Upload 2 files

README.md

@@ -1,566 +1,149 @@
 ---
-title: CopernicusAI - Research-Driven Podcast Generation Platform
-emoji: 🔬
-colorFrom: purple
+title: GLMP - Genome Logic Modeling Project
+emoji: 🧬
+colorFrom: green
 colorTo: blue
 sdk: static
-pinned: false
+pinned: true
 license: mit
 ---
 
-# 🔬 CopernicusAI - Knowledge Engine for Scientific Discovery
+# 🧬 GLMP - Genome Logic Modeling Project
 
-A collaborative research platform that transforms cutting-edge scientific research into accessible, multi-format tools for collective knowledge exploration. These are research instruments—like microscopes for observing the collective knowledge of humanity—enabling hypothesis formation, testing, and discovery across scientific disciplines.
-
-## Summary
-
-**CopernicusAI** is an operational research platform that synthesizes scientific literature from 250+ million papers into AI-generated podcasts, integrates with a knowledge graph of 12,000+ indexed papers, and provides collaborative tools for research discovery. The system demonstrates production-ready multi-source research synthesis with full citation tracking and evidence-based content generation requiring minimum 3 research sources per episode.
-
-The platform includes a fully operational Research Tools Dashboard (deployed December 2025) with interactive knowledge graph visualization, vector search, and RAG capabilities, enabling researchers to explore, query, and synthesize scientific knowledge across disciplines.
-
-## Prior Work: CopernicusAI Research Interface
-
-CopernicusAI is an active research prototype exploring AI-generated audio briefings as an interface for assisted scientific research.
-
-The system allows any user to generate, refine, and share AI-generated science podcasts based on structured prompts, enabling rapid orientation to a topic, iterative deepening, and personalized research briefings.
-
-Rather than functioning as a static content platform, CopernicusAI supports collectively generated and shared research artifacts, analogous to community-driven knowledge platforms (e.g., discussion forums), but grounded in scientific sources and metadata-aware workflows.
-
-This work demonstrates technical feasibility for:
-- AI-assisted research briefing and orientation
-- Iterative question refinement via conversational interfaces
-- Integration of text, audio, and metadata in research workflows
-
-### Current Implementation (December 2025)
-
-The Research Tools Dashboard is **fully operational** and deployed to Google Cloud Run, providing unified access to all components with interactive knowledge graph visualization, vector search, RAG queries, and content browsing.
-
-## 🎯 Mission & Vision
-
-Inspired by Nicolaus Copernicus who challenged accepted knowledge with evidence and rigorous analysis, **CopernicusAI** creates collaborative research tools that enable collective participation in scientific discovery. These platforms are instruments for exploring humanity's collective knowledge—tools for hypothesis formation, testing, and collaborative research, not just educational content.
-
-Just as a microscope enables observation of the microscopic world, CopernicusAI tools enable observation and exploration of humanity's collective knowledge. Subscribers collaborate to prompt, generate, and refine research content—sharing discoveries publicly or keeping them private. As large language models (LLMs) and AI systems gain unprecedented knowledge, CopernicusAI provides the infrastructure for human-AI collaborative knowledge exploration, with evidence-based truth-seeking as our guiding principle.
-
----
-
-## 🌟 Core Platform Capabilities
-
-### 🎙️ AI-Powered Podcast Generation
-
-**Production-Ready System:**
-- Collaborative platform where subscribers prompt and generate multi-voice AI podcasts (5-10 minutes) synthesizing research from multiple academic sources
-- Subscribers can share their podcasts publicly or keep them private
-- Evidence-based content generation requiring minimum 3 research sources per episode
-- Comprehensive research integration across 8+ academic databases
-- **64 episodes** generated across Biology, Chemistry, Computer Science, Mathematics, and Physics
-- Automated audio synthesis with professional multi-speaker dialogue
-- AI-generated episode thumbnails with scientific visualizations
-- RSS feed distribution compatible with Spotify, Apple Podcasts, Google Podcasts
-
-**Research Integration:**
-- Real-time discovery from PubMed, arXiv, NASA ADS, Zenodo, bioRxiv, CORE, Google Scholar, and News APIs
-- Parallel search across multiple databases for comprehensive coverage
-- Quality scoring and relevance ranking of research sources
-- Paradigm shift identification and interdisciplinary connection analysis
-- Automatic citation extraction and formatting
-- Source validation and authenticity verification
-
-### 🤖 Advanced LLM Integration
-
-**Multi-Model Architecture:**
-- **Google Gemini 3** - Latest research analysis and content generation
-- **OpenAI GPT-4/GPT-3.5** - Content synthesis and quality validation
-- **Anthropic Claude 3** (Sonnet, Haiku via OpenRouter) - Alternative reasoning paths
-- **ElevenLabs TTS** - Multi-voice text-to-speech synthesis
-- Model selection based on task complexity and expertise level
