Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update is a dataset published in Nucleic Acids Research (2016). On theSindex it has a DataRank of 15.9, placing it in the top 11.1% of the data-sharing corpus. It has been cited 11,578 times, with 191 citing works in its 1-hop citation network. Its calibrated FAIR score is 39/100.
Abstract
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
1.4
From this paper's citation signal
Citation Network Contribution
14.5
From 191 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profilesProceedings of the National Academy of Sciences200555,906 citationsDataRank 1.6
- KEGG: Kyoto Encyclopedia of Genes and GenomesNucleic Acids Research200038,911 citationsDataRank 25.4Top 2%
- Metascape provides a biologist-oriented resource for the analysis of systems-level datasetsNature Communications201915,474 citationsDataRank 14.7Top 13%
- Integrating single-cell transcriptomic data across different conditions, technologies, and speciesNature Biotechnology201814,465 citationsDataRank 1.4
- NCBI GEO: archive for functional genomics data sets—updateNucleic Acids Research201210,702 citationsDataRank 20.2Top 5%
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 9% comes from its base citations and 91% from the citation network (191 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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