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September 3, 2019

Tiffany J. Callahan edited this page Dec 10, 2023 · 15 revisions

PKT Human Disease Knowledge Graph Benchmark Builds (v1.0.0)

Build Date: September 03, 2019


Resources

The KG Benchmark Builds can be downloaded from Zenodo:
πŸ‘‰ KGs: https://zenodo.org/doi/10.5281/zenodo.7030200
πŸ‘‰ Embeddings: https://zenodo.org/doi/10.5281/zenodo.7030188


Required Input Documents

  • resource_info.txt
  • class_source_list.txt
  • instance_source_list.txt
  • ontology_source_list.txt

Data


Data Download Date:Β November 30, 2018 -Β Data Source Details

Ontologies

Classes

Instances




Knowledge Graphs


Knowledge Representation
We worked with a PhD-level biologist to develop a knowledge representation (see the figure below) that modeled mechanisms underlying human disease.

image

To do this, we manually mapped all possible combinations of the following six node types:

  • Humans Diseases
  • Human Phenotypes
  • Human Genes
  • Gene Ontology concepts
  • Reactome Pathways
  • Chemicals

As shown inΒ the figure above, theΒ Basic Formal OntologyΒ andΒ Relation OntologyΒ ontologies were then used to create edges between the node types.


As shown in this figure, the following edge-types were created:


Knowledge Graph
The knowledge graph represented above was built using the following steps: Merge Ontologies:Β Merge ontologies using theΒ OWL Tools API
Express New Ontology Concept Annotations:Β Create new ontology annotations by asserting a relation between the instance and an instance of the ontology class. For example to assert the following relations:

MorphineΒ -->Β is substance that treatsΒ --> Migraine

We would need to create two axioms:

  • isSubstanceThatTreats(Morphine, x1)
  • instanceOf(x1, Migraine)

While the instance of the HP class hemiplegic migraines can be treated as an anonymous node in the knowledge graph, we generate a new international resource identifier for each newly generated instance.

Deductively Close Knowledge Graph:Β The knowledge graph is deductively closed by using the OWL 2 EL reasoner, ELK via ProtΓ©gΓ© v5.1.1. ELK is able to classify instances and supports inferences over class hierarchies and object properties. inference over disjointness, intersection, and existential quantification (ontology class hierarchies).

Generate Edge List:Β The final step before exporting the edge list is to remove any nodes that are not biologically meaningful or would otherwise reduce the performance of machine learning algorithms and the algorithm used to generate embeddings.


🚨 Scroll to the right πŸ‘‰ to see all of the available data 🚨

All Builds
PheKnowLator_v1_ClassInstancesOnly_KG.owl
PheKnowLator_v1_ClassInstancesOnly_KG_ClassInstanceMap.json
PheKnowLator_v1_Full_KG.owl
PheKnowLator_v1_Full_KG_NoDisjointness.owl
PheKnowLator_v1_MergedOntologies_BioKG.owl
Closed KGs Not Closed KGs
PheKnowLator_v1_Full_BioKG_Closed_Triples_Integer_Labels_Map.json
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_ELK.owl
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_ELK_Reasoner_RESULTS.txt
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_ELK_Triples_Integers.bcsr
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_ELK_Triples_Integers.txt
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_ELK_Triples_Labels.txt
PheKnowLator_v1_Full_BioKG_NoDisjointness_Closed_NoMetadataNodes.owl
PheKnowLator_v1_Full_BioKG_NoDisjointness_NotClosed_NoMetadataNodes.owl
PheKnowLator_v1_Full_BioKG_NoDisjointness_NotClosed_Triples_Integers.txt
PheKnowLator_v1_Full_BioKG_NoDisjointness_NotClosed_Triples_Integers_.bcsr
PheKnowLator_v1_Full_BioKG_NoDisjointness_NotClosed_Triples_Labels.txt
PheKnowLator_v1_Full_BioKG_NotClosed_Triples_Integer_Labels_Map.json
Embeddings
closed_knowledge_graphs.zip
not_closed_knowledge_graphs.zip


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