BioNetDB models biology data as a network of nodes and relations.Biology data comes from different formats and sources it comprises system biology data from Reactome, annotation data from CellBase and human genetic variations from healthcare centers' clinical data. BioNetDB relies on Neo4j graph database that allows users to access biological data using the Cypher query language (similar to SQL in relational databases).
The figure below shows BioNetDB nodes with their labels. for clarity, some labels have been shortened:
Shortened labes in the previous figure:
Shortened label | Node label |
---|---|
1 POPUL. FREQUEN | POPULATION_FREQUENCY |
2 FUNCT. SCORE | FUNCTIONAL_SCORE |
3 TRAIT ASSOCIA. | TRAIT_ASSOCIATION |
4 CONSEQ. TYPE | CONSEQUENCE_TYPE |
5 PROTEIN VAR. ANNOT. | PROTEIN_VARIANT_ANNOTATION |
6 SUBST. SCORE | SUBSTITUTION_SCORE |
7 KEYWORD | PROTEIN_KEYWORD |
8 FEATURE | PROTEIN_FEATURE |
This section lists the main nodes of the BioNetDB network data model and for each of them, its properties and relationships are shown.
Gene node properties:
uid
id
name
chromosome
start
end
strand
description:
source
status
Gene relationships:
Transcript node properties:
uid
id
name
biotype
chromosome
proteinId
genomicCodingEnd
genomicCodingStart
annotationFlags
cdnaCodingEnd
cdnaCodingStart
cdsLength
description
status
Transcript relationships (transcript node in pink):
Protein node properties:
uid
id
name
accession
dataset
Protein relationships:
Variant node properties:
uid
id
alternativeNames
Variant relationships:
Regulation node properties:
uid
id
Regulation relationships:
Pathway node properties:
uid
id
Pathway relationships (pathway nodes in yellow):
Table of Contents: