omnipath

is an Aggregator.

It is part of the BER collection.

OmniPath is a comprehensive prior knowledge resource that integrates molecular interactions and biological pathway information from over 100 original databases and resources. It provides unified access to protein-protein interactions, gene regulatory interactions, enzyme-PTM relationships, protein complexes, protein annotations, and intercellular communication data through multiple interfaces including web services, R/Bioconductor packages, Python clients, and Cytoscape plugins.

Domains

systems biology, biological systems, proteomics, pathways

License

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Homepage

omnipath

Repository

GitHub

Infores ID

Unknown

FAIRsharing ID

Unknown

Product Summary

Products

From this Resource
ID Name URL Category Format Description
omnipath.webservice OmniPath Web Service queries ProgrammingInterface json Web service API providing programmati...
omnipath.r_package OmnipathR Package OmnipathR.html ProgrammingInterface mixed R/Bioconductor package (OmnipathR) fo...
omnipath.python_client OmniPath Python Client omnipath ProgrammingInterface python Python client library providing progr...
omnipath.cytoscape_plugin OmniPath Cytoscape Plugin omnipath ProcessProduct java Cytoscape plugin for importing and vi...
omnipath.explorer OmniPath Explorer explore.omnipathdb.org GraphicalInterface http Interactive database explorer for bro...
omnipath.pypath PyPath Database Builder pypath-omnipath ProcessProduct python Python package (pypath) for building ...
From other Resources
ID Name URL Category Format Description
bioteque.embeddings Bioteque Embeddings embeddings Product ❔ Network embeddings of the Bioteque gr...

Details

OmniPath

OmniPath is a comprehensive molecular biology prior knowledge database that integrates and harmonizes data from over 100 original resources to provide unified access to diverse types of molecular interactions and biological pathway information. Developed through collaboration between the Saez Lab at Universitat Pompeu Fabra and the Korcsmaros Lab at Earlham Institute, OmniPath serves as a central hub for accessing curated biological knowledge essential for systems biology and network medicine research.

Overview

The OmniPath database encompasses five major integrated databases that together provide a comprehensive view of molecular interactions within and between cells:

  1. Signaling Networks: Protein-protein interactions with directional information and effect signs, focusing on literature-curated signaling pathways
  2. Enzyme-PTM Relationships: Post-translational modification interactions between enzymes and their substrates
  3. Protein Complexes: Experimentally verified and computationally predicted protein complex compositions
  4. Molecular Annotations: Functional, structural, and localization annotations for proteins including Gene Ontology terms, pathway memberships, and tissue expression data
  5. Intercellular Communication: Ligand-receptor interactions and communication pathways between different cell types

Key Features

Comprehensive Integration

OmniPath aggregates data from over 100 original databases and resources, including major interaction databases (BioGRID, IntAct, MINT, STRING), pathway databases (Reactome, KEGG, SIGNOR, NetPath), and specialized resources for protein complexes (CORUM, ComplexPortal), post-translational modifications (PhosphoSitePlus, ELM), and intercellular communication (CellTalkDB, CellPhoneDB, ICELLNET).

Quality Control and Curation

The database emphasizes high-quality, literature-curated interactions over high-throughput experimental data. Each interaction is associated with literature references and experimental evidence, ensuring reliability for downstream analysis and modeling applications.

Multiple Access Methods

OmniPath provides flexible access through multiple interfaces designed for different user communities:

  • Web Service API for programmatic access and integration into computational workflows
  • R/Bioconductor Package (OmnipathR) for statistical analysis and visualization in R
  • Python Client for integration with Python-based data science pipelines
  • Cytoscape Plugin for network visualization and analysis
  • Interactive Web Interface for exploratory data access and querying

Network Medicine Applications

The integrated nature of OmniPath makes it particularly valuable for network medicine applications, enabling researchers to:

  • Construct comprehensive molecular interaction networks
  • Perform pathway enrichment analysis
  • Model intercellular communication networks
  • Integrate multi-omics data in the context of prior knowledge
  • Develop mechanistic models of disease processes

Applications and Use Cases

OmniPath supports a wide range of applications in systems biology and network medicine:

  • Pathway Analysis: Enrichment analysis and pathway reconstruction using comprehensive interaction networks
  • Network Modeling: Construction of mechanistic models incorporating protein-protein interactions, regulatory relationships, and intercellular communication
  • Multi-Omics Integration: Contextualization of genomics, transcriptomics, and proteomics data within comprehensive interaction networks
  • Drug Discovery: Target identification and mechanism of action studies using integrated molecular interaction data
  • Disease Research: Investigation of disease mechanisms through network-based approaches and intercellular communication analysis

Data Sources and Coverage

The database integrates data from diverse categories of resources:

  • Interaction Databases: BioGRID, IntAct, MINT, STRING, HPRD, InnateDB
  • Pathway Databases: Reactome, KEGG, SIGNOR, NetPath, WikiPathways
  • Regulatory Networks: DoRothEA, RegNetwork, TRRUST
  • Protein Complexes: CORUM, ComplexPortal, hu.MAP
  • Post-translational Modifications: PhosphoSitePlus, ELM, dbPTM
  • Intercellular Communication: CellTalkDB, CellPhoneDB, ICELLNET, ConnectomeDB
  • Functional Annotations: Gene Ontology, UniProt, Human Protein Atlas

This comprehensive integration ensures broad coverage of molecular interaction types while maintaining data quality through systematic curation and validation procedures.

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Created: July 08, 2025 | Last modified: September 27, 2025