.. sidebar::

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

       * - **Domain**
         - Chemistry
       * - **Category**
         - Chemistry, Molecular Biology
       * - **Current Version**
         - 2022-05-11
       * - **Last Updated**
         - 2022-05-11
       * - **Creator**
         - None
       * - **License**
         - Creative Commons 4.0
       * - **Format**
         - owl
       * - **Download**
         - `Download Molecular Process Ontology (MOP) <https://terminology.tib.eu/ts/ontologies/MOP>`_

Molecular Process Ontology (MOP)
========================================================================================================

The Molecular Process Ontology (MOP) is a systematic vocabulary for describing and classifying molecular-level chemical processes and transformations that occur in organic chemistry. It provides formal definitions of common molecular processes such as cyclization, methylation, demethylation, oxidation, reduction, and other fundamental reaction steps underlying named reactions in chemistry. MOP serves as the foundational semantic layer for the Reaction Ontology (RXNO), enabling precise description of chemical reaction mechanisms and their constituent molecular processes. The ontology facilitates integration of chemical databases, computational chemistry platforms, and reaction informatics systems by providing standardized semantic representations of molecular transformations. MOP enables advanced searching and classification of reactions based on their underlying molecular mechanisms.

**Example Usage**: Represent a cyclization reaction step in RXNO by linking to MOP terms for the specific cyclization type (e.g., "6-membered ring closure"), enabling automated discovery of similar reactions across chemical databases.

Metrics & Statistics
--------------------------

.. tab:: Graph


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

        * - **Total Nodes**
          - 15794
        * - **Total Edges**
          - 41157
        * - **Root Nodes**
          - 3693
        * - **Leaf Nodes**
          - 8182
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 3717
        * - **Individuals**
          - 0
        * - **Properties**
          - 11

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 6
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 1.09
        * - **Depth Variance**
          - 0.63
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 7300
        * - **Minimum Breadth**
          - 3
        * - **Average Breadth**
          - 2253.14
        * - **Breadth Variance**
          - 7474153.55
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 0
        * - **Taxonomic Relations**
          - 3840
        * - **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 MOP

    ontology = MOP()
    ontology.load("path/to/MOP-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