Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

Enrichr-KG

General information

URL: https://maayanlab.cloud/enrichr-kg
Full name:
Description: Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization.
Year founded: 2023
Last update: 2023
Version: v1.0
Accessibility:
Accessible
Country/Region: United States

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Icahn School of Medicine at Mount Sinai
Address: John Erol Evangelista, Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, NY, NY, USA
City:
Province/State:
Country/Region: United States
Contact name (PI/Team): Avi Ma’ayan
Contact email (PI/Helpdesk): avi.maayan@mssm.edu

Publications

37166973
Enrichr-KG: bridging enrichment analysis across multiple libraries. [PMID: 37166973]
John Erol Evangelista, Zhuorui Xie, Giacomo B Marino, Nhi Nguyen, Daniel J B Clarke, Avi Ma'ayan

Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enrichment analysis with many gene set libraries from different categories, integrating enrichment results across libraries and domains of knowledge can further hypothesis generation. To this end, Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization. The enrichment results are presented as subgraphs made of nodes and links that connect genes to their enriched terms. In addition, users of Enrichr-KG can add gene-gene links, as well as predicted genes to the subgraphs. This graphical representation of cross-library results with enriched and predicted genes can illuminate hidden associations between genes and annotated enriched terms from across datasets and resources. Enrichr-KG currently serves 26 gene set libraries from different categories that include transcription, pathways, ontologies, diseases/drugs, and cell types. To demonstrate the utility of Enrichr-KG we provide several case studies. Enrichr-KG is freely available at: https://maayanlab.cloud/enrichr-kg.

Nucleic Acids Res. 2023:51(W1) | 125 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
314/6895 (95.46%)
Expression:
46/1347 (96.659%)
Pathway:
25/451 (94.678%)
314
Total Rank
106
Citations
53
z-index

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Record metadata

Created on: 2023-08-28
Curated by:
Yuanyuan Cheng [2023-09-13]
Yue Qi [2023-09-12]
Yuanyuan Cheng [2023-09-04]
Xinyu Zhou [2023-08-28]