The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible
Please always quote using this URN: urn:nbn:de:bvb:20-opus-181445
- 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 onA 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/.…
Author: | Damian Szklarczyk, John H. Morris, Helen Cook, Michael Kuhn, Stefan Wyder, Milan Simonovic, Aalberto Santos, Nadezhda T. Doncheva, Alexander Roth, Peer Bork, Lars J. Jensen, Christian von Mering |
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URN: | urn:nbn:de:bvb:20-opus-181445 |
Document Type: | Journal article |
Faculties: | Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften |
Language: | English |
Parent Title (English): | Nucleic Acids Research |
Year of Completion: | 2017 |
Volume: | 45 |
Issue: | D1 |
Pagenumber: | D362–D368 |
Source: | Nucleic Acids Research (2017) 45:D1, D362–D368. https://doi.org/10.1093/nar/gkw937 |
DOI: | https://doi.org/10.1093/nar/gkw937 |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Tag: | cellular function; proteins; quality control; string database |
Release Date: | 2024/09/18 |
Licence (German): | CC BY-NC: Creative-Commons-Lizenz: Namensnennung, Nicht kommerziell 4.0 International |