.. sidebar::

    .. list-table:: **Ontology Card**
       :header-rows: 0

       * - **Domain**
         - Chemistry
       * - **Category**
         - Chemical Entities
       * - **Current Version**
         - 239
       * - **Last Updated**
         - 01/01/2025
       * - **Creator**
         - None
       * - **License**
         - Creative Commons 4.0
       * - **Format**
         - owl
       * - **Download**
         - `Download Chemical Entities of Biological Interest (ChEBI) <https://www.ebi.ac.uk/chebi/>`_

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
--------------------------

.. tab:: Graph


    .. list-table:: Graph Statistics
        :widths: 50 50
        :header-rows: 0

        * - **Total Nodes**
          - 2433610
        * - **Total Edges**
          - 6913389
        * - **Root Nodes**
          - 609907
        * - **Leaf Nodes**
          - 1528418
    ::


.. tab:: Coverage


    .. list-table:: Knowledge Coverage Statistics
        :widths: 50 50
        :header-rows: 0

        * - **Classes**
          - 220816
        * - **Individuals**
          - 0
        * - **Properties**
          - 10

    ::

.. tab:: Hierarchy


    .. list-table:: Hierarchical Metrics
        :widths: 50 50
        :header-rows: 0

        * - **Maximum Depth**
          - 6
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 1.14
        * - **Depth Variance**
          - 0.69
    ::


.. tab:: Breadth


    .. list-table:: Breadth Metrics
        :widths: 50 50
        :header-rows: 0

        * - **Maximum Breadth**
          - 908127
        * - **Minimum Breadth**
          - 26
        * - **Average Breadth**
          - 310545.00
        * - **Breadth Variance**
          - 135103408992.57
    ::

.. tab:: LLMs4OL


    .. list-table:: LLMs4OL Dataset Statistics
        :widths: 50 50
        :header-rows: 0

        * - **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:

.. code-block:: python

    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