Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Faculty of Medical Laboratory Science, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
J Mol Biol. 2024 Sep 1;436(17):168705. doi: 10.1016/j.jmb.2024.168705. Epub 2024 Jul 23.
We introduce XGR-model (or XGRm), a web server made accessible at http://www.xgrm.pro, with the aim of meeting the increasing demand for effectively interpreting summary-level genomic data in model organisms. Currently, it hosts two enrichment analysers and two subnetwork analysers to support enrichment and subnetwork analyses for user-input mouse genomic data, whether gene-centric or genomic region-centric. The enrichment analysers identify ontology term enrichments for input genes (GElyser) or for genes linked from input genomic regions (RElyser). The subnetwork analysers rely on our previously established network algorithm to identify gene subnetworks from input gene-centric summary data (GSlyser) or from input region-centric summary data (RSlyser), leveraging network information about either functional interactions or pathway-derived interactions. Collectively, XGRm offers an all-in-one solution for gaining systems biology insights into summary-level genomic data in mice, underpinned by our commitment to regular updates as well as natural extensions to other model organisms.
我们介绍了 XGR-model(或 XGRm),这是一个可在 http://www.xgrm.pro 访问的网络服务器,旨在满足对有效解释模式生物汇总水平基因组数据的日益增长的需求。目前,它提供了两个富集分析器和两个子网分析器,以支持用户输入的鼠标基因组数据的富集和子网分析,无论是以基因为中心还是以基因组区域为中心。富集分析器确定输入基因的本体论术语富集(GElyser)或从输入基因组区域链接的基因的富集(RElyser)。子网分析器依赖于我们先前建立的网络算法,从输入的以基因为中心的汇总数据(GSlyser)或从输入的以区域为中心的汇总数据(RSlyser)中识别基因子网,利用关于功能相互作用或途径衍生相互作用的网络信息。总的来说,XGRm 为从系统生物学角度深入了解鼠标汇总水平基因组数据提供了一站式解决方案,这得益于我们对定期更新以及对其他模式生物的自然扩展的承诺。