CHEBI Integrated Role Ontology (CHIRO)

The CHEBI Integrated Role Ontology (CHIRO) is a specialized ontology designed to provide a structured role hierarchy for chemicals. It connects chemicals in the structural hierarchy via a ‘has role’ relation, linking them to relevant classes in other ontologies. This enables the formalization of relationships between chemical structures (e.g., small molecules, drugs) and their functional roles, such as their biological or chemical activities. CHIRO facilitates the integration of chemical data with biological and biomedical ontologies, supporting applications in drug discovery, chemical informatics, and systems biology. By providing a standardized framework for describing chemical roles, CHIRO enhances data interoperability and enables advanced semantic queries across chemical and biological datasets. The ontology is particularly useful for linking chemical entities to their roles in biological processes, such as enzyme inhibitors, signaling molecules, or structural components.

Example Usage: Annotate a dataset of small molecules with CHIRO terms to specify their roles, such as “enzyme inhibitor” or “neurotransmitter,” and link these roles to relevant biological processes or pathways.

Metrics & Statistics

Graph Statistics

Total Nodes

81778

Total Edges

197071

Root Nodes

14636

Leaf Nodes

50439

Knowledge Coverage Statistics

Classes

13930

Individuals

0

Properties

15

Hierarchical Metrics

Maximum Depth

16

Minimum Depth

0

Average Depth

1.36

Depth Variance

1.13

Breadth Metrics

Maximum Breadth

34719

Minimum Breadth

2

Average Breadth

4620.24

Breadth Variance

105924794.30

LLMs4OL Dataset Statistics

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