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NET-GE:一个基于网络的人类基因富集网络服务器。

NET-GE: a web-server for NETwork-based human gene enrichment.

作者信息

Bovo Samuele, Di Lena Pietro, Martelli Pier Luigi, Fariselli Piero, Casadio Rita

机构信息

Biocomputing Group, CIG, Interdepartmental Center «Luigi Galvani» for Integrated Studies of Bioinformatics, Biophysics and Biocomplexity, University of Bologna, Bologna, Italy.

DISI, University of Bologna, Bologna, Italy.

出版信息

Bioinformatics. 2016 Nov 15;32(22):3489-3491. doi: 10.1093/bioinformatics/btw508. Epub 2016 Aug 2.

Abstract

MOTIVATION

Gene enrichment is a requisite for the interpretation of biological complexity related to specific molecular pathways and biological processes. Furthermore, when interpreting NGS data and human variations, including those related to pathologies, gene enrichment allows the inclusion of other genes that in the human interactome space may also play important key roles in the emergency of the phenotype. Here, we describe NET-GE, a web server for associating biological processes and pathways to sets of human proteins involved in the same phenotype RESULTS: NET-GE is based on protein-protein interaction networks, following the notion that for a set of proteins, the context of their specific interactions can better define their function and the processes they can be related to in the biological complexity of the cell. Our method is suited to extract statistically validated enriched terms from Gene Ontology, KEGG and REACTOME annotation databases. Furthermore, NET-GE is effective even when the number of input proteins is small.

AVAILABILITY AND IMPLEMENTATION

NET-GE web server is publicly available and accessible at http://net-ge.biocomp.unibo.it/enrich CONTACT: gigi@biocomp.unibo.itSupplementary information: Supplementary data are available at Bioinformatics online.

摘要

动机

基因富集是解读与特定分子途径和生物过程相关的生物复杂性的必要条件。此外,在解读NGS数据和人类变异(包括与病理学相关的变异)时,基因富集能够纳入在人类相互作用组空间中可能在表型出现过程中也发挥重要关键作用的其他基因。在此,我们描述了NET - GE,一个用于将生物过程和途径与参与相同表型的人类蛋白质集相关联的网络服务器。结果:NET - GE基于蛋白质 - 蛋白质相互作用网络,其理念是对于一组蛋白质,它们特定相互作用的背景能够更好地定义其功能以及它们在细胞生物复杂性中可能相关的过程。我们的方法适合从基因本体论、KEGG和REACTOME注释数据库中提取经过统计验证的富集术语。此外,即使输入蛋白质的数量很少,NET - GE也很有效。

可用性和实现方式

NET - GE网络服务器可公开获取,网址为http://net - ge.biocomp.unibo.it/enrich 联系方式:gigi@biocomp.unibo.it 补充信息:补充数据可在《生物信息学》在线获取。

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