-- Fallback chains for reliability and cost optimization
-
-**Capabilities:**
-- Multi-paper analysis and synthesis
-- Paradigm shift detection in research domains
-- Interdisciplinary connection identification
-- Entity extraction (genes, proteins, chemical compounds, mathematical concepts)
-- Citation tracking and cross-reference analysis
-- Content quality scoring and validation
-
-### 📊 Research Resource Access
-
-**Comprehensive Academic Database Coverage:**
-
-Our research pipeline integrates with **8+ major academic databases**, providing access to:
-
-- **PubMed/NCBI** (~30+ million biomedical papers)
-- **arXiv** (~2+ million preprints in physics, mathematics, CS, quantitative biology)
-- **NASA ADS** (~15+ million astronomy/astrophysics papers)
-- **Zenodo** (100K+ open science datasets and publications)
-- **bioRxiv/medRxiv** (preprints in life sciences)
-- **CORE** (~200+ million open access papers)
-- **Google Scholar** (comprehensive academic search)
-- **News API** (current events and trending research topics)
-- **YouTube Data API** (academic videos, conference talks, lectures)
-
-**Total Access:** **250+ million research papers and academic resources** across all major scientific disciplines.
-
-### 🎙️ Audio and Video Podcast Production
-
-**Operating Audio Podcast System:**
-Full production and distribution platform for subscriber-generated podcasts. Users can prompt, generate, publish, and distribute audio podcasts with RSS feed support for Spotify, Apple Podcasts, and Google Podcasts.
-
-- Multi-voice AI podcast generation
-- Research-driven content creation
-- RSS feed distribution
-- Public and private podcast options
-- Professional audio quality
-
-**Video Production (Future - Phase 2+):**
-
-Advanced video features planned for future development:
-
-**Planned Advanced Features (Phase 2-4):**
-- **Visual Content Integration:**
-  - Automated extraction of figures and diagrams from research papers
-  - Screen capture and processing of academic illustrations
-  - Web scraping from scientific journal websites and preprint servers
-  - JSON database integration for structured visual data
-
-- **Dynamic Visualization Generation:**
-  - On-the-fly scientific animations (molecular structures, data flows, algorithms)
-  - Real-time chart and graph generation from research data
-  - Python-based animations using matplotlib, plotly, mayavi
-  - Mathematical formula rendering (LaTeX → video)
-
-- **External Video Quoting:**
-  - YouTube video segment extraction and integration
-  - Time-stamped video quoting with proper attribution
-  - Educational fair use compliance
-  - Source video discovery during research phase
-
-- **Advanced Composition:**
-  - Multi-layer video composition (background, content, overlays, effects)
-  - Automatic subtitle generation from transcripts
-  - Text overlay system (key concepts, citations, speaker identification)
-  - Professional transitions and effects
-  - Audio-visual synchronization
-
-**See:** [Science Video Database](https://huggingface.co/spaces/garywelz/sciencevideodb) - Companion project for research video content management.
-
-### 📚 Research Papers Metadata Database (Phase 2)
-
-**Planned Implementation:**
-A centralized **metadata repository** (not a file archive) that provides:
-
-- **Structured JSON Objects:** Research paper metadata including:
-  - DOI, arXiv ID, publication information
-  - Abstracts and key findings
-  - Extracted entities (genes, proteins, chemical compounds, equations)
-  - Citation networks and cross-references
-  - Paradigm shift indicators
-  - Interdisciplinary connections
-  - Quality scores and relevance metrics
-
-- **AI-Powered Preprocessing:**
-  - LLM-based entity extraction and annotation
-  - Automatic categorization by discipline and subdomain
-  - Keyword extraction and semantic tagging
-  - Citation tracking and relationship mapping
-  - Quality assessment and validation
-
-- **Integration Features:**
-  - DOI/arXiv ID resolution and metadata enrichment
-  - Cross-reference linking between papers
-  - Podcast-to-paper relationship tracking
-  - Search and query capabilities
-  - API access for programmatic retrieval
-
-**Technical Architecture:**
-- Firestore NoSQL database for flexible JSON storage
-- Google Cloud Functions for automated metadata processing
-- Vertex AI for entity extraction and analysis
-- RESTful API for external access
-
-**Benefits:**
-- Enables rapid research discovery across podcasts
-- Supports knowledge graph construction
-- Facilitates cross-disciplinary pattern recognition
-- Provides foundation for semantic search capabilities
-
----
-
-## 🗄️ System Architecture
-
-### Database Structure (Firestore)
-
-**Collections:**
-- **`subscribers`** - User accounts, preferences, subscription tiers, usage analytics
-- **`podcast_jobs`** - Generated podcasts with full metadata, source papers, engagement metrics
-- **`episodes`** - Published episodes with RSS distribution status
-- **`research_papers`** (Phase 2) - Paper metadata database with AI-extracted entities
-
-### Storage Structure (Google Cloud Storage)
-
-- **`audio/`** - MP3 podcast files (multi-voice ElevenLabs synthesis)
-- **`videos/`** - MP4 video podcasts (current and future)
