CHEBI Integrated Role Ontology (CHIRO)¶
The CHEBI Integrated Role Ontology (CHIRO) is a specialized ontology designed to provide a structured role hierarchy for chemicals [1] [2]. It extends the role branch associated with ChEBI by connecting chemicals in the structural hierarchy through a has role relation and by linking chemical roles to relevant classes in other ontologies [1] [2]. This enables formal representation of relationships between chemical structures, such as small molecules and drugs, and the biological or chemical roles they play [1] [2]. By providing a standardized framework for describing chemical roles, CHIRO supports semantic interoperability, ontology-based integration, and advanced querying across chemical and biomedical datasets [1] [2].
Example Usage: Annotate a dataset of small molecules with CHIRO terms to specify roles such as enzyme inhibitor or neurotransmitter, and link those roles to related biological processes or target classes, enabling semantic search, cross-dataset integration, and role-based analysis of chemical entities [1] [2].
Metrics & Statistics¶
Total Nodes |
81778 |
Total Edges |
197071 |
Root Nodes |
14636 |
Leaf Nodes |
50439 |
Classes |
13930 |
Individuals |
0 |
Properties |
15 |
Maximum Depth |
16 |
Minimum Depth |
0 |
Average Depth |
1.36 |
Depth Variance |
1.13 |
Maximum Breadth |
34719 |
Minimum Breadth |
2 |
Average Breadth |
4620.24 |
Breadth Variance |
105924794.30 |
Term Types |
0 |
Taxonomic Relations |
25262 |
Non-taxonomic Relations |
0 |
Average Terms per Type |
0.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import CHIRO
ontology = CHIRO()
ontology.load("path/to/CHIRO-ontology.owl")
# Extract datasets
data = ontology.extract()
# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations