BRENDA Tissue Ontology (BTO)¶
The BRENDA Tissue Ontology (BTO) is a structured controlled vocabulary for describing and classifying enzyme sources, including tissues, cell lines, cell types, and cell cultures [1] [2]. Developed as part of the BRENDA enzyme information system, BTO provides standardized terminology for identifying biological sample origins in enzymatic, biochemical, and molecular biology studies [2].
BTO supports semantic annotation and integration of enzyme-related data by linking tissue and cell-source information to biochemical research records [1] [2]. It includes terms for tissues, anatomical structures, organs, cell cultures, cell types, and cell lines from different organisms, enabling accurate search and comparison of enzymes studied in specific biological contexts [2].
Example Usage: Annotate an enzyme assay result with a BTO term such as BTO:0000079 for liver or BTO:0000142 for kidney to indicate the tissue source of the enzyme sample, enabling semantic search and integration with biochemical databases [1] [2].
Metrics & Statistics¶
Total Nodes |
37130 |
Total Edges |
86188 |
Root Nodes |
5619 |
Leaf Nodes |
21886 |
Classes |
6569 |
Individuals |
0 |
Properties |
10 |
Maximum Depth |
7 |
Minimum Depth |
0 |
Average Depth |
1.37 |
Depth Variance |
0.68 |
Maximum Breadth |
16002 |
Minimum Breadth |
9 |
Average Breadth |
4411.62 |
Breadth Variance |
36150459.73 |
Term Types |
0 |
Taxonomic Relations |
5888 |
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 BTO
ontology = BTO()
ontology.load("path/to/BTO-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