Smart analytics infrastructure on biological knowledge graphs; extends Bio2RDF, develops semantic analytics methods that became OPA2Vec / OWL2Vec.
- Start
- 2018
- End
- 2020
- Tags
- knowledge graphs, ontologies, machine learning, ontology embeddings, semantic similarity, cross-species
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
- Ontology based text mining of gene-phenotype associations: application to candidate gene prediction
- Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings
research topics borg:topic
Referenced by
on project borg:onProject
from project borg:fromProject
- OPA2Vec
- Onto2Vec
- DL2Vec
- Walking RDF and OWL
- DeepGOPlus
- DeepGO
- Onto2Graph
- OntoFunc
- vec2SPARQL
- SmuDGE
- Multi-Drug Embedding
- DeepMOCCA
- 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
- 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)
{
"@context": {
"schema": "https://schema.org/",
"foaf": "http://xmlns.com/foaf/0.1/",
"prov": "http://www.w3.org/ns/prov#",
"dct": "http://purl.org/dc/terms/",
"borg": "https://borg.kaust.edu.sa/kg/ns/",
"borg-id": "https://borg.kaust.edu.sa/kg/",
"owl": "http://www.w3.org/2002/07/owl#"
},
"@id": "https://leechuck.de/kg-browser/id/project/crg-bio2vec",
"@type": "borg:Project",
"owl:sameAs": {
"@id": "https://borg.kaust.edu.sa/kg/project/crg-bio2vec"
},
"schema:name": "Bio2Vec: Smart analytics infrastructure for the life sciences",
"borg:startYear": 2018,
"borg:endYear": 2020,
"schema:abstract": "Smart analytics infrastructure on biological knowledge graphs; extends Bio2RDF, develops semantic analytics methods that became OPA2Vec / OWL2Vec.",
"borg:fundedBy": [
{
"@id": "https://leechuck.de/kg-browser/id/grant/crg-bio2vec"
}
],
"borg:hasMember": [
{
"@id": "https://leechuck.de/kg-browser/id/person/robert-hoehndorf",
"borg:roleOnProject": "PI"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/xin-gao",
"borg:roleOnProject": "CoI"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/michel-dumontier",
"borg:roleOnProject": "CoI"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/jens-lehmann",
"borg:roleOnProject": "CoI"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/mona-alshahrani",
"borg:roleOnProject": "PhD (alumnus)"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/maxat-kulmanov",
"borg:roleOnProject": "PhD (alumnus)"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/sumyyah-toonsi",
"borg:roleOnProject": "MSc (alumnus)"
}
],
"borg:producedPub": [
{
"@id": "https://leechuck.de/kg-browser/id/pub/aging-ontologies"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Althubaiti561480"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/ontoextend"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Abdelhakim2020"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/10.1093/bioinformatics/btz595"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/varisig2017"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/10754/631015"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/padimi2019"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/pathophenodb"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/database2019"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/vec2sparql"
}
],
"borg:producedSW": [],
"borg:tag": [
"knowledge graphs",
"ontologies",
"machine learning",
"ontology embeddings",
"semantic similarity",
"cross-species"
],
"borg:tagsByGroup": {
"theme": [
"knowledge graphs",
"ontologies",
"machine learning"
],
"application": [],
"method": [
"ontology embeddings",
"semantic similarity"
],
"population": [
"cross-species"
]
},
"borg:topic": [
{
"@id": "https://leechuck.de/kg-browser/id/topic/applied-ontology"
},
{
"@id": "https://leechuck.de/kg-browser/id/topic/neuro-symbolic-ai"
},
{
"@id": "https://leechuck.de/kg-browser/id/topic/semantic-similarity"
}
]
}
Machine-readable copy: data.jsonld. Full dataset: kg.jsonld.