DISEASES
Description: DISEASES is a weekly updated web resource that integrates evidence on disease-gene associations from automatic text mining, manually curated literature, cancer mutation data, and genome-wide association studies. We further unify the evidence by assigning confidence scores that facilitate comparison of the different types and sources of evidence.
Cross-references: https://github.com/NCATSTranslator/Translator-All/wiki/Diseases
Edge Categories Distribution
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Epistemic Robustness
Epistemic Robustness measures the provenance quality of edges from this knowledge source, using Knowledge Level and Agent Type from the Biolink Model to assess evidence strength and reliability. Higher scores indicate stronger evidence and greater manual curation.
-0.45
Average Epistemic Score
Average Epistemic Score
-0.59
Knowledge Level Score
Most common: Prediction
Knowledge Level Score
Most common: Prediction
-0.30
Agent Type Score
Most common: Text-Mining Agent
Agent Type Score
Most common: Text-Mining Agent
1,475,046
Edges Included
Edges Included
0
Edges with Missing Provenance
(Both Knowledge Level and Agent Type not provided)
Edges with Missing Provenance
(Both Knowledge Level and Agent Type not provided)
Edge Type Validation
This section shows the validation of edge types in this knowledge source against the recognized biolink schema patterns.
46,212
Recognized Edges
( 3.1 %)
Recognized Edges
( 3.1 %)
1,428,717
Unrecognized Edges
( 96.9 %)
Unrecognized Edges
( 96.9 %)
ABox / TBox Classification
The TBox-to-ABox balance reflects how much a knowledge graph emphasizes abstract schema versus concrete instances—too much of either can hinder effective learning and reasoning.
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1,474,929
ABox Edges
( 100.0 %)
ABox Edges
( 100.0 %)
0
TBox Edges
( 0.0 %)
TBox Edges
( 0.0 %)
0
Undefined
( 0.0 %)
Undefined
( 0.0 %)