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SubcellulaRVis:一个基于网络的工具,用于简化和可视化细胞内区室富集。

SubcellulaRVis: a web-based tool to simplify and visualise subcellular compartment enrichment.

机构信息

Division of Evolution, Infection & Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester M13 9PT, UK.

Division of Molecular & Cell Biology, School of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester M13 9PT, UK.

出版信息

Nucleic Acids Res. 2022 Jul 5;50(W1):W718-W725. doi: 10.1093/nar/gkac336.

Abstract

Cells contain intracellular compartments, including membrane-bound organelles and the nucleus, and are surrounded by a plasma membrane. Proteins are localised to one or more of these cellular compartments; the correct localisation of proteins is crucial for their correct processing and function. Moreover, proteins and the cellular processes they partake in are regulated by relocalisation in response to various cellular stimuli. High-throughput 'omics experiments result in a list of proteins or genes of interest; one way in which their functional role can be understood is through the knowledge of their subcellular localisation, as deduced through statistical enrichment for Gene Ontology Cellular Component (GOCC) annotations or similar. We have designed a bioinformatics tool, named SubcellulaRVis, that compellingly visualises the results of GOCC enrichment for quick interpretation of the localisation of a group of proteins (rather than single proteins). We demonstrate that SubcellulaRVis precisely describes the subcellular localisation of gene lists whose locations have been previously ascertained. SubcellulaRVis can be accessed via the web (http://phenome.manchester.ac.uk/subcellular/) or as a stand-alone app (https://github.com/JoWatson2011/subcellularvis). SubcellulaRVis will be useful for experimental biologists with limited bioinformatics expertise who want to analyse data related to protein (re)localisation and location-specific modules within the intracellular protein network.

摘要

细胞包含细胞内区室,包括膜结合细胞器和细胞核,并被质膜包围。蛋白质定位于这些细胞区室之一或多个;蛋白质的正确定位对于其正确的加工和功能至关重要。此外,蛋白质及其参与的细胞过程受到各种细胞刺激的重新定位的调节。高通量“组学”实验产生了一组感兴趣的蛋白质或基因;了解它们的亚细胞定位的一种方法是通过统计富集基因本体细胞成分 (GOCC) 注释或类似注释来推断其功能作用。我们设计了一种名为 SubcellulaRVis 的生物信息学工具,它可以直观地显示 GOCC 富集的结果,以便快速解释一组蛋白质(而不是单个蛋白质)的定位。我们证明 SubcellulaRVis 可以精确描述先前确定位置的基因列表的亚细胞定位。SubcellulaRVis 可以通过网络(http://phenome.manchester.ac.uk/subcellular/)或独立应用程序(https://github.com/JoWatson2011/subcellularvis)访问。SubcellulaRVis 将对具有有限生物信息学专业知识但希望分析与蛋白质(再)定位和细胞内蛋白质网络中特定位置模块相关数据的实验生物学家非常有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0b9/9252817/52407e30c025/gkac336figgra1.jpg

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