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STRING v11: protein–protein association networks with increased coverage supporting functional discovery in genome-wide experimental datasets

机译:STRING v11:覆盖面更广的蛋白质-蛋白质关联网络支持全基因组实验数据集中的功能性发现

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摘要

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at .
机译:蛋白质及其功能相互作用形成了细胞机制的骨干。为了充分理解生物学现象,需要考虑它们的连通性网络,但是有关蛋白质间相互作用的可用信息并不完整,并且注释水平和可靠性也各不相同。 STRING数据库旨在收集,评分和整合所有可公开获得的蛋白质间相互作用信息的来源,并通过计算预测对这些来源进行补充。其目标是建立一个全面,客观的全球网络,包括直接(物理)和间接(功能)交互。最新版本的STRING(11.0)将其涵盖的生物数量增加了一倍以上,达到5090。最重要的新功能是可以上传整个基因组范围的数据集作为输入的选项,允许用户将子集可视化为交互网络,并可以对整个输入进行基因集富集分析。为了进行富集分析,STRING实施了著名的分类系统,如Gene Ontology和KEGG,但还提供了基于高通量文本挖掘以及关联网络本身的层次聚类的其他新分类系统。可在上在线获取STRING资源。

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