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Updated: Mar 3, 2026
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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
Published on: August 16, 2017
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WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit
Jing Wang1,2, Suhas Vasaikar1,2, Zhiao Shi1,2
1Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA.
Nucleic Acids Research
|May 5, 2017
Summary
WebGestalt 2017 enhances functional enrichment analysis for high-throughput omics data. It offers new analysis methods and improved usability for biologists, supporting more organisms and functional categories.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Functional enrichment analysis is crucial for interpreting high-throughput omics data.
- WebGestalt is a widely used web tool for this purpose, requiring continuous updates.
Purpose of the Study:
- To introduce WebGestalt 2017, an updated version of the functional enrichment analysis tool.
- To highlight new features and expanded capabilities for biological data interpretation.
Main Methods:
- WebGestalt 2017 supports 12 organisms and 324 gene identifiers.
- It includes 150,937 functional categories from public and computational sources.
- Users can upload custom data not supported by default.
Main Results:
- Added Gene Set Enrichment Analysis and Network Topology-based Analysis alongside Over-Representation Analysis.
- Introduced a user-friendly interface and the GOView tool for interactive exploration.
- Expanded support for diverse omics data and functional annotations.
Conclusions:
- WebGestalt 2017 provides a more comprehensive, powerful, and flexible platform for functional enrichment analysis.
- The tool facilitates efficient and interactive exploration of omics data interpretation.
- It is freely available online for the research community.
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