https://github.com/halaway/graph-net-project
Examining the versatility of database management systems, we use Neo4j along with Spark to establish connections between nodes and optimize user question-oriented queries.
https://github.com/halaway/graph-net-project
Last synced: 2 months ago
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Examining the versatility of database management systems, we use Neo4j along with Spark to establish connections between nodes and optimize user question-oriented queries.
- Host: GitHub
- URL: https://github.com/halaway/graph-net-project
- Owner: halaway
- Created: 2023-10-13T15:47:41.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-15T03:33:49.000Z (over 2 years ago)
- Last Synced: 2025-03-18T16:55:44.799Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 6.89 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# graph-net-project
🚀 This project examines graph-based data storage for managing and connecting nodes from
components such as _Compounds_, _Diseases_, _Genes_, and _Anatomies_ with an interactive Graphical User Interface for Queries.
## 📖 Files
- The _"nodes_test.tsv"_ contains over 20,000 nodes pertaining to these four element types with
each unique attribute such as _ID_, _Name_, and _Kind_.
| ID | Name | Kind |
| ---------------------- |:---------------:| ---------:|
|Anatomy::UBERON:0000042 | serous membrane | Anatomy |
| Compound::DB00396 | Progesterone | Compound |
- The _"edges_test.tsv_" file contains over 1M edge relationships between a target and source node
with individually labeled relationship types referred to by the "_metaedges.tsv_" file.
| Metaedge | abbreviation | edges | source_nodes | target_nodes | unbiased |
| ------------------------- |:---------------:| ---------:| ---------------------- |:---------------:| ---------:|
|Anatomy downregulates Gene| AdG | 102240 | 36 | 15097 | 102240|
|Anatomy - expresses - Gene| AeG | 526407 | 241 | 18094 | 453477 |
|Anatomy - upregulates - Gene| AuG | 97848 | 36 | 15929 | 97848|
# 💡 NOTE
- Files Can be hosted on a local Python server using:
python3 -m http.server
- The Neo4J Base Server Requires authentication and must remain active.
- When creating a database, the data should only be loaded once for both Nodes and Edges.
- To execute a query from the terminal:
- run: python3 projectBD.py <"QUERY SELECTED">
# Example Node Structure
- When finding possible treatments for Diseases that have no direct connection to any Compound, the approach for such a query is to begin by navigating the genes that are _DownRegulated\UpRegulated_ by a Compound and Anatomy, in the opposite direction, in which the same Disease localizes. This would create the following graph.
## 📝 QUERIES
The following Cypher Queries solve a specific portion of the project using Neo4J as a graph-based NoSQL Store.
# Return Disease Name
MATCH (n WHERE n.name='Disease' AND
n.id ='Disease::DOID:8577')
RETURN n
# Return Compounds that Palliate or Treat Disease
MATCH m=(n:Data)-[:CpD|CtD]->(b:Data where
b.id='Disease::DOID:7148') RETURN n
# Return Genes that Cause this Disease
MATCH p=(a:Data WHERE a.id='Disease::DOID:7148')
-[r:DaG]->(n:Data where n.name ='Gene') RETURN n
# Return Where Disease Occurs
MATCH p=(a:Data WHERE a.id ='Disease::DOID:7148')
-[r:DlA]->(n:Data) RETURN
# Potential Cures to Diseases
match p = (d:Data where d.name='Disease')-[:DlA]->
(a:Data where a.name ='Anatomy')-[:AuG|AdG]->(g:Data where g.name ='Gene')with d,a,g
match (n:Data where n.name='Compound')-[:CdG|CuG]->
(f:Data where f.name ='Gene' and f.id = g.id)
with d,a,g,n match (n) where not (n)-[:CtD|CpD]->(d) return n
# Loading Nodes: ALREADY LOADED
LOAD CSV WITH HEADERS FROM "http://localhost:8000/nodes_test.tsv"
As row FIELDTERMINATOR "\t"
Create (n:Data {name:row.kind, id:row.id, dataName:row.name})
# Loading Edges: ALREADY LOADED
LOAD CSV WITH HEADERS FROM "http://localhost:8000/edges_test.tsv" AS row FIELDTERMINATOR "\t"
WITH row
WHERE row.ource IS NOT NULL AND row.target IS NOT NULL and row.metaedge is not NULL
MERGE (s:Data {id: row.ource})
MERGE (t:Data {id: row.target})
WITH s, t, row
CALL apoc.create.relationship(s, row.metaedge, {}, t) YIELD rel
RETURN *