-- **`transcripts/`** - Full text transcripts with speaker markers
-- **`descriptions/`** - Markdown descriptions with academic references
-- **`thumbnails/`** - AI-generated episode artwork (DALL-E 3)
-- **`video-assets/`** - Extracted figures, animations, visual content
-- **`glmp-v2/`** - Genome Logic Modeling Project flowcharts (JSON)
-
-### Backend Services (Google Cloud Run)
-
-**Microservices Architecture:**
-- **Podcast Generation Service** - Orchestrates research, content generation, and media production
-- **Research Pipeline Service** - Multi-API academic search and analysis
-- **Video Generation Service** - Video composition and encoding (Phase 1 complete)
-- **RSS Service** - Feed generation and distribution
-- **Episode Service** - Catalog management and metadata
-
----
-
-## ⚙️ Technology Stack
-
-### AI & Machine Learning
-- **Google Gemini 3** - Latest LLM for research analysis
-- **Google Vertex AI** - Enterprise-scale model deployment and orchestration (used throughout platform)
-- **OpenAI GPT-4/GPT-3.5** - Content synthesis and validation
-- **Anthropic Claude 3** - Alternative reasoning via OpenRouter
-- **ElevenLabs TTS** - Multi-voice text-to-speech synthesis
-- **DALL-E 3** - AI-generated scientific visualizations
-- **Google Cloud Vision API** - Image analysis and quality assessment
-- **Video Intelligence API** - Scene detection and content analysis
-
-### Backend Infrastructure
-- **FastAPI** (Python) - RESTful API framework
-- **Google Cloud Run** - Serverless container deployment
-- **Firestore** - NoSQL document database
-- **Cloud Storage** - Media file storage and CDN
-- **Cloud Functions** - Event-driven processing
-- **Cloud Tasks** - Background job queuing
-- **Secret Manager** - API key and credential management
-
-### Media Processing
-- **FFmpeg** - Video encoding and composition
-- **MoviePy** - Python video editing (planned)
-- **Matplotlib/Plotly** - Scientific visualization (planned)
-- **PyPDF2/pdfplumber** - PDF processing (planned)
-
-### Frontend
-- **Next.js 15.5.7** - React framework
-- **Alpine.js** - Lightweight reactive UI
-- **Tailwind CSS** - Utility-first styling
-- **Vercel** - Frontend hosting and deployment
-
----
-
-## 📈 Platform Capabilities
-
-### Research Coverage
-- **250+ million research papers** accessible through integrated APIs
-- **8+ academic databases** integrated with parallel search
-- **Minimum 3 sources** required per episode for quality assurance
-- **Multi-paper analysis** for comprehensive coverage
-
-### Platform Features
-- **Subscriber-driven content generation** - Users prompt and create podcasts
-- **RSS feed distribution** to major podcast platforms
-- **Public and private podcast options** - Share discoveries or keep them private
-
----
-
-## 🔗 Live Platform & Resources
-
-### Production Deployment
-- 🏠 **[Homepage - Browse Podcasts](https://www.copernicusai.fyi)** - Public podcast catalog
-- 📊 **[Creator Dashboard](https://www.copernicusai.fyi/subscriber-dashboard.html)** - Subscriber interface
-- 📡 **[RSS Feed](https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/feeds/copernicus-mvp-rss-feed.xml)** - Podcast distribution feed
-
-## 🧩 CopernicusAI Knowledge Engine Components
-
-The CopernicusAI Knowledge Engine is an integrated ecosystem of research and collaboration tools. The Knowledge Engine is **fully implemented and operational** (December 2025), with a working system deployed to Google Cloud Run. Currently, the platform includes five core components, with additional tools, databases, and collaboration features planned for future development:
-
-### 🎯 Knowledge Engine Implementation (December 2025)
-
-**Fully Operational System:**
-- **Public Project Interface:** https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html
-- **Research Tools Dashboard:** https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine
-- **Knowledge Graph:** Interactive visualization with 23,246 indexed papers, relationship extraction (citations, semantic similarity, categories), and graph query capabilities
-- **Vector Search:** Semantic search using Vertex AI embeddings across papers, podcasts, and processes
-- **RAG System:** Retrieval-augmented generation with citation support, context retrieval, and multi-modal content integration
-- **Unified Web Dashboard:** Production-ready interface with knowledge map visualization, search, RAG queries, content browsing, and statistics
-- **Architecture:** FastAPI backend, Next.js frontend, Firestore database, Vertex AI for embeddings and LLM capabilities, Model Context Protocol (MCP) server for AI assistant integration
-- **Deployment:** Fully deployed to Google Cloud Run, accessible 24/7
-
-### Core Components
-
-1. **🔬 CopernicusAI (This Platform)** - Core synthesis and distribution component
-   - AI-powered research synthesis and podcast generation
-   - Multi-API research integration (250+ million papers)
-   - Subscriber-driven content creation and sharing
-   - RSS feed distribution and platform management
-
-2. **🛠️ Programming Framework** - Foundational meta-tool
-   - Universal method for process analysis across any discipline
-   - LLM-powered extraction and Mermaid visualization
-   - Domain-agnostic methodology for complex process analysis
