We use ontologies to standardize and analyze complex phenotypes across domains. Earlier work focused on foundational ontologies, including the General Formal Ontology (GFO) and its biological extension GFO-Bio, as well as the development of a formal ontology of functions to curate functional knowledge in the life sciences.
- Section
- Foundations
- Keywords
- formal ontology, GFO, GFO-Bio, ontology of functions, phenotype ontology, FLOPO, ontology design patterns
Connections
related papers borg:linkedPaper
- Semantic similarity and machine learning with ontologies
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data
- Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies
- Improving the classification of cardinality phenotypes using collections
- Ontology-based prediction of cancer driver genes
- GFVO: the Genomic Feature and Variation Ontology
- Best behaviour? Ontologies and the formal description of animal behaviour
- FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation
- DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species
- DermO; an ontology for the description of dermatologic disease
- FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration
- A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
- Notions of similarity for systems biology models
- A Review of Current Standards and the Evolution of Histopathology Nomenclature for Laboratory Animals
- The role of ontologies in biological and biomedical research: a functional perspective
- The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants
- Evaluating the effect of annotation size on measures of semantic similarity
- DELE: Deductive EL++ Embeddings for Knowledge Base Completion
- An ontology approach to comparative phenomics in plants
- Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations
- Ontology based mining of pathogen--disease associations from literature
- The anatomy of phenotype ontologies: principles, properties and applications
- Ontology-based validation and identification of regulatory phenotypes
- Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies
- Semantic units: organizing knowledge graphs into semantically meaningful units of representation
- The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery
- Statistical tests for associations between two directed acyclic graphs.
- Applying the functional abnormality ontology pattern to anatomical functions.
- The ontology of biological sequences.
- BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology.
- Relations as patterns: bridging the gap between OBO and OWL.
- GFO-Bio: A biomedical core ontology
- Representing default knowledge in biomedical ontologies: Application to the integration of anatomy and phenotype ontologies
- A top-level ontology of functions and its application in the Open Biomedical Ontologies.
- Interoperability between phenotype and anatomy ontologies
- A common layer of interoperability for biomedical ontologies based on OWL EL
- The RNA Ontology (RNAO): An Ontology for Integrating RNA Sequence and Structure Data
- Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning
- Integrating systems biology models and biomedical ontologies
- PIDO: The Primary Immunodeficiency Disease Ontology
- Ontology design patterns to disambiguate relations between genes and gene products in GENIA
- New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models
- OBML - Ontologies in Biomedicine and Life Sciences
- Linking PharmGKB to phenotype studies and animal models of disease for drug repurposing
- Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL
- Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology
- Quantitative comparison of mapping methods between Human and Mammalian Phenotype Ontology
- Towards improving phenotype representation in OWL
- Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes
- Evaluation of research in biomedical ontologies
- The Units Ontology: a tool for integrating units of measurement in science
- Chapter Four - The Neurobehavior Ontology: An Ontology for Annotation and Integration of Behavior and Behavioral Phenotypes
- Representing physiological processes and their participants with PhysioMaps
- Evaluation and Cross-Comparison of Lexical Entities of Biological Interest (LexEBI)
- Semantic Systems Biology: Formal Knowledge Representation in Systems Biology for Model Construction, Retrieval, Validation and Discovery
- BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains.
