WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013

By Jing Wang, Dexter T. Duncan, Zhiao Shi, Bing Zhang. Nucleic Acids Res., 2013

1,550 citations recorded by the source corpus.

Functional enrichment analysis is an essential task for the interpretation of gene lists derived from large-scale genetic, transcriptomic and proteomic studies. WebGestalt (WEB-based GEne SeT AnaLysis Toolkit) has become one of the popular software tools in this field since its publication in 2005. For the last 7 years, WebGestalt data holdings have grown substantially to satisfy the requirements of users from different research areas. The current version of WebGestalt supports 8 organisms and 201 gene identifiers from various databases and different technology platforms, making it directly available to the fast growing omics community. Meanwhile, by integrating functional categories derived from centrally and publicly curated databases as well as computational analyses, WebGestalt has significantly increased the coverage of functional categories in various biological contexts including Gene Ontology, pathway, network module, gene–phenotype association, gene–disease association, gene–drug association and chromosomal location, leading to a total of 78 612 functional categories. Finally, new interactive features, such as pathway map, hierarchical network visualization and phenotype ontology visualization have been added to WebGestalt to help users better understand the enrichment results. WebGestalt can be freely accessed through http://www.webgestalt.org or http://bioinfo.vanderbilt.edu/webgestalt/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/957fed4fe44b005a8cce18ec76736bee2d436432

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Citations in the corpus

In Vivo Imaging Reveals Extracellular Vesicle-Mediated Phenocopying of Metastatic Behavior (2015, methodology): “(F) These genes in (D) were used as input for WebGestalt analysis (Wang et al., 2013).”
WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs (2019, methodology): “Following updates in 2013 and 2017 (2,3), WebGestalt had 27 000 unique users per year according to Google Analytics and has been cited in 739 papers indexed in Scopus since 2017.”
CIRI: an efficient and unbiased algorithm for de novo circular RNA identification (2015, methodology): “We applied Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses to a total of 966 gene IDs of exonic circRNAs present in more than 10 cell types [20,21].”
Deep Proteomics of the Xenopus laevis Egg using an mRNA-derived Reference Database (2014, positive): “With the current state of technology, RNA-seq is more sensitive than protein detection via mass spectrometry.”
g:Profiler—a web server for functional interpretation of gene lists (2016 update) (2016, neutral): “Tools such as Panther (14), FuncAssociate (15) and GOrilla (16) aim to support the analysis of many species, while others such as WebGestalt (17) focus on the convenient mapping of diverse gene identifiers.”
Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics Profiles (2020, methodology): “Enrichment analyses were performed using the Webgestalt tool [52] for the exploratory analyses for the case studies.”
iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections (2014, methodology): “Functional categories found enriched for co-factors of p53 were calculated by DAVID and WebGestalt [126] based on Gene Ontology and KEGG pathways.”