Molecular Process Ontology (MOP)¶
The Molecular Process Ontology (MOP) is a systematic ontology for describing and classifying molecular-level chemical processes and transformations [1] [2]. It provides a structured vocabulary for representing processes such as cyclization, methylation, demethylation, oxidation, reduction, and other fundamental transformations relevant to chemical reaction description [1] [2].
MOP supports standardized semantic representation of molecular processes that underlie reaction mechanisms and can be used to organize and classify reaction information in chemistry databases and reaction informatics systems [1] [2]. By providing explicit terms for molecular transformations, MOP supports semantic interoperability, structured querying, and mechanism-oriented analysis across chemical data resources [1] [2].
Example Usage: Represent a cyclization reaction step by linking it to an appropriate MOP term for the corresponding molecular process, such as a ring-closure transformation, enabling structured classification of reactions and discovery of related transformations across chemical databases [1] [2].
Metrics & Statistics¶
Total Nodes |
15794 |
Total Edges |
41157 |
Root Nodes |
3693 |
Leaf Nodes |
8182 |
Classes |
3717 |
Individuals |
0 |
Properties |
11 |
Maximum Depth |
6 |
Minimum Depth |
0 |
Average Depth |
1.09 |
Depth Variance |
0.63 |
Maximum Breadth |
7300 |
Minimum Breadth |
3 |
Average Breadth |
2253.14 |
Breadth Variance |
7474153.55 |
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:
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