- Thematic series on biomedical ontologies in JBMS: challenges and new directions
- Analyzing gene expression data in mice with the Neuro Behavior Ontology
- Enriched biodiversity data as a resource and service
- Exploring the Use of Ontology Components for Distantly-Supervised Disease and Phenotype Named Entity Recognition
- Updating the CEMO ontology for future epidemiological challenges
- Large-Scale Reasoning over Functions in Biomedical Ontologies
- To MIREOT or not to MIREOT? A case study of the impact of using MIREOT in the Experimental Factor Ontology (EFO)
- Ontology based mining of pathogen-disease associations from literature
- Evaluating the effect of annotation size on measures of semantic similarity
- Using SPARQL to Unify Queries over Data, Ontologies, and Machine Learning Models in the PhenomeBrowser Knowledgebase
- Fully Geometric Multi-hop Reasoning on Knowledge Graphs with Transitive Relations
- Applying ontology design patterns to the implementation of relations in GENIA
- The Ontology of Primary Immunodeficiency Diseases (PIDs): Using PIDs to Rethink the Ontology of Phenotypes
- Relational patterns in OWL and their application to OBO
- OWLDEF: Integrating OBO and OWL
- The application of an ontology design pattern for functional abnormalities to phenotype ontologies and the extraction of an ontology of anatomical functions
- Developing Consistent and Modular Software Models with Ontologies
- Contributions to the formal ontology of functions and dispositions: an application of non-monotonic reasoning
- A Formal Ontology of Sequences
- Towards Ontological Interpretations for Improved Text Mining
- From Terms to Categories: Testing the Significance of Co-occurrences between Ontological Categories
- BOWiki: An ontology-based wiki for annotation of data and integration of knowledge in biology
- The design of a wiki-based curation system for the Ontology of Functions
- A proposal for a gene functions wiki
- BOWiki - a collaborative annotation and ontology curation framework
- Higgs bosons, mars missions, and unicorn delusions: How to deal with terms of dubious reference in scientific ontologies
- Investigation of the fundamental strategy for interoperability of description of biological measurements
- Exploring Gene Ontology Annotations with OWL
- Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes
- Towards Improving Phenotype Representation in OWL
- Realism for scientific ontologies
- Argumentation to Represent and Reason over Biological Systems
- JOWO 2020: The Joint Ontology Workshops : Proceedings of the Joint Ontology Workshops co-located with the Bolzano Summer of Knowledge (BOSK 2020)
- Datamining with Ontologies
- Ontologies in Biology
related projects borg:linkedProject
- Towards sound, complete, and explainable machine learning with biomedical ontologies (CRG11)
- Computational methods for functional metagenomics: from protein functions to multi-scale interactions
- IBNSINA-QI: Integrating Biomedical Networks and Semantic Information for Neural network Analysis of Quantitative Information
- CompleX: Variant Prioritization in Complex Disease
- Improvement of genetic variant prioritization technology
- Bio2Vec: Smart analytics infrastructure for the life sciences
- Data integration and ontologies for microbial cell factories
related people borg:linkedPerson
- Robert Hoehndorf
- Mona Alshahrani
- Sarah Alghamdi
- Sumyyah Toonsi
- Sara Althubaiti
- Maxat Kulmanov
- Imane Boudellioua
- Azza Althagafi
- Miguel Angel Rodriguez Garcia
- Zhenwei Tang
- Yang Liu
- Xi Peng
- Rund Tawfiq
- Kexin Niu
- Tengwei Song
- Paul N Schofield
- Takashi Gojobori
- Georgios V Gkoutos
- Vladimir Bajic
- Xin Gao
- Michel Dumontier
- Jens Lehmann
- Fernando Zhapa-Camacho
- Abeer Almutairi
- Daulet Toibazar
- Amal Alhelal
- Md Nurul Muttakin
- Hatoon Al Ali
- Shahad Qatan
- Safana Bakheet
- Mahdi Bu Ali
- Asaad Mohammedsaleh
- Ashraf Kibraya
related courses borg:linkedCourse
- Knowledge Representation and Reasoning
- Neurosymbolic AI
- Knowledge Representation and Reasoning
- Neurosymbolic AI
- Knowledge Representation and Reasoning
- Knowledge Representation and Reasoning
- Knowledge Representation and Reasoning
- Applied Ontology
- Knowledge Representation and Reasoning
- Applied Ontology
- Knowledge Representation and Reasoning
- Ontology in medical information systems
Referenced by
research topics borg:topic
- Towards sound, complete, and explainable machine learning with biomedical ontologies (CRG11)
- Computational methods for functional metagenomics: from protein functions to multi-scale interactions
- IBNSINA-QI: Integrating Biomedical Networks and Semantic Information for Neural network Analysis of Quantitative Information
- CompleX: Variant Prioritization in Complex Disease
- Improvement of genetic variant prioritization technology
