Lavoisier Documentation

Welcome to the comprehensive documentation for the Lavoisier mass spectrometry analysis framework. Lavoisier is a high-performance computing framework that combines numerical and visual processing methods with integrated artificial intelligence modules for automated compound identification and structural elucidation.

🎯 NEW: Buhera Scripting Language

Lavoisier now includes Buhera, a revolutionary domain-specific scripting language that transforms mass spectrometry analysis by encoding the actual scientific method as executable scripts.

Buhera Documentation

• 📋 Buhera Overview - Complete introduction to the Buhera scripting language
• 📖 Language Reference - Comprehensive syntax and semantics reference
• 🔧 Integration Guide - Detailed guide to Buhera-Lavoisier integration
• 📚 Tutorials - Step-by-step tutorials from beginner to advanced
• 💼 Script Examples - Practical examples for various applications

Key Buhera Features

• 🎯 Objective-First Analysis: Scripts declare explicit scientific goals before execution
• ✅ Pre-flight Validation: Catch experimental flaws before wasting time and resources
• 🧠 Goal-Directed AI: Bayesian evidence networks optimized for specific objectives
• 🔬 Scientific Rigor: Enforced statistical requirements and biological coherence

Core Lavoisier Framework

System Architecture & Installation

• 🏗️ Architecture Overview - System design and component relationships
• ⚙️ Installation Guide - Setup instructions and requirements
• 🚀 Performance Benchmarks - System performance characteristics

AI Modules & Intelligence

• 🤖 AI Modules Overview - Comprehensive guide to all AI modules
• 🧠 Specialized Intelligence - Domain-specific AI capabilities
• 🔗 HuggingFace Integration - Machine learning model integration
• 📊 Embodied Understanding - 3D molecular reconstruction validation

Analysis Pipelines

• 🔢 Numerical Analysis - Mathematical foundations and algorithms
• 👁️ Visual Processing - Computer vision and image analysis
• 📈 Results & Validation - Analysis outputs and validation metrics

Development & Integration

• 🔧 Implementation Roadmap - Development planning and milestones
• 🦀 Rust Integration - High-performance Rust components
• 🐍 Python Integration - Python module organization
• 🚗 Autobahn Integration - Probabilistic reasoning integration

Benchmarking & Validation

• 📊 Benchmarking - Performance evaluation methodologies
• 📋 Task Specifications - Analytical task definitions and requirements

Quick Start Guide

1. Traditional Lavoisier Analysis

# Install Lavoisier
pip install lavoisier

# Run basic analysis
lavoisier analyze --input sample.mzML --output results/

2. Buhera Script Analysis (NEW!)

# Build Buhera language
cd lavoisier-buhera && cargo build --release

# Create a script
cat > biomarker_discovery.bh << 'EOF'
objective DiabetesBiomarkerDiscovery:
    target: "identify metabolites predictive of diabetes progression"
    success_criteria: "sensitivity >= 0.85 AND specificity >= 0.85"

validate InstrumentCapability:
    check_instrument_capability
    if target_concentration < instrument_detection_limit:
        abort("Instrument cannot detect target concentrations")

phase EvidenceBuilding:
    evidence_network = lavoisier.mzekezeke.build_evidence_network(
        objective: "diabetes_biomarker_discovery",
        pathway_focus: ["glycolysis", "gluconeogenesis"]
    )
EOF

# Validate and execute
buhera validate biomarker_discovery.bh
buhera execute biomarker_discovery.bh

Use Cases

🔬 Scientific Research

• Biomarker Discovery: Identify disease-specific metabolites with clinical utility
• Drug Metabolism: Characterize hepatic metabolism pathways and drug interactions
• Environmental Analysis: Detect contaminants and assess environmental impact
• Food Safety: Monitor pesticide residues and mycotoxin contamination

🤖 AI & Machine Learning

• Multi-Domain LLM Systems: Template for combining specialized AI models
• Adversarial ML Research: Framework for testing ML robustness
• Bayesian Network Applications: Probabilistic reasoning in scientific domains
• Context Verification: Novel approaches to AI system integrity

🔒 Quality & Validation

• Method Validation: Comprehensive analytical method validation workflows
• Instrument QC: Continuous performance monitoring and predictive maintenance
• Regulatory Compliance: Automated compliance checking and reporting
• Data Integrity: Cryptographic verification of analysis context

Contributing

We welcome contributions to both the core Lavoisier framework and the Buhera scripting language:

1. Core Framework: Python-based AI modules and analysis pipelines
2. Buhera Language: Rust-based language implementation and validation
3. Documentation: Tutorials, examples, and best practices
4. Validation: Test cases and benchmarking datasets

See our implementation roadmap for current development priorities.

Community

• GitHub: lavoisier
• Issues: Report bugs and request features
• Discussions: Share use cases and get help
• Wiki: Community-contributed examples and tutorials

License

Lavoisier is released under the MIT License. See LICENSE file for details.

---

“Only the extraordinary can beget the extraordinary” - Antoine Lavoisier

Transform your mass spectrometry analysis with surgical precision using Lavoisier and Buhera.