-   - [Explore Framework →](https://huggingface.co/spaces/garywelz/programming_framework)
-
-3. **🧬 GLMP - Genome Logic Modeling Project** - Specialized biological application
-   - First application of Programming Framework to biology
-   - 50+ biological processes visualized as interactive flowcharts
-   - JSON-based structured data in Google Cloud Storage
-   - [Explore GLMP →](https://huggingface.co/spaces/garywelz/glmp)
-
-4. **📚 Research Paper Metadata Database** - Core data infrastructure
-   - Centralized metadata repository for scientific research papers
-   - AI-powered preprocessing and entity extraction
-   - Citation network analysis and relationship mapping
-   - Foundation for knowledge graph construction
-   - [Explore Metadata Database →](https://huggingface.co/spaces/garywelz/metadata_database)
-
-5. **🎬 Science Video Database** - Multi-modal content component
-   - Curated searchable database of scientific video content
-   - Transcript-based search across multiple disciplines
-   - Integration with YouTube and other video sources
-   - [Explore Video Database →](https://huggingface.co/spaces/garywelz/sciencevideodb)
-   - [Live Demo →](https://scienceviddb-web-204731194849.us-central1.run.app/)
-
-### Future Components
-
-The Knowledge Engine is designed to grow and evolve. Additional tools, databases, and collaboration components will be added as the project develops, expanding capabilities for AI-assisted scientific research and knowledge discovery.
-
----
-
-## 🔌 API Documentation
-
-**Base URL:** `https://copernicus-podcast-api-phzp4ie2sq-uc.a.run.app`
-
-### Podcast Generation Endpoints
-- `POST /generate-podcast-with-subscriber` - Generate new podcast from research topic
-- `GET /api/subscribers/podcasts/{id}` - Retrieve podcast details
-- `POST /api/subscribers/podcasts/submit-to-rss` - Publish to RSS feed
-
-### Research Endpoints
-- `POST /api/papers/upload` - Upload paper metadata (Phase 2)
-- `GET /api/papers/{paper_id}` - Retrieve paper metadata
-- `POST /api/papers/query` - Query papers by discipline, keywords
-- `POST /api/papers/{id}/link-podcast/{id}` - Link paper to podcast
-
-### Admin Endpoints
-- `GET /api/admin/subscribers` - List all subscribers and statistics
-- `POST /api/admin/podcasts/fix-missing-titles` - Content maintenance
-- `GET /api/admin/podcasts/catalog` - Full podcast catalog
-
----
-
-## 🚀 Development Roadmap
-
-### ✅ Phase 1: Core Platform (Complete)
-- Multi-API research integration
-- AI podcast generation with multi-voice synthesis
-- RSS feed distribution
-- Subscriber platform
-- Basic video generation (static)
-
-### 🔄 Phase 2: Content Enhancement (In Progress)
-- **Research Papers Metadata Database** - JSON-based metadata repository
-- **Visual Content Extraction** - Figures from papers, web scraping
-- **YouTube Video Quoting** - External video integration with attribution
-- **Advanced Video Features** - Multi-layer composition, animations
-
-### 📋 Phase 3: Advanced Visualizations (Planned)
-- Scientific animation generation (matplotlib, plotly)
-- Real-time data visualization
-- Mathematical formula rendering
-- Dynamic graph and network visualizations
-
-### ✅ Phase 4: Knowledge Integration (Implemented - December 2025)
-- **Knowledge Graph:** Fully operational with interactive visualization, 12,000+ papers indexed
-- **Vector Search:** Semantic search implemented using Vertex AI embeddings
-- **RAG System:** Retrieval-augmented generation with citations operational
-- **Cross-Disciplinary Pattern Discovery:** Relationship extraction across papers, concepts, and categories
-- **AI-Powered Content Recommendations:** Integrated into unified web dashboard
-- **Public Project Interface:** https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html
-- **Research Tools Dashboard:** https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine
-
----
-
-## 🔬 Collaborative Research Tools
-
-**These platforms enable collective participation and collaboration across diverse user communities:**
-
-- **Researchers** - Tools for hypothesis formation and testing, rapid synthesis of cross-disciplinary findings
-- **Collaborators** - Collective knowledge exploration and refinement
-- **Subscribers** - Prompt, generate, and share podcasts (public or private)
-- **Community** - User suggestions, comments, and collaborative flowchart improvement (GLMP)
-
-**Key Innovations:**
-- **Multi-Source Validation** - Requires minimum 3 research sources per episode
-- **Evidence-Based Generation** - No content generated without research backing
-- **Paradigm Shift Detection** - Identifies revolutionary vs. incremental research
-- **Interdisciplinary Connections** - Reveals cross-domain insights
-- **Collaborative Participation** - User-driven content generation and sharing
-- **Reproducibility** - Full citation tracking and source attribution
-
-> *Like a microscope enables observation of the microscopic world, these tools enable observation and exploration of humanity's collective knowledge.*
-
----
+A microscope for biological processes. GLMP applies the Programming Framework to visualize complex biochemical processes as interactive flowcharts, revealing the logic of life at the molecular level.
 