- Bio2Vec: Smart analytics infrastructure for the life sciences
- Data integration and ontologies for microbial cell factories
- Robert Hoehndorf
- Imane Boudellioua
- Mona Alshahrani
- Maxat Kulmanov
- Sarah Alghamdi
- Azza Althagafi
- Sumyyah Toonsi
- Rund Tawfiq
- Yang Liu
- Fernando Zhapa-Camacho
- Abeer Almutairi
- Sara Althubaiti
- Daulet Toibazar
- Amal Alhelal
- Md Nurul Muttakin
- Hatoon Al Ali
- Shahad Qatan
- Kexin Niu
- Xi Peng
- Zhenwei Tang
- Safana Bakheet
- Mahdi Bu Ali
- Asaad Mohammedsaleh
- Miguel Angel Rodriguez Garcia
- Ashraf Kibraya
- Tengwei Song
- Takashi Gojobori
- Paul N Schofield
- Georgios V Gkoutos
- Vladimir Bajic
- Xin Gao
- Michel Dumontier
- Jens Lehmann
- The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants
- Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies
- Exploring the Use of Ontology Components for Distantly-Supervised Disease and Phenotype Named Entity Recognition
- Ontology-based prediction of cancer driver genes
- Improving the classification of cardinality phenotypes using collections
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data
- Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies
- Ontology based mining of pathogen--disease associations from literature
- Using SPARQL to Unify Queries over Data, Ontologies, and Machine Learning Models in the PhenomeBrowser Knowledgebase
- Semantic similarity and machine learning with ontologies
- GFVO: the Genomic Feature and Variation Ontology
- Best behaviour? Ontologies and the formal description of animal behaviour
- FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation
- DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species
- DermO; an ontology for the description of dermatologic disease
- FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration
- A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
- Notions of similarity for systems biology models
- A Review of Current Standards and the Evolution of Histopathology Nomenclature for Laboratory Animals
- The role of ontologies in biological and biomedical research: a functional perspective
- Evaluating the effect of annotation size on measures of semantic similarity
- DELE: Deductive EL++ Embeddings for Knowledge Base Completion
- An ontology approach to comparative phenomics in plants
- Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations
- The anatomy of phenotype ontologies: principles, properties and applications
- Ontology-based validation and identification of regulatory phenotypes
- Semantic units: organizing knowledge graphs into semantically meaningful units of representation
- The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery
- Statistical tests for associations between two directed acyclic graphs.
- Applying the functional abnormality ontology pattern to anatomical functions.
- The ontology of biological sequences.
- BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology.
- Relations as patterns: bridging the gap between OBO and OWL.
- GFO-Bio: A biomedical core ontology
- Representing default knowledge in biomedical ontologies: Application to the integration of anatomy and phenotype ontologies
- A top-level ontology of functions and its application in the Open Biomedical Ontologies.
- Interoperability between phenotype and anatomy ontologies
- A common layer of interoperability for biomedical ontologies based on OWL EL
- The RNA Ontology (RNAO): An Ontology for Integrating RNA Sequence and Structure Data
- Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning
- Integrating systems biology models and biomedical ontologies
- PIDO: The Primary Immunodeficiency Disease Ontology
- Ontology design patterns to disambiguate relations between genes and gene products in GENIA
- New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models
- OBML - Ontologies in Biomedicine and Life Sciences
- Linking PharmGKB to phenotype studies and animal models of disease for drug repurposing
- Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL
- Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology
- Quantitative comparison of mapping methods between Human and Mammalian Phenotype Ontology
- Towards improving phenotype representation in OWL
- Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes
- Evaluation of research in biomedical ontologies
- The Units Ontology: a tool for integrating units of measurement in science
- Chapter Four - The Neurobehavior Ontology: An Ontology for Annotation and Integration of Behavior and Behavioral Phenotypes
- Representing physiological processes and their participants with PhysioMaps
- Evaluation and Cross-Comparison of Lexical Entities of Biological Interest (LexEBI)
- Semantic Systems Biology: Formal Knowledge Representation in Systems Biology for Model Construction, Retrieval, Validation and Discovery
- BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains.
