InnateDB

InnateDB integrates manually curated and public-source molecular interactions and pathways to support systems-level analysis of innate immune responses in human, mouse, and bovine.

Key Features:

• Manually Curated Data: Over 3,500 experimentally verified interactions relevant to innate immunity have been contextually annotated through review of more than 1,000 publications.
• Integration with Public Databases: Known pathways and molecular interactions from major public databases are aggregated to extend coverage of innate immunity components.
• Network Visualization Software: Tools for visualizing complex molecular interaction networks enable representation of non-linear signaling relationships.
• Pathway Analysis Tools: Computational pathway analysis functions support interrogation of signaling mechanisms underlying innate immune responses.
• Orthologous Interaction Network Construction: Capabilities for building orthology-based interaction networks facilitate cross-species comparative analyses.
• Gene Expression Data Overlay: Functionality to map gene expression data onto molecular interaction networks and pathway contexts for integrated analyses.
• Species Coverage: Focused coverage of the innate immunity interactome for human, mouse, and bovine species.

Scientific Applications:

• Systems-level Network Analysis: Elucidation of complex innate immune signaling networks beyond linear pathway models.
• Pathway and Signaling Interpretation: Identification and interpretation of signaling pathways and molecular mechanisms in innate immunity.
• Comparative and Orthology Studies: Construction and comparison of orthologous interaction networks across human, mouse, and bovine.
• Integrative Expression Analysis: Integration of gene expression data with interaction networks to generate hypotheses about immune response regulation.

Methodology:

Manually curate experimentally verified interactions from publications; integrate known pathways and interactions from public databases; construct orthologous interaction networks; perform network visualization and pathway analysis; and overlay gene expression data onto interaction networks.