 ## 📚 Prior Work & Research Contributions
 
 ### Overview
-This platform represents **prior work** that demonstrates foundational research and development achievements in AI-powered scientific knowledge synthesis, collaborative research tools, and multi-modal content generation. These contributions establish the technical foundation and proof-of-concept for the broader **CopernicusAI Knowledge Engine** initiative.
-
-### Research Contributions
-
-**1. AI-Powered Research Synthesis System**
-- Developed and deployed a production-ready system for multi-source research synthesis using LLMs
-- Demonstrated integration of 8+ academic databases (250+ million papers) with parallel search capabilities
-- Implemented evidence-based content generation requiring minimum 3 research sources per output
-- Achieved operational deployment with 64+ generated podcast episodes across 5 scientific disciplines
-
-**2. Multi-Model LLM Architecture**
-- Designed and implemented intelligent model selection framework using Google Gemini 3, OpenAI GPT-4, and Anthropic Claude 3
-- Developed fallback chains for reliability and cost optimization
-- Demonstrated paradigm shift detection and interdisciplinary connection identification in research domains
-- Implemented entity extraction (genes, proteins, chemical compounds, mathematical concepts) from research literature
-
-**3. Collaborative Research Platform Infrastructure**
-- Built subscriber-driven content generation system enabling public/private research sharing
-- Implemented RSS feed distribution compatible with major podcast platforms
-- Developed microservices architecture on Google Cloud Run with Firestore and Cloud Storage
-- Created RESTful API framework for programmatic access to research synthesis capabilities
-
-**4. Integration with Knowledge Engine Components**
-- Established integration pathways with GLMP (Genome Logic Modeling Project) for biological process visualization
-- Designed architecture for Research Papers Metadata Database (Phase 2)
-- Planned integration with Science Video Database for multi-modal content
-- Created framework for Programming Framework integration across disciplines
-
-### Technical Achievements
-
-**Production Deployment:**
-- Live platform: https://www.copernicusai.fyi
-- Operational API: https://copernicus-podcast-api-phzp4ie2sq-uc.a.run.app
-- RSS feed distribution: Active and functional
-- Multi-voice audio synthesis: ElevenLabs TTS integration operational
-
-**Research Infrastructure:**
-- 250+ million research papers accessible via integrated APIs
-- 8+ academic database integrations (PubMed, arXiv, NASA ADS, Zenodo, bioRxiv, CORE, Google Scholar, News API)
-- **23,246 papers indexed** with full metadata and vector embeddings in Knowledge Engine
-- Automated citation extraction and formatting
-- Quality scoring and relevance ranking systems
-- **Knowledge Graph:** Fully operational with relationship extraction and interactive visualization
-- **Vector Search:** Semantic search across papers, podcasts, and processes
-- **RAG System:** Operational with citation support and multi-modal content integration
-
-**Scalability & Architecture:**
-- Serverless microservices architecture (Google Cloud Run)
-- NoSQL database (Firestore) for flexible metadata storage
-- Cloud Storage for media files and structured data
-- Event-driven processing with Cloud Functions and Cloud Tasks
-
-### Position Within CopernicusAI Knowledge Engine
-
-This platform serves as the **core synthesis and distribution component** of the CopernicusAI Knowledge Engine. The Knowledge Engine is an integrated ecosystem of research and collaboration tools that work together to assist scientists in their workflow, from research discovery through knowledge synthesis to multi-format content generation.
-
-**Current Components:**
-1. **CopernicusAI** (This platform) - Core synthesis and distribution component for AI-powered research synthesis and podcast generation
-2. **Research Tools Dashboard** (✅ Implemented December 2025) - Fully operational web interface with knowledge graph visualization, vector search, RAG queries, content browsing, and statistics. Live at: https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine
-3. **Public Project Interface** (✅ Implemented January 2025) - Comprehensive public-facing page providing access to all CopernicusAI Knowledge Engine components. Live at: https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html
-4. **Programming Framework** - Foundational meta-tool providing universal process analysis methodology
-5. **GLMP (Genome Logic Modeling Project)** - Specialized biological application demonstrating domain-specific use of the Programming Framework
-6. **Research Paper Metadata Database** - Core data infrastructure providing structured metadata and citation networks
-7. **Science Video Database** - Multi-modal content component enabling video-based learning and research discovery
-
-**Future Development:**
-The Knowledge Engine is designed to grow and evolve. Additional tools, databases, and collaboration components will be added as the project develops, expanding capabilities for AI-assisted scientific research and knowledge discovery.
-
-### Academic & Research Impact
-
-**Publications & Presentations:**
