Chemical Entities of Biological Interest (ChEBI)¶
Chemical Entities of Biological Interest (ChEBI) is a comprehensive ontology and dictionary of molecular entities, focusing on small chemical compounds. It provides a structured vocabulary for describing constitutionally or isotopically distinct atoms, molecules, ions, radicals, complexes, and other molecular entities. ChEBI includes both naturally occurring substances and synthetic products used in biological systems. The ontology incorporates an ontological classification system, specifying relationships between molecular entities and their parent or child classes. ChEBI is widely used in bioinformatics, cheminformatics, and systems biology to annotate chemical data, enabling interoperability between databases and facilitating advanced queries. By providing a standardized framework for describing chemical entities, ChEBI supports data integration, analysis, and sharing across diverse scientific domains.
Example Usage: Annotate a dataset of metabolites with ChEBI terms to specify their molecular structures and roles in metabolic pathways, such as “ChEBI:15377 (glucose)” or “ChEBI:15378 (ATP).”
Metrics & Statistics¶
Total Nodes |
2433610 |
Total Edges |
6913389 |
Root Nodes |
609907 |
Leaf Nodes |
1528418 |
Classes |
220816 |
Individuals |
0 |
Properties |
10 |
Maximum Depth |
6 |
Minimum Depth |
0 |
Average Depth |
1.14 |
Depth Variance |
0.69 |
Maximum Breadth |
908127 |
Minimum Breadth |
26 |
Average Breadth |
310545.00 |
Breadth Variance |
135103408992.57 |
Term Types |
0 |
Taxonomic Relations |
739967 |
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 ChEBI
ontology = ChEBI()
ontology.load("path/to/ChEBI-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