Szklarczyk Damian, Morris John H, Cook Helen, Kuhn Michael, Wyder Stefan, Simonovic Milan, Santos Alberto, Doncheva Nadezhda T, Roth Alexander, Bork Peer, Jensen Lars J, von Mering Christian
Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Resource on Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94158-2517, USA.
Nucleic Acids Res. 2017 Jan 4;45(D1):D362-D368. doi: 10.1093/nar/gkw937. Epub 2016 Oct 18.
A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
对细胞功能的全系统理解需要了解所表达蛋白质之间的所有功能相互作用。STRING数据库旨在通过整合大量生物体已知的和预测的蛋白质-蛋白质关联数据来收集和整合这些信息。STRING中的关联包括直接(物理)相互作用以及间接(功能)相互作用,只要两者都是特异性的且具有生物学意义。除了收集和重新评估关于蛋白质-蛋白质相互作用的现有实验数据,以及从经过整理的数据库中导入已知的通路和蛋白质复合物外,相互作用预测还来源于以下几个方面:(i)系统共表达分析,(ii)跨基因组共享选择信号的检测,(iii)对科学文献的自动文本挖掘,以及(iv)基于基因直系同源性在生物体之间进行相互作用知识的计算转移。在STRING的最新版本10.5中,最大的变化涉及数据传播:网络前端已被完全重新设计,以减少对过时浏览器技术的依赖,并且现在还可以在流行的Cytoscape软件框架内查询该数据库。进一步的改进包括对用户输入进行功能富集的自动背景分析,以及简化的下载选项。STRING资源可在网上获取,网址为http://string-db.org/ 。