-- Platform architecture and methodology suitable for academic publication
-- Open-source components available for research community use
-- Publicly accessible research tools demonstrating AI-human collaboration in scientific knowledge synthesis
-
-**Research Applications:**
-- Supports hypothesis formation and testing through rapid multi-source synthesis
-- Enables cross-disciplinary pattern recognition and connection identification
-- Facilitates reproducible research communication with full citation tracking
-- Provides infrastructure for collaborative knowledge exploration
-
-**Educational Contributions:**
-- 64+ research-driven podcast episodes across Biology, Chemistry, Computer Science, Mathematics, and Physics
-- Evidence-based content requiring minimum 3 academic sources
-- Public and private sharing options for research dissemination
-- Integration with major podcast platforms for broad accessibility
-
-### Citation Information
-
-**For Grant Proposals:**
-When citing this work as prior research, please reference:
-
-- **Platform Name:** CopernicusAI - Knowledge Engine for Scientific Discovery
-- **URL:** https://huggingface.co/spaces/garywelz/copernicusai
-- **Live Platform:** https://www.copernicusai.fyi
-- **Primary Developer:** Gary Welz
-- **Year:** 2024-2025
-- **License:** MIT
-
-**Suggested Citation Format:**
+The Genome Logic Modeling Project (GLMP) represents **prior work** that demonstrates the first successful application of the Programming Framework to biological process visualization. This research establishes a novel methodology for transforming complex biochemical processes into structured, interactive visual flowcharts using LLM-powered analysis and Mermaid visualization technology.
+
+### 🔬 Research Contributions
+- **Biological Process Visualization:** 50+ processes mapped across 6 major categories
+- **LLM-Powered Analysis:** Automated extraction using Google Gemini 2.0 Flash
+- **Interactive Visualization:** Mermaid.js-based dynamic flowchart system
+- **Knowledge Engine Integration:** Links to CopernicusAI and Programming Framework
+
+### ⚙️ Technical Achievements
+- **Structured Database:** JSON format in Google Cloud Storage
+- **Process Coverage:** Central Dogma, Metabolism, Signaling, Proteins, Photosynthesis, DNA Repair
+- **Scalable Architecture:** GCS-based storage with web viewer integration
+- **Metadata-Rich Format:** Categories, versions, references, source papers
+
+### 🎯 Position Within CopernicusAI Knowledge Engine
+GLMP serves as a **specialized application component** of the CopernicusAI Knowledge Engine, demonstrating how the Programming Framework can be applied to domain-specific scientific visualization. It integrates with:
+
+- Programming Framework (meta-tool)
+- CopernicusAI (main knowledge engine)
+- **Research Tools Dashboard** (✅ Implemented December 2025) - Fully operational web interface with knowledge graph visualization, vector search, RAG queries, and content browsing. Live at: https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine
+- Research Papers Metadata Database
+- Science Video Database
+- Multi-modal learning integration
+
+This work establishes a proof-of-concept for domain-specific applications of the Programming Framework, demonstrating its utility in biological sciences and potential for extension to other scientific disciplines. The Knowledge Engine now provides a unified interface for exploring biological processes alongside research papers, podcasts, and other content types.
+
+## 🎯 What is GLMP?
+
+The Genome Logic Modeling Project is the first specialized application of the [Programming Framework](https://huggingface.co/spaces/garywelz/programming_framework) to the domain of biology. It transforms complex biochemical processes into clear, visual flowcharts that reveal the step-by-step logic underlying life's molecular machinery.
+
+### Key Features
+
+- **50+ Biological Processes** mapped as interactive flowcharts
+- **JSON-based storage** in Google Cloud Storage
+- **LLM-powered analysis** using Google Gemini 2.0
+- **Mermaid visualization** for clear, interactive diagrams
+- **Integration with CopernicusAI** for enhanced learning
+
+## 📚 Process Categories
+
+### 🧬 Central Dogma
+- DNA Replication
+- Transcription
+- Translation
+- RNA Processing
+- Post-translational Modifications
+
+### ⚡ Metabolic Pathways
+- Glycolysis
+- Krebs Cycle (TCA)
+- Oxidative Phosphorylation
+- Gluconeogenesis
+- Pentose Phosphate Pathway
+
+### 📡 Cell Signaling
+- MAPK Pathway
+- PI3K/AKT Pathway
+- Wnt Signaling
+- Notch Pathway
+- JAK-STAT Pathway
+
+### 🔄 Protein Processes
+- Protein Folding
+- Ubiquitination
+- Autophagy
+- Proteasome Degradation
+- Chaperone Systems
+
+### 🌱 Photosynthesis
+- Light Reactions
+- Calvin Cycle
+- C4 Pathway
+- CAM Photosynthesis
+- Photorespiration
+
+### 🔧 DNA Repair
+- Base Excision Repair
+- Nucleotide Excision Repair
+- Mismatch Repair
+- Double-strand Break Repair
+- Direct Repair
+
+## 🗄️ Database
+
+All GLMP flowcharts are stored as JSON files in Google Cloud Storage:
+
 ```
-Welz, G. (2025). CopernicusAI: Knowledge Engine for Scientific Discovery. 
-Hugging Face Space. https://huggingface.co/spaces/garywelz/copernicusai
+gs://regal-scholar-453620-r7-podcast-storage/glmp-v2/
 ```
 
