ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

By Gabriela Bindea, Bernhard Mlecnik, Hubert Hackl, Pornpimol Charoentong, M. Tosolini, A. Kirilovsky, W. Fridman, Franck Pagès, Zlatko Trajanoski, Jérôme Galon. Bioinform., 2009

5,809 citations recorded by the source corpus.

Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5403c47e5ff80578ae475896431565535016e286

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Citations in the corpus

NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis (2019, methodology): “To improve the interpretability of the results from enrichment analysis, we have implemented an interactive enrichment network viewer based on a similar concept introduced by ClueGO and EnrichmentMap (32,33).”
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation (2010, methodology): “ClueGO and MCM are useful, as they offer an expressive and intuitive organization of gene-sets, applicable to any gene-set source.”
The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible (2016, background): “Cytoscape and its hundreds of apps provide numerous ways for users to interact with, visualize and analyze STRING networks (49), including integrating additional data from public repositories or their own experiments, changing visual styles and applying algorithms for network layout, clustering (50)”
Combining bioinformatics, network pharmacology and artificial intelligence to predict the mechanism of celastrol in the treatment of type 2 diabetes (2022, methodology): “0) (28) was used for enrichment analysis in Gene Ontology (GO) and contained annotations for Biological Process (BP), Cell Composition (CC) and Molecular Function (MF), and Kyoto Protocol Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to plot them into diagrams.”
Reprogramming of miRNA networks in cancer and leukemia. (2010, methodology): “The union of the target mRNAs with a score above 3 was used as an input to ClueGO.”
Proteomic and Metabolomic Characterization of COVID-19 Patient Sera (2020, methodology): “(B) The GO terms enriched using the Cytoscape plug-in ClueGO.”
Big Data Analytics in Healthcare (2015, methodology): “Category Selected applications Onto-Express [139, 140] Pathway analysis Breast cancer [141] GoMiner [142] Pathway analysis Pancreatic cancer [143] ClueGo [144] Pathway analysis Colorectal tumors [145] GSEA [146] Pathway analysis Diabetes [147] Pathway-Express [148] Pathway analysis Leukemia [149] Re”
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters (2012, neutral): “Therefore, several new tools such as ClueGO (Bindea et al., 2009) and goProfiles (Sánchez et al.”