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Examples

This directory contains example scripts demonstrating how to use the Logic Network Generator.

Available Examples

1. generate_pathway_example.py

Purpose: Complete example showing how to generate and analyze a pathway logic network.

What it demonstrates:

  • Generating a logic network for a specific Reactome pathway
  • Analyzing network properties (edges, nodes, logic relationships)
  • Finding root inputs and terminal outputs
  • Handling common errors (connection failures, invalid pathways)

Usage:

# Ensure Neo4j is running
docker run -p 7474:7474 -p 7687:7687 \
  -e NEO4J_dbms_memory_heap_maxSize=8g \
  public.ecr.aws/reactome/graphdb:Release94

# Run the example
poetry run python examples/generate_pathway_example.py

Expected Output:

Logic Network Generator - Example Usage
======================================================================

Generating logic network for pathway: Cell Cycle, Mitotic
Pathway ID: 69620

Step 1: Fetching reactions from Neo4j...
Step 2: Decomposing complexes and entity sets...
Step 3: Creating logic network...

======================================================================
Generation Complete!
======================================================================

Network Analysis:
  Total edges: 4995

  Edge types:
    - input: 3200
    - output: 1200
    - catalyst: 350
    - regulator: 245

  Logic relationships:
    - AND edges (required): 4100
    - OR edges (alternatives): 895

  Network structure:
    - Root inputs (starting points): 9
    - Terminal outputs (endpoints): 11
    - Unique physical entities: 458

Example Pathways

Here are some good pathways to try:

Pathway ID Pathway Name Complexity Description
69620 Cell Cycle, Mitotic Medium Well-studied cell cycle pathway
68875 Apoptosis Medium Programmed cell death pathway
1640170 Cell Cycle Large Complete cell cycle regulation
112316 Neuronal System Large Neural signaling pathways
382551 Transport of small molecules Large Molecular transport mechanisms

Common Usage Patterns

Pattern 1: Generate Multiple Pathways

pathway_ids = ["69620", "68875", "112316"]

for pathway_id in pathway_ids:
    generate_pathway_file(
        pathway_id=pathway_id,
        taxon_id="9606",
        pathway_name=f"Pathway_{pathway_id}",
        decompose=False
    )

Pattern 2: Load and Analyze Existing Network

import pandas as pd
from src.logic_network_generator import find_root_inputs, find_terminal_outputs

# Load previously generated network from output directory
network = pd.read_csv("output/pathway_logic_network_69620.csv")

# Find starting and ending points
roots = find_root_inputs(network)
terminals = find_terminal_outputs(network)

# Analyze specific subsets
and_edges = network[network['and_or'] == 'and']
or_edges = network[network['and_or'] == 'or']

print(f"Network has {len(roots)} entry points and {len(terminals)} exit points")
print(f"AND edges: {len(and_edges)}, OR edges: {len(or_edges)}")

Pattern 3: Export for Cytoscape

import pandas as pd

# Load network from output directory
network = pd.read_csv("output/pathway_logic_network_69620.csv")

# Create Cytoscape-compatible format
cytoscape_edges = network[['source_id', 'target_id', 'and_or', 'edge_type']].copy()
cytoscape_edges.columns = ['Source', 'Target', 'Logic', 'EdgeType']

# Save for Cytoscape import
cytoscape_edges.to_csv("network_for_cytoscape.csv", index=False)
print("Exported to network_for_cytoscape.csv")
print("Import in Cytoscape: File → Import → Network from File")

Troubleshooting

Neo4j Connection Issues

Error: ConnectionError: Failed to connect to Neo4j database

Solution:

# Check if Neo4j is running
docker ps | grep reactome

# Start Neo4j if not running
docker run -p 7474:7474 -p 7687:7687 \
  -e NEO4J_dbms_memory_heap_maxSize=8g \
  public.ecr.aws/reactome/graphdb:Release94

# Wait 30 seconds for Neo4j to start, then try again

Invalid Pathway ID

Error: ValueError: No reactions found for pathway ID: 12345

Solution:

  • Verify the pathway ID exists at https://reactome.org/PathwayBrowser/
  • Check that you're using the numeric database ID (not the stable identifier)
  • Try a known working pathway like 69620

Out of Memory

Error: MemoryError or very slow performance

Solution:

  • Start with smaller pathways (< 500 reactions)
  • Increase Neo4j memory: -e NEO4J_dbms_memory_heap_maxSize=16g
  • Run on a machine with more RAM

Additional Resources

  • Main README: README.md - Quick start and features
  • Architecture Documentation: docs/ARCHITECTURE.md - System design and data flow
  • Validation System: VALIDATION_README.md - Comprehensive validation documentation
  • Test Suite: tests/ directory with 62 comprehensive tests
  • Reactome Database: https://reactome.org/