-## 🌐 Grant Support & Collaboration
+Each file contains:
+- Process name and description
+- Mermaid flowchart syntax
+- Metadata (category, version, references)
+- Links to source papers
 
-**Grant Applications Supported:**
-This platform is designed to support grant applications to:
-- **NSF (National Science Foundation)** - Science education and research infrastructure
-- **DOE (Department of Energy)** - Scientific computing and data science
-- **SAIR Foundation** - AI research and development initiatives
+## 🚀 How to Use
 
-**Research Contributions:**
-- Open-source components and methodologies
-- Publicly accessible research tools
-- Educational content for broader scientific literacy
-- Infrastructure for reproducible research communication
+1. **Browse the interactive viewer** on the main page
+2. **Select a biological process** from the dropdown
+3. **Explore the flowchart** showing each step and decision point
+4. **Link to source papers** for deeper understanding
+5. **Integrate with CopernicusAI podcasts** for audio learning
 
-**Collaboration Opportunities:**
-- Integration with academic institutions
-- Partnership with research organizations
-- Open data initiatives
-- Educational program development
+## 🔗 Related Projects
 
----
+- [Programming Framework](https://huggingface.co/spaces/garywelz/programming_framework) - The meta-tool powering GLMP
+- [CopernicusAI](https://huggingface.co/spaces/garywelz/copernicusai) - Knowledge engine integrating GLMP with AI podcasts
 
-## How to Cite This Work
+### How to Cite This Work
 
-Welz, G. (2024–2025). *CopernicusAI: AI-Generated Audio Briefings as a Research Interface*.
-Hugging Face Spaces. https://huggingface.co/spaces/garywelz/copernicusai
+Welz, G. (2024–2025). *Genome Logic Modeling Project (GLMP)*.
+Hugging Face Spaces. https://huggingface.co/spaces/garywelz/glmp
 
----
+This project serves as a testbed for integrating AI systems into scientific reasoning pipelines, enabling both human and AI agents to analyze, compare, and extend biological knowledge structures.
 
-## 📄 License & Attribution
+GLMP is designed as infrastructure for AI-assisted science, not as a static visualization collection.
 
-**License:** MIT
+## 💻 Technology Stack
 
-**Attributions:**
-- Built with Google Cloud Platform, Gemini AI, OpenAI, Anthropic Claude, and ElevenLabs
-- Research data from PubMed, arXiv, NASA ADS, Zenodo, bioRxiv, CORE, and Google Scholar
-- Academic paper metadata from respective publishers
+- **LLM**: Google Gemini 2.0 Flash
+- **Visualization**: Mermaid.js
+- **Storage**: Google Cloud Storage
+- **Format**: JSON
+- **Frontend**: Static HTML + Tailwind CSS
 
 ---
 
-## 📧 Contact & Support
-
-For questions, collaboration inquiries, or grant application support:
-- **Hugging Face Space:** [https://huggingface.co/spaces/garywelz/copernicusai](https://huggingface.co/spaces/garywelz/copernicusai)
-- **Platform:** [https://www.copernicusai.fyi](https://www.copernicusai.fyi)
-
----
+**Part of the CopernicusAI Knowledge Engine**
 
-**© 2025 CopernicusAI. All rights reserved.**
+© 2025 Gary Welz. All rights reserved.
 
-*Advancing scientific knowledge through AI-powered research communication and discovery.*

