mirror of
https://github.com/mims-harvard/ToolUniverse.git
synced 2026-09-19 07:31:47 +08:00
Shanghua
cc20c556d2
- Add BiGG Models API (7 tools for metabolic models) - Add CELLxGENE Census API (7 tools for single-cell data) - Add ChIP-Atlas API (4 tools for ChIP-seq data) - Add 4DN Data Portal API (4 tools for Hi-C data) - Add GTEx v2 API (10 tools for gene expression) - Add Rfam API (9 tools for RNA families) - Add PPI tools (BioGRID, STRING) - Expand Ensembl API (10 additional tools) - Fix duplicate 'status' keys in fourdn_tool.py Co-authored-by: Cursor <cursoragent@cursor.com>
355 lines
11 KiB
Python
355 lines
11 KiB
Python
"""
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Comprehensive Examples for 4 Scientific APIs
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This module demonstrates tools from:
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1. BioModels - Systems biology computational models
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2. HCA (Human Cell Atlas) - Single-cell data
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3. IEDB (Immune Epitope Database) - Immunology data
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4. Pathway Commons - Biological pathway interactions
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All these tools were discovered as complete implementations needing tests/examples.
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Author: ToolUniverse
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Date: February 2026
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"""
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from tooluniverse import ToolUniverse
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def example_1_biomodels_search():
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"""
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Example 1: Search BioModels for systems biology models
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BioModels database contains computational models of biological processes
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in SBML and other formats, used for simulation and analysis.
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"""
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print("\n" + "="*80)
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print("Example 1: Search BioModels for Computational Models")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Search for glycolysis models
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result = tu.tools.biomodels_search(**{
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"query": "glycolysis",
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"limit": 3
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})
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if result["status"] == "success" and "data" in result:
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matches = result["data"].get("matches", [])
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print(f"\n✅ Found {result.get('count', 0)} glycolysis models")
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if matches:
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print("\nTop results:")
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for i, model in enumerate(matches[:3], 1):
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print(f"\n{i}. {model.get('name', 'N/A')}")
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print(f" ID: {model.get('id', 'N/A')}")
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print(f" Format: {model.get('format', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_2_biomodels_get_and_download():
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"""
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Example 2: Get BioModels metadata and download information
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Retrieve detailed information about a specific model and get download URLs.
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"""
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print("\n" + "="*80)
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print("Example 2: BioModels - Get Model Details and Files")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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model_id = "BIOMD0000000469"
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# Get model metadata
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result = tu.tools.BioModels_get_model(**{"model_id": model_id})
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if result["status"] == "success" and "data" in result:
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model = result["data"]
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print(f"\n✅ Model: {model.get('name', 'N/A')}")
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print(f" Format: {model.get('format', 'N/A')}")
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print(f" Created: {model.get('created', 'N/A')}")
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# List available files
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files_result = tu.tools.BioModels_list_files(**{"model_id": model_id})
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if files_result["status"] == "success":
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print(f"\n Files available: {files_result.get('count', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_3_hca_search_projects():
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"""
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Example 3: Search Human Cell Atlas projects by organ
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HCA contains single-cell RNA-seq data from various organs and diseases.
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Find projects filtering by organ or disease.
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"""
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print("\n" + "="*80)
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print("Example 3: Human Cell Atlas - Search Projects by Organ")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Search for heart projects
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result = tu.tools.hca_search_projects(**{
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"action": "search_projects",
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"organ": "heart",
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"limit": 3
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})
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if "projects" in result and not result.get("error"):
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print(f"\n✅ Found {result.get('total_hits', 0)} heart projects")
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for i, project in enumerate(result["projects"][:3], 1):
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print(f"\n{i}. {project.get('projectTitle', 'N/A')}")
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print(f" ID: {project.get('entryId', 'N/A')}")
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print(f" Organs: {project.get('organ', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_4_hca_get_files():
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"""
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Example 4: Get downloadable files from HCA project
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Retrieve file manifest with download URLs for a specific project.
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"""
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print("\n" + "="*80)
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print("Example 4: HCA - Get Project File Manifest")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Using example project ID
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project_id = "7027adc6-c9c9-46f3-84ee-9badc3a4f53b"
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result = tu.tools.hca_get_file_manifest(**{
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"action": "get_file_manifest",
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"project_id": project_id,
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"limit": 5
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})
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if "files" in result and not result.get("error"):
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print(f"\n✅ Found {result.get('total_files', 0)} total files")
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print(f" Showing first {len(result['files'])} files:")
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for i, file in enumerate(result["files"][:5], 1):
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print(f"\n{i}. {file.get('name', 'N/A')}")
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print(f" Format: {file.get('format', 'N/A')}")
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print(f" Size: {file.get('size', 0)} bytes")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_5_iedb_search_epitopes():
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"""
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Example 5: Search IEDB for epitopes
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IEDB contains immune epitope data for vaccine design and immunology research.
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Search for epitopes with various filters.
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"""
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print("\n" + "="*80)
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print("Example 5: IEDB - Search Epitopes")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Search epitopes
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result = tu.tools.iedb_search_epitopes(**{"limit": 5})
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if result["status"] == "success" and "data" in result:
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epitopes = result["data"]
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print(f"\n✅ Found {len(epitopes)} epitopes")
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for i, epitope in enumerate(epitopes[:3], 1):
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print(f"\n{i}. Epitope ID: {epitope.get('epitope_id', 'N/A')}")
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print(f" Sequence: {epitope.get('linear_sequence', 'N/A')[:50]}")
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print(f" Type: {epitope.get('structure_type', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_6_iedb_search_antigens():
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"""
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Example 6: Search IEDB for antigens and MHC data
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Find antigens and MHC binding information useful for immunology research.
