Life Ontology (LifO)¶
The Life Ontology (LifO) is a general-purpose ontology designed to represent the life processes of organisms and their associated entities and relationships. It provides a structured framework for describing common biological features across diverse organisms, including unicellular prokaryotes such as E. coli and multicellular organisms such as humans [1] [2]. LifO represents life processes of organisms together with related entities and relations, providing a common vocabulary for modelling biological phenomena in a standardized way [1] [2]. The ontology is intended as a broad life-science resource that can support interoperable description of organism-level biological knowledge across different systems and datasets [1] [2]. By providing a shared framework for representing biological processes and related entities, LifO can support comparative studies, knowledge organization, and bioinformatics applications that benefit from a common semantic structure [1].
Example Usage: Use LifO to annotate a dataset describing organismal life processes or related biological entities. For example, linking metabolic or reproductive processes in E. coli or human-related datasets to standardized ontology terms to support consistent description, comparison, and integration across biological datasets [1] [2].
Metrics & Statistics¶
Total Nodes |
2140 |
Total Edges |
4179 |
Root Nodes |
43 |
Leaf Nodes |
1522 |
Classes |
239 |
Individuals |
9 |
Properties |
98 |
Maximum Depth |
2 |
Minimum Depth |
0 |
Average Depth |
1.18 |
Depth Variance |
0.83 |
Maximum Breadth |
65 |
Minimum Breadth |
17 |
Average Breadth |
41.67 |
Breadth Variance |
384.89 |
Term Types |
9 |
Taxonomic Relations |
321 |
Non-taxonomic Relations |
0 |
Average Terms per Type |
9.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import LIFO
ontology = LIFO()
ontology.load("path/to/LIFO-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