enrichr-kg

is a Knowledge Graph.

Enrichr-KG is a Ma'ayan Lab knowledge graph and enrichment web resource built from Enrichr gene set libraries, connecting genes to pathways, diseases, drugs, cell types, ontologies, and other functional annotations for graph-based exploration and enrichment analysis.

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Domains

biomedical, genomics, systems biology, drug discovery, biological systems

License

CC BY 4.0

Homepage

enrichr-kg

Repository

GitHub

Infores ID

Unknown

FAIRsharing ID

Unknown

Product Summary

Products

From this Resource
ID Name URL Category Format Description
enrichr-kg.graph Enrichr-KG Neo4j Database ❔ GraphProduct neo4j Neo4j graph database integrating Enri...
From other Resources
ID Name URL Category Format Relation Description
enrichr-kg.portal Enrichr-KG Explorer enrichr-kg GraphicalInterface http had primary source Interactive web interface for gene se...
enrichr-kg.api Enrichr-KG API api ProgrammingInterface json had primary source API surface for programmatic access t...

Details

Enrichr-KG

Enrichr-KG is a Ma’ayan Lab knowledge graph and enrichment-analysis resource that builds on the Enrichr library ecosystem. Its public interface supports standard gene-list submission, term-centric exploration of Enrichr libraries, and graph traversal across connected biological entities.

Key Features

Comprehensive Integration

  • Integrates Enrichr gene set libraries covering multiple biological domains
  • Connects genes to functional terms, pathways, diseases, and drug perturbations
  • Spans multiple species with focus on human, mouse, and other model organisms
  • Contains large numbers of gene-term associations from curated, imported, and derived libraries exposed through the Enrichr ecosystem

Multi-Modal Connectivity

  • Gene-to-pathway associations from KEGG, Reactome, WikiPathways
  • Gene-disease relationships from DisGeNET, GWAS Catalog, and clinical databases
  • Drug-gene interactions from LINCS L1000, CREEDS, and chemical perturbation datasets
  • Cell type and tissue-specific expression patterns from single-cell and bulk RNA-seq

Interactive Exploration

  • Web-based interface for gene-list enrichment, single-term search, and two-term graph searches
  • Shortest path analysis between biological entities
  • Neighborhood exploration around genes, diseases, drugs, and pathways
  • Customizable visualization and export capabilities

Original Sources

  • Enrichr gene set libraries and associated enrichment-analysis workflows

Applications

Drug Repurposing

  • Identify potential therapeutic targets through disease-gene-drug networks
  • Explore mechanism of action for existing drugs
  • Predict drug side effects and contraindications

Biomarker Discovery

  • Connect disease phenotypes to molecular signatures
  • Identify diagnostic and prognostic biomarkers
  • Explore tissue-specific disease mechanisms

Pathway Analysis

  • Multi-layered pathway enrichment across different databases
  • Cross-species pathway conservation analysis
  • Identification of pathway crosstalk and regulatory networks

Data Sources

Enrichr-KG is built from the Enrichr collection of gene set libraries, which in turn aggregate and normalize content from many upstream biological resources. The public Enrichr-KG site highlights integrated library families spanning pathway databases such as KEGG, Reactome, and WikiPathways; disease and phenotype resources such as GWAS Catalog, DisGeNET, HPO, and MGI; perturbation and drug-signature resources including LINCS and DepMap; and expression- or cell-type-oriented resources such as ARCHS4, Tabula Sapiens, Tabula Muris, HuBMAP, and GTEx-derived collections.

Automated Evaluation

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Created: September 23, 2025 | Last modified: May 21, 2026