GOLEM: an interactive graph-based gene-ontology navigation and analysis tool
Open accessAbstract
BACKGROUND: The Gene Ontology has become an extremely useful tool for the analysis of genomic data and structuring of biological knowledge. Several excellent software tools for navigating the gene ontology have been developed. However, no existing system provides an interactively expandable graph-based view of the gene ontology hierarchy. Furthermore, most existing tools are web-based or require an Internet connection, will not load local annotations files, and provide either analysis or visualization functionality, but not both. RESULTS: To address the above limitations, we have developed GOLEM (Gene Ontology Local Exploration Map), a visualization and analysis tool for focused exploration of the gene ontology graph. GOLEM allows the user to dynamically expand and focus the local graph structure of the gene ontology hierarchy in the neighborhood of any chosen term. It also supports rapid analysis of an input list of genes to find enriched gene ontology terms. The GOLEM application permits the user either to utilize local gene ontology and annotations files in the absence of an Internet connection, or to access the most recent ontology and annotation information from the gene ontology webpage. GOLEM supports global and organism-specific searches by gene ontology term name, gene ontology id and gene name. CONCLUSION: GOLEM is a useful software tool for biologists interested in visualizing the local directed acyclic graph structure of the gene ontology hierarchy and searching for gene ontology terms enriched in genes of interest. It is freely available both as an application and as an applet at http://function.princeton.edu/GOLEM.
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Biological ontologies are large hierarchies with a DAG structure, so existing tools for visualizing ontologies can have direct application to data-driven multiscale models.
“Biological ontologies are large hierarchies which also have a DAG structure; as such, existing tools for visualizing ontologies can also have direct application to data-driven multiscale models (Binns et al., 2009; Eden et al., 2009; Sealfon et al., 2006; Supek et al., 2011; Zhu et al., 2019).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Sealfon et al., 2006
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- Authors
- Sealfon, R. S., Hibbs, M. A., Huttenhower, C., Myers, C. L., & Troyanskaya, O. G.
- Affiliations
- Princeton University (US)
- Corresponding author
- Troyanskaya, Olga G
- Venue
- BMC Bioinformatics
- Published
- 2006-10-10
- Volume
- 7
- Issue
- 1
- Pages
- 443-443
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W1912468900
- Cited by
- 58
- References
- 14
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2022: 1 · 2021: 4 · 2020: 3 · 2019: 1 · 2017: 1 · 2016: 3 · 2015: 1 · 2014: 2 · 2013: 2 · 2012: 4
- FWCI
- 2.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- PubMed (publishedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (0513552, P50 GM071508, 9972930)
- National Institutes of Health (GM071508, HG003284)
- National Human Genome Research Institute (T32HG003284)
- National Institute of General Medical Sciences (GM071508, R01GM071966, GM071966, P50GM071508)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- Gene Ontology, Golem, network visualization, ontological hierarchy, gene ontology enrichment, directed acyclic graphs, genome annotation, software tools
- MeSH terms
- Computer Graphics, Database Management Systems, Documentation, Proteins, Software, User-Computer Interface, Information Storage and Retrieval, Protein Interaction Mapping, Databases, Protein
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