- Thematic series on biomedical ontologies in JBMS: challenges and new directions
- Analyzing gene expression data in mice with the Neuro Behavior Ontology
- Enriched biodiversity data as a resource and service
- Updating the CEMO ontology for future epidemiological challenges
- Large-Scale Reasoning over Functions in Biomedical Ontologies
- To MIREOT or not to MIREOT? A case study of the impact of using MIREOT in the Experimental Factor Ontology (EFO)
- Ontology based mining of pathogen-disease associations from literature
- Evaluating the effect of annotation size on measures of semantic similarity
- Fully Geometric Multi-hop Reasoning on Knowledge Graphs with Transitive Relations
- Applying ontology design patterns to the implementation of relations in GENIA
- The Ontology of Primary Immunodeficiency Diseases (PIDs): Using PIDs to Rethink the Ontology of Phenotypes
- Relational patterns in OWL and their application to OBO
- OWLDEF: Integrating OBO and OWL
- The application of an ontology design pattern for functional abnormalities to phenotype ontologies and the extraction of an ontology of anatomical functions
- Developing Consistent and Modular Software Models with Ontologies
- Contributions to the formal ontology of functions and dispositions: an application of non-monotonic reasoning
- A Formal Ontology of Sequences
- Towards Ontological Interpretations for Improved Text Mining
- From Terms to Categories: Testing the Significance of Co-occurrences between Ontological Categories
- BOWiki: An ontology-based wiki for annotation of data and integration of knowledge in biology
- The design of a wiki-based curation system for the Ontology of Functions
- A proposal for a gene functions wiki
- BOWiki - a collaborative annotation and ontology curation framework
- Higgs bosons, mars missions, and unicorn delusions: How to deal with terms of dubious reference in scientific ontologies
- Investigation of the fundamental strategy for interoperability of description of biological measurements
- Exploring Gene Ontology Annotations with OWL
- Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes
- Towards Improving Phenotype Representation in OWL
- Realism for scientific ontologies
- Argumentation to Represent and Reason over Biological Systems
- JOWO 2020: The Joint Ontology Workshops : Proceedings of the Joint Ontology Workshops co-located with the Bolzano Summer of Knowledge (BOSK 2020)
- Datamining with Ontologies
- Ontologies in Biology
- Knowledge Representation and Reasoning
- Neurosymbolic AI
- Knowledge Representation and Reasoning
- Neurosymbolic AI
- Knowledge Representation and Reasoning
- Knowledge Representation and Reasoning
- Knowledge Representation and Reasoning
- Applied Ontology
- Knowledge Representation and Reasoning
- Applied Ontology
- Knowledge Representation and Reasoning
- Ontology in medical information systems
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/topic/applied-ontology",
"@type": "borg:Topic",
"owl:sameAs": {
"@id": "https://borg.kaust.edu.sa/kg/topic/applied-ontology"
},
"schema:name": "Applied Ontology",
"borg:shortName": "Applied Ontology",
"borg:section": "Foundations",
"schema:abstract": "We use ontologies to standardize and analyze complex phenotypes across domains. Earlier work focused on foundational ontologies, including the General Formal Ontology (GFO) and its biological extension GFO-Bio, as well as the development of a formal ontology of functions to curate functional knowledge in the life sciences.",
"borg:keyword": [
"formal ontology",
"GFO",
"GFO-Bio",
"ontology of functions",
"phenotype ontology",
"FLOPO",
"ontology design patterns"
],
"borg:linkedPaper": [
{
"@id": "https://leechuck.de/kg-browser/id/pub/10.1093/bib/bbaa199"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/10754/631015"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/aging-ontologies"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Alghamdi2023"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Althubaiti561480"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Baran2015"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/bestbehavior"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Bolleman2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/destomato"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Fisher2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/foodon"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/He2022"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Henkel2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/histopathology"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2015role"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Kulmanov2017"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Mashkova2026"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Oellrich2015"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/onto2vec"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/padimi2019"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/pato-paper"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/rule-phenotype"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Slater2020"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Vogt2024"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/sio"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h3"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h7"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h10"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h15"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h20"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h23"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h25"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h26"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h29"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/elvira"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/rnao"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2011incon"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2011models"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Adams2011"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2011genia"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Schofield2011"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2010obml"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2012psb"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Jupp2012"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2012cpo"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Oellrich2012"