SIGNOR

SIGNOR provides a curated repository of experimentally validated causal interactions among proteins, chemicals, phenotypes, and complexes to support analysis of signal transduction mechanisms.

Key Features:

• Manually-Annotated Causal Relationships: The database contains over 23,000 manually curated binary causal interactions annotated with effect (up-regulation or down-regulation) and mechanism (e.g., binding, phosphorylation, transcriptional activation).
• Entity Scope: Interactions involve proteins and other biological entities including chemicals, phenotypes, and complexes.
• Graphical Representation: Signaling information is represented as signed directed graphs to encode causal directionality and sign of interactions.
• Confidence Scoring: Each interaction is annotated with a confidence score indicating its assessed reliability.
• Pathway Collection: SIGNOR includes a curated collection of 37 signaling pathways.
• FAIR and Programmatic Access: The resource provides stable identifiers, REST APIs, bioschemas metadata, and downloadable datasets in PSI-MI CausalTAB and GMT formats.

Scientific Applications:

• Pathway Analysis: Use curated causal interactions to identify and analyze signaling pathways and pathway crosstalk.
• Network Biology: Construct signed directed networks for topological and causal network analyses.
• Systems Biology Modeling: Incorporate causal interactions and confidence scores into mechanistic or computational models of signal transduction.
• Mechanistic Interpretation of Disease: Map molecular mechanisms underlying cellular processes and disease states using curated causal relationships.

Methodology:

Manual curation of causal interactions with annotation of effect and mechanism, representation as signed directed graphs, assignment of interaction-specific confidence scores, and provision of stable identifiers, REST APIs, bioschemas, and data exports in PSI-MI CausalTAB and GMT formats.