noctua 0.1.3

TODO

noctua-py

Python tools for programmatically manipulating GO-CAM (Gene Ontology Causal Activity Models) via the Noctua/Minerva/Barista API stack, with additional support for querying GO annotations and bioentities via GOlr.

Features

• Build biological pathways programmatically - Create GO-CAM models representing signaling cascades, metabolic pathways, and regulatory networks
• Safe by default - Uses dev server by default; production requires explicit --live flag
• Production protection - Models with state="production" are protected from accidental deletion
• Multiple export formats - Export models as OWL, Turtle, JSON-LD, GAF, Markdown, and more
• Python API and CLI - Use as a library or command-line tool
• Variable tracking - Use simple names instead of IDs for better readability
• Undo/rollback support - Revert operations if needed
• Validation with auto-rollback - Ensure model consistency with automatic rollback on failure
• Individual annotations - Update and manage annotations on model elements
• GO data queries - Search bioentities and annotations via GOlr with precise filtering
• Evidence finding - Automatically find GO annotations that support GO-CAM model edges

Quick Start

Installation

# Install with pip
pip install noctua-py

# Or use uv (recommended)
uv pip install noctua-py

Basic Usage

# Set token for dev server (safe for testing)
# Set your Barista token (required)
# For development: Contact the GO team for a dev token
export BARISTA_TOKEN=your-token-here

# Create a new model
noctua-py barista create-model --title "My pathway model"

# Add molecular activities (with validation)
noctua-py barista add-individual --model gomodel:XYZ --class GO:0003924 \
    --validate "GO:0003924=GTPase activity"

# Export model
noctua-py barista export-model --model gomodel:XYZ --format ttl -o model.ttl

# Clear a model (dev/test models only)
noctua-py barista clear-model --model gomodel:XYZ

Using Production Server

# Get token from Noctua login
export BARISTA_TOKEN=your-production-token

# Use --live flag for production
noctua-py barista create-model --title "Production model" --live

CLI Commands

All commands default to the dev server. Add --live to use production.

Model Management

• create-model - Create a new empty GO-CAM model
• clear-model - Remove all nodes and edges (protected for production models)
• export-model - Export model in various formats (OWL, TTL, JSON-LD, GAF, Markdown)

Building Models

• add-individual - Add a molecular activity/biological process/cellular component
• add-fact - Create relationships between individuals
• add-fact-evidence - Add evidence supporting relationships

Examples

# Build a simple signaling pathway
MODEL_ID=gomodel:68d6f96e00000003

# Add receptor activity
noctua-py barista add-individual --model $MODEL_ID --class GO:0004888 --assign receptor

# Add kinase activity
noctua-py barista add-individual --model $MODEL_ID --class GO:0004674 --assign kinase

# Connect them with causal relationship
noctua-py barista add-fact --model $MODEL_ID \
  --subject receptor --object kinase \
  --predicate RO:0002413  # directly positively regulates

# Add evidence
noctua-py barista add-fact-evidence --model $MODEL_ID \
  --subject receptor --object kinase --predicate RO:0002413 \
  --eco ECO:0000314 --source PMID:12345678

Python API

from noctua.barista import BaristaClient

# Initialize client (uses dev server by default)
client = BaristaClient()

# Create a new model
resp = client.create_model("My model")
model_id = resp.model_id

# Add individuals with variable tracking
client.add_individual(model_id, "GO:0003924", assign_var="ras")
client.add_individual(model_id, "GO:0004674", assign_var="raf")

# Add causal relationship using variables
client.add_fact(model_id, "ras", "raf", "RO:0002413")

# Add with validation and auto-rollback
resp = client.add_individual_validated(
    model_id,
    "GO:0003924",
    expected_type={"id": "GO:0003924", "label": "GTPase activity"}
)
if resp._validation_failed:
    print(f"Validation failed: {resp._validation_reason}")

# Add with undo support
resp = client.add_fact(model_id, "ras", "raf", "RO:0002413", enable_undo=True)
# Can undo if needed
if resp.can_undo():
    resp.undo()

# Update individual annotations
client.update_individual_annotation(
    model_id,
    "ras",  # Can use variable name
    "enabled_by",
    "UniProtKB:P12345"
)

# Export model
export_resp = client.export_model(model_id, format="ttl")

Querying GO Data

from noctua.amigo import AmigoClient

# Initialize Amigo client for GO queries
amigo = AmigoClient()

# Find human kinases
kinases = amigo.search_bioentities(
    text="kinase",
    taxon="NCBITaxon:9606",  # Human
    bioentity_type="protein"
)

# Get annotations for a protein
annotations = amigo.get_annotations_for_bioentity(
    "UniProtKB:P12345",
    evidence_types=["IDA", "IPI"]  # Direct evidence
)

# Find proteins with specific GO function
proteins = amigo.get_bioentities_for_term(
    "GO:0016301",  # protein kinase activity
    include_closure=True,  # Include child terms
    taxon="NCBITaxon:9606"
)

Finding Evidence for GO-CAM Models

# Find supporting GO annotations for model edges
evidence = client.find_evidence_for_edge(
    model_id,
    subject_id="activity1",  # Molecular function
    object_id="protein1",     # Bioentity
    predicate="RO:0002333",   # enabled_by
    evidence_types=["IDA", "IPI"]
)

print(f"Found {len(evidence['annotations'])} supporting annotations")

# Find evidence for all edges in a model
model_evidence = client.find_evidence_for_model(
    model_id,
    evidence_types=["IDA", "IPI", "IMP"],
    limit_per_edge=5
)

print(f"Total annotations: {model_evidence['total_annotations']}")

Safety Features

• Dev server by default - All commands use the test server unless --live is specified
• Production protection - Models with state="production" cannot be cleared without --force
• Confirmation prompts - Destructive operations require confirmation
• Dry-run mode - Preview operations with --dry-run

Environment Variables

• BARISTA_TOKEN - API token (required for mutations)
• BARISTA_BASE - Base URL (default: http://barista-dev.berkeleybop.org)
• BARISTA_NAMESPACE - Namespace (default: minerva_public_dev)
• TEST_MODEL_ID - Model ID for integration tests

Documentation Website

https://geneontology.github.io/noctua-py

Repository Structure

• docs/ - mkdocs-managed documentation
• project/ - project files (these files are auto-generated, do not edit)
• src/ - source files (edit these)
  • noctua
• tests/ - Python tests
  • data/ - Example data

Developer Tools

There are several pre-defined command-recipes available. They are written for the command runner just. To list all pre-defined commands, run just or just --list.

Credits

This project uses the template monarch-project-copier

MCP server (FastMCP)

We expose Barista tools over MCP using FastMCP.

Environment:

• BARISTA_TOKEN (required to perform mutations; read once from environment; no runtime config tool)
• BARISTA_BASE (default: http://barista-dev.berkeleybop.org)
• BARISTA_NAMESPACE (default: minerva_public_dev)
• BARISTA_PROVIDED_BY (default: http://geneontology.org)

Run the server:

uv run fastmcp run src/noctua/mcp_server.py:mcp

Then connect using a compatible MCP client and call tools like:

• add_individual
• add_fact
• add_fact_evidence