Ontology-based data integration for synthetic biology and metabolic engineering. Hoehndorf led the data-integration work package.
- Start
- 2016
- End
- 2018
- Tags
- ontologies, knowledge graphs, microbial communities, drug discovery, ontology embeddings
Connections
funded by borg:fundedBy
team borg:hasMember
publications borg:producedPub
- Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies
- Ontology-based prediction of cancer driver genes
- Combining lexical and context features for automatic ontology extension
- DDIEM: drug database for inborn errors of metabolism
- DeepGOPlus: improved protein function prediction from sequence
- Phenotype-driven discovery of digenic variants in personal genome sequences
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data
- Ontology based mining of pathogen--disease associations from literature
- PathoPhenoDB: linking human pathogens to their disease phenotypes in support of infectious disease research
- Using SPARQL to Unify Queries over Data, Ontologies, and Machine Learning Models in the PhenomeBrowser Knowledgebase
- Integrating phenotype ontologies with PhenomeNET
- Ontology based text mining of gene-phenotype associations: application to candidate gene prediction
- Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings
Referenced by
on project borg:onProject
from project borg:fromProject
- AberOWL
- Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies
- Ontology-based prediction of cancer driver genes
- Combining lexical and context features for automatic ontology extension
- DDIEM: drug database for inborn errors of metabolism
- DeepGOPlus: improved protein function prediction from sequence
- Phenotype-driven discovery of digenic variants in personal genome sequences
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data
- Ontology based mining of pathogen--disease associations from literature
- PathoPhenoDB: linking human pathogens to their disease phenotypes in support of infectious disease research
- Using SPARQL to Unify Queries over Data, Ontologies, and Machine Learning Models in the PhenomeBrowser Knowledgebase
- Integrating phenotype ontologies with PhenomeNET
- Ontology based text mining of gene-phenotype associations: application to candidate gene prediction
- Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings
related projects borg:linkedProject
Open in the interactive graph →
JSON-LD (this resource)
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Machine-readable copy: data.jsonld. Full dataset: kg.jsonld.