information from multiple sources and multiple levels have the potential to provide great insights to the complex relationships among drugs, targets, disease genes and diseases at a system level.>Results: In this article, we have proposed a computational framework based on a heterogeneous network model and applied the approach on drug repositioning by using existing omics data about diseases, drugs and drug targets. The novelty of the framework lies in the fact that the strength between a disease–drug pair is calculated through an iterative algorithm on the heterogeneous graph that also incorporates drug-target information. Comprehensive experimental results show that the proposed approach significantly outperforms several recent approaches. Case studies further illustrate its practical usefulness.>Availability and implementation: >Contact: >Supplementary information: are available at Bioinformatics online.
机译:>动机:网络医学的出现不仅为更好,更全面地了解疾病的分子复杂性提供了更多机会,而且还为确定新的药物靶标和建立疾病之间的新关系提供了有希望的工具可以重新定位药物。通过整合来自多个来源和多个级别的信息来进行药物重新定位的计算方法,有可能为系统级别的药物,靶标,疾病基因和疾病之间的复杂关系提供深刻的见解。>结果:文章中,我们提出了一个基于异构网络模型的计算框架,并通过使用有关疾病,药物和药物靶点的现有组学数据将这种方法应用于药物重新定位。该框架的新颖之处在于,通过异质图上的迭代算法计算疾病-药物对之间的强度,该算法还结合了药物靶标信息。全面的实验结果表明,所提出的方法明显优于最近的几种方法。案例研究进一步说明了其实用性。>可用性和实现: >联系方式: >补充信息:可在Bioinformatics在线获得。

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