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GUILDify v2.0:一种用于识别人类疾病、其共病和可药物治疗靶点的分子网络的工具。

GUILDify v2.0: A Tool to Identify Molecular Networks Underlying Human Diseases, Their Comorbidities and Their Druggable Targets.

机构信息

Structural Bioinformatics Group, Research Programme on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain.

Integrative Biomedical Informatics Group, Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain.

出版信息

J Mol Biol. 2019 Jun 14;431(13):2477-2484. doi: 10.1016/j.jmb.2019.02.027. Epub 2019 Mar 7.

Abstract

The genetic basis of complex diseases involves alterations on multiple genes. Unraveling the interplay between these genetic factors is key to the discovery of new biomarkers and treatments. In 2014, we introduced GUILDify, a web server that searches for genes associated to diseases, finds novel disease genes applying various network-based prioritization algorithms and proposes candidate drugs. Here, we present GUILDify v2.0, a major update and improvement of the original method, where we have included protein interaction data for seven species and 22 human tissues and incorporated the disease-gene associations from DisGeNET. To infer potential disease relationships associated with multi-morbidities, we introduced a novel feature for estimating the genetic and functional overlap of two diseases using the top-ranking genes and the associated enrichment of biological functions and pathways (as defined by GO and Reactome). The analysis of this overlap helps to identify the mechanistic role of genes and protein-protein interactions in comorbidities. Finally, we provided an R package, guildifyR, to facilitate programmatic access to GUILDify v2.0 (http://sbi.upf.edu/guildify2).

摘要

复杂疾病的遗传基础涉及多个基因的改变。揭示这些遗传因素之间的相互作用是发现新的生物标志物和治疗方法的关键。2014 年,我们引入了 GUILDify,这是一个用于搜索与疾病相关基因的网络服务器,它应用各种基于网络的优先级算法来寻找新的疾病基因,并提出候选药物。在这里,我们介绍了 GUILDify v2.0,这是对原始方法的重大更新和改进,其中我们包括了七种物种和 22 个人类组织的蛋白质相互作用数据,并纳入了 DisGeNET 的疾病-基因关联。为了推断与多种疾病相关的潜在疾病关系,我们引入了一种新的功能,用于使用排名最高的基因以及相关的生物学功能和途径(由 GO 和 Reactome 定义)的富集来估计两种疾病的遗传和功能重叠。对这种重叠的分析有助于确定基因和蛋白质-蛋白质相互作用在共病中的机制作用。最后,我们提供了一个 R 包,guildifyR,以方便对 GUILDify v2.0 的编程访问(http://sbi.upf.edu/guildify2)。

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