Abstract

Protein networks have become a popular tool for analyzing and visualizing the often long lists of proteins or genes obtained from proteomics and other high-throughput technologies. One of the most popular sources of such networks is the STRING database, which provides protein networks for more than 2000 organisms, including both physical interactions from experimental data and functional associations from curated pathways, automatic text mining, and prediction methods. However, its web interface is mainly intended for inspection of small networks and their underlying evidence. The Cytoscape software, on the other hand, is much better suited for working with large networks and offers greater flexibility in terms of network analysis, import, and visualization of additional data. To include both resources in the same workflow, we created stringApp, a Cytoscape app that makes it easy to import STRING networks into Cytoscape, retains the appearance and many of the features of STRING, and integrates data from associated databases. Here, we introduce many of the stringApp features and show how they can be used to carry out complex network analysis and visualization tasks on a typical proteomics data set, all through the Cytoscape user interface. stringApp is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/stringapp .

Keywords

ProteomicsVisualizationComputer scienceComputational biologyData visualizationData scienceData miningBiologyGenetics

MeSH Terms

Computational BiologyData AnalysisInternetProtein Interaction MapsProteomicsSoftwareUser-Computer Interface

Affiliated Institutions

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Publication Info

Year
2018
Type
article
Volume
18
Issue
2
Pages
623-632
Citations
2266
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

2266
OpenAlex
1838
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Cite This

Nadezhda T. Doncheva, John H. Morris, Jan Gorodkin et al. (2018). Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. Journal of Proteome Research , 18 (2) , 623-632. https://doi.org/10.1021/acs.jproteome.8b00702

Identifiers

DOI
10.1021/acs.jproteome.8b00702
PMID
30450911
PMCID
PMC6800166

Data Quality

Data completeness: 86%