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"""
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print("\n" + "="*80)
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print("Example 6: IEDB - Search Antigens and MHC")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Search antigens
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antigen_result = tu.tools.iedb_search_antigens(**{"limit": 3})
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if antigen_result["status"] == "success":
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print(f"\n✅ Antigens found: {len(antigen_result.get('data', []))}")
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# Search MHC binding data
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mhc_result = tu.tools.iedb_search_mhc(**{"limit": 3})
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if mhc_result["status"] == "success":
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print(f"✅ MHC entries found: {len(mhc_result.get('data', []))}")
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def example_7_pathway_commons_search():
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"""
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Example 7: Search Pathway Commons for biological pathways
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Pathway Commons aggregates pathway data from multiple sources
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(Reactome, KEGG, PANTHER, etc.) for comprehensive pathway analysis.
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"""
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print("\n" + "="*80)
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print("Example 7: Pathway Commons - Search Pathways")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Search for apoptosis pathways
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result = tu.tools.pc_search_pathways(**{
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"action": "search_pathways",
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"keyword": "apoptosis",
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"limit": 5
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})
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if "pathways" in result and not result.get("error"):
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print(f"\n✅ Found {result.get('total_hits', 0)} apoptosis pathways")
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for i, pathway in enumerate(result["pathways"][:3], 1):
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print(f"\n{i}. {pathway.get('name', 'N/A')}")
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print(f" Source: {pathway.get('source', 'N/A')}")
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print(f" Organism: {pathway.get('organism', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_8_pathway_commons_interactions():
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"""
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Example 8: Get gene interaction network from Pathway Commons
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Retrieve interaction networks for specific genes in SIF format,
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showing relationships like controls, binds, or participates with.
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"""
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print("\n" + "="*80)
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print("Example 8: Pathway Commons - Gene Interaction Network")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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# Get interactions for TP53 and MDM2
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result = tu.tools.pc_get_interactions(**{
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"action": "get_interaction_graph",
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"gene_list": ["TP53", "MDM2"]
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})
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if "interactions" in result and not result.get("error"):
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print(f"\n✅ Found {len(result['interactions'])} interactions")
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print(f" Format: {result.get('format', 'N/A')}")
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print("\nInteractions:")
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for i, interaction in enumerate(result["interactions"][:10], 1):
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print(f"{i}. {interaction.get('source', 'N/A')} "
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f"--[{interaction.get('relation', 'N/A')}]--> "
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f"{interaction.get('target', 'N/A')}")
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else:
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print(f"❌ Error: {result.get('error', 'Unknown')}")
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def example_9_cross_database_workflow():
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"""
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Example 9: Cross-database workflow combining multiple tools
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Demonstrate using multiple APIs together for comprehensive analysis:
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1. Search pathways in Pathway Commons
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2. Find computational models in BioModels
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3. Look up immune data in IEDB
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"""
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print("\n" + "="*80)
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print("Example 9: Cross-Database Workflow")
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print("="*80)
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tu = ToolUniverse()
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tu.load_tools()
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keyword = "p53"
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print(f"\nSearching for '{keyword}' across databases...")
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# 1. Pathway Commons
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pc_result = tu.tools.pc_search_pathways(**{
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"action": "search_pathways",
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"keyword": keyword,
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"limit": 2
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})
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if "pathways" in pc_result:
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print(f"\n✅ Pathway Commons: {pc_result.get('total_hits', 0)} pathways")
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# 2. BioModels
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bm_result = tu.tools.biomodels_search(**{
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"query": keyword,
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"limit": 2
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})
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if bm_result["status"] == "success":
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print(f"✅ BioModels: {bm_result.get('count', 0)} models")
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# 3. IEDB (search epitopes)
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iedb_result = tu.tools.iedb_search_epitopes(**{"limit": 2})
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if iedb_result["status"] == "success":
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print(f"✅ IEDB: {len(iedb_result.get('data', []))} epitopes")
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print("\nCross-database search complete!")
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def main():
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"""Run all examples"""
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print("\n" + "="*80)
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print("4 SCIENTIFIC APIs - COMPREHENSIVE USAGE EXAMPLES")
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print("="*80)
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print("\nDemonstrating:")
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print("• BioModels - Systems biology computational models")
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print("• HCA - Human Cell Atlas single-cell data")
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print("• IEDB - Immune Epitope Database")
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print("• Pathway Commons - Biological pathway networks")
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# Run examples
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example_1_biomodels_search()
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example_2_biomodels_get_and_download()
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example_3_hca_search_projects()
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example_4_hca_get_files()
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example_5_iedb_search_epitopes()
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example_6_iedb_search_antigens()
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example_7_pathway_commons_search()
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example_8_pathway_commons_interactions()
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example_9_cross_database_workflow()
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print("\n" + "="*80)
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print("All examples completed!")
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print("="*80)
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print("\n📚 Resources:")
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print("- BioModels: https://www.ebi.ac.uk/biomodels/")
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print("- HCA: https://data.humancellatlas.org/")
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print("- IEDB: https://www.iedb.org/")
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print("- Pathway Commons: https://www.pathwaycommons.org/")
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print("\n💡 Tips:")
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print("- BioModels: Great for finding validated computational models")
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print("- HCA: Filter by organ/disease for targeted single-cell data")
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print("- IEDB: Essential for vaccine design and immunology research")
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print("- Pathway Commons: Aggregates pathways from multiple sources")
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if __name__ == "__main__":
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main()
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