DISGENET

DISGENET integrates and standardizes information on disease-associated genes and variants to support applications in genomic medicine and drug research and development.

Key Features:

• Disease Coverage: The database covers the full spectrum of human diseases as well as normal and abnormal traits, including adverse events of drugs, with more than 24,000 diseases and traits, 17,000 genes and 117,000 genomic variants in the current release.
• Data Integration: DISGENET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature.
• Data Standardization: Data are homogeneously annotated with controlled vocabularies and community-driven ontologies.
• Prioritization Metrics: Several original metrics are provided to assist the prioritization of genotype-phenotype relationships, including a score based on supporting evidence for gene-disease associations.
• Semantic Web Integration: DISGENET-RDF publishes gene-disease associations and their provenance metadata as human-readable and machine-processable web resources interlinked to other biomedical databases.

Scientific Applications:

• Disease Mechanism Investigation: Investigation of the molecular underpinnings of specific human diseases and their comorbidities.
• Disease Gene Analysis: Analysis of the properties of disease genes.
• Drug Hypothesis Generation: Generation of hypotheses on drug therapeutic action and drug adverse effects.
• Gene Prediction Validation: Validation of computationally predicted disease genes.
• Text-Mining Evaluation: Evaluation of text-mining methods performance.

Methodology:

DISGENET combines expert curated information with data automatically mined from the scientific literature, and applies data standardization using controlled vocabularies and community-driven ontologies.