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Loebe2012"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Gkoutos2012yeast"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2012eval"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Gkoutos2012units"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Gkoutos2012behavior"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Cook2013"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/lexebi"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/dumontier2013semantic"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Katayama2014"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2014thematicseries"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2013nbo"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Biosphere"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/DBLP:conf/icbo/ToonsiKH23"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/DBLP:conf/swat4ls/Queralt-Rosinach23"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2016fois"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/IT702"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Kafkas2018-ismb"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Kulmanov2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Syed2022UsingST"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/ZhapaCamacho2026"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h1"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h2"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h4"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h5"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h11"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h12"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h13"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h14"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h16"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h17"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h18"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h19"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h21"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h27"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/unicorn1"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/icbo2"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/goannos"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/obml2011h1"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/obml2011h3"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h8"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Wyner2012"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/1479305"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/Hoehndorf2016abc"
},
{
"@id": "https://leechuck.de/kg-browser/id/pub/h9"
}
],
"borg:linkedProject": [
{
"@id": "https://leechuck.de/kg-browser/id/project/crg-explainable-ml-ontologies"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/crg-functional-metagenomics"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/crg-ibnsina-qi"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/crg-complex-variant-prioritization"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/cpf-variant-prioritization-improvement"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/crg-bio2vec"
},
{
"@id": "https://leechuck.de/kg-browser/id/project/ccf-microbial-cell-factories"
}
],
"borg:linkedPerson": [
{
"@id": "https://leechuck.de/kg-browser/id/person/robert-hoehndorf"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/mona-alshahrani"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/sarah-alghamdi"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/sumyyah-toonsi"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/sara-althubaiti"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/maxat-kulmanov"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/imane-boudellioua"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/azza-althagafi"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/miguel-angel-rodriguez-garcia"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/zhenwei-tang"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/yang-liu"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/xi-peng"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/rund-tawfiq"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/kexin-niu"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/tengwei-song"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/paul-n-schofield"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/takashi-gojobori"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/georgios-v-gkoutos"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/vladimir-bajic"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/xin-gao"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/michel-dumontier"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/jens-lehmann"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/fernando-zhapa-camacho"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/abeer-almutairi"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/daulet-toibazar"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/amal-alhelal"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/md-nurul-muttakin"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/hatoon-al-ali"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/shahad-qatan"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/safana-bakheet"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/mahdi-bu-ali"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/asaad-mohammedsaleh"
},
{
"@id": "https://leechuck.de/kg-browser/id/person/ashraf-kibraya"
}
],
"borg:linkedCourse": [
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2026"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/neurosymbolic-2026"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2024"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/neurosymbolic-2024"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2022"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2021"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2020"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/applied-ontology-2018"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2017-2018"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/applied-ontology-2016-2017"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/krr-2015-2016"
},
{
"@id": "https://leechuck.de/kg-browser/id/course/ontology-medical-info-2005-2008"
}
]
}
Machine-readable copy: data.jsonld. Full dataset: kg.jsonld.