About This Database

Gene Staging System

Two-stage data ingestion ensures quality: genes first enter a staging area for normalization and validation, then move to curated status after passing quality checks.

Multi-Source Integration

Aggregates evidence from multiple authoritative sources with automatic retry logic and cache validation. Each source contributes unique annotations: nomenclature, constraint scores, variants, phenotypes, expression, interactions, and literature.

Evidence Scoring

Weighted scoring algorithm aggregates evidence from multiple sources to produce a confidence score (0-100). Scores are dynamic and update automatically as new evidence becomes available from our data sources.

High-Performance Architecture

Non-blocking architecture with L1/L2 caching (memory + database) delivers fast response times for cached requests. ThreadPoolExecutor ensures event loop never blocks during heavy operations.

Quality Assurance

Comprehensive quality checks at every stage: retry logic prevents transient failures, cache validation ensures data integrity, and audit trails track all normalization attempts in the gene staging table.

Real-Time Progress Tracking

WebSocket connections provide real-time updates during pipeline operations without page refresh or polling. Watch genes flow from staging to curation with live progress bars and status updates.