index.html

@@ -3,11 +3,12 @@
 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>CopernicusAI - Research-Driven Podcast Generation Platform</title>
+    <title>GLMP - Genome Logic Modeling Project</title>
     <script src="https://cdn.tailwindcss.com"></script>
+    <script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
     <style>
         .gradient-bg {
-            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            background: linear-gradient(135deg, #10b981 0%, #059669 100%);
         }
         .card-hover {
             transition: transform 0.3s ease, box-shadow 0.3s ease;
@@ -16,12 +17,8 @@
             transform: translateY(-4px);
             box-shadow: 0 20px 40px rgba(0,0,0,0.15);
         }
-        .stat-number {
-            font-size: 2.5rem;
-            font-weight: bold;
-            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-            -webkit-background-clip: text;
-            -webkit-text-fill-color: transparent;
+        .process-card {
+            border-left: 4px solid #10b981;
         }
     </style>
 </head>
@@ -30,710 +27,295 @@
     <header class="gradient-bg text-white">
         <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-16">
             <div class="text-center">
-                <div class="text-6xl mb-4">🔬</div>
-                <h1 class="text-5xl font-bold mb-4">CopernicusAI</h1>
-                <p class="text-xl opacity-90 mb-6">Knowledge Engine for Scientific Discovery</p>
-                <p class="text-lg opacity-75 max-w-4xl mx-auto">
-                    A collaborative research platform that transforms cutting-edge scientific research into accessible, 
-                    multi-format tools for collective knowledge exploration. These are research instruments—like microscopes 
-                    for observing the collective knowledge of humanity—enabling hypothesis formation, testing, and discovery 
-                    across scientific disciplines.
+                <div class="text-6xl mb-4">🧬</div>
+                <h1 class="text-5xl font-bold mb-4">Genome Logic Modeling Project</h1>
+                <p class="text-xl opacity-90 mb-6">A Microscope for Biological Processes</p>
+                <p class="text-lg opacity-75 max-w-3xl mx-auto">
+                    GLMP applies the Programming Framework to visualize complex biochemical processes as interactive 
+                    flowcharts, revealing the logic of life at the molecular level.
                 </p>
             </div>
         </div>
     </header>
 
-    <!-- Abstract/Summary -->
+    <!-- Prior Work & Research Contributions -->
     <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8 border-l-4 border-purple-600">
-            <h2 class="text-2xl font-bold text-gray-900 mb-4">📋 Summary</h2>
-            <p class="text-lg text-gray-700 leading-relaxed mb-3">
-                <strong>CopernicusAI</strong> is an operational research platform that synthesizes scientific literature from 250+ million papers into AI-generated podcasts, integrates with a knowledge graph of 23,246 indexed papers, and provides collaborative tools for research discovery. The system demonstrates production-ready multi-source research synthesis with full citation tracking and evidence-based content generation requiring minimum 3 research sources per episode.
-            </p>
-            <p class="text-gray-600">
-                The platform includes a fully operational Research Tools Dashboard (deployed December 2025) with interactive knowledge graph visualization, vector search, and RAG capabilities, enabling researchers to explore, query, and synthesize scientific knowledge across disciplines.
-            </p>
-        </div>
-    </section>
-
-    <!-- System Architecture -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">🏗️ Knowledge Engine Architecture</h2>
-            <p class="text-lg text-gray-700 leading-relaxed mb-6">
-                The CopernicusAI Knowledge Engine systematically transforms information into knowledge through integrated capabilities. At its core, a knowledge engine is any system—biological or artificial—that systematically transforms information into knowledge, performing work by converting raw materials (information) into useful outputs (knowledge, understanding, insights).
-            </p>
-            <p class="text-gray-700 mb-6">
-                The system architecture demonstrates the integration of data ingestion, processing, storage, and query capabilities across multiple modalities—research papers, process descriptions, and media content—enabling comprehensive knowledge discovery and synthesis.
-            </p>
+        <div class="bg-gradient-to-r from-green-50 to-blue-50 rounded-xl shadow-lg p-8 mb-8">
+            <h2 class="text-3xl font-bold text-gray-900 mb-6">📚 Prior Work & Research Contributions</h2>
             
-            <div class="bg-gray-50 rounded-lg p-6 mb-6">
-                <img src="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/images/copernicusai_architecture.png" 
-                     alt="Knowledge Engine Architecture Diagram showing data ingestion, processing, storage, and query layers" 
-                     class="w-full rounded-lg shadow-md"
-                     style="max-width: 100%; height: auto;">
-                <p class="text-sm text-gray-600 mt-4 italic text-center">
-                    Figure: Knowledge Engine Architecture - Data flow from ingestion through processing and storage to query interfaces
+            <div class="bg-white rounded-lg p-6 mb-6">
+                <h3 class="text-xl font-semibold text-gray-900 mb-4">Overview</h3>
+                <p class="text-gray-700 mb-4">
+                    The Genome Logic Modeling Project (GLMP) represents <strong>prior work</strong> that demonstrates the first 
+                    successful application of the Programming Framework to biological process visualization. This research establishes 
+                    a novel methodology for transforming complex biochemical processes into structured, interactive visual flowcharts 
+                    using LLM-powered analysis and Mermaid visualization technology.
                 </p>
             </div>
 
-            <div class="grid md:grid-cols-3 gap-6 mt-6">
-                <div class="bg-blue-50 rounded-lg p-6">
-                    <h3 class="text-lg font-semibold text-gray-900 mb-3">📥 Data Ingestion</h3>
-                    <p class="text-sm text-gray-700">
-                        Multi-source acquisition from academic databases (PubMed, arXiv, NASA ADS), literature sources (textbooks, reviews), and educational content (videos, transcripts), with quality assessment and type classification.
-                    </p>
-                </div>
-                
-                <div class="bg-green-50 rounded-lg p-6">
-                    <h3 class="text-lg font-semibold text-gray-900 mb-3">⚙️ Processing & Storage</h3>
-                    <p class="text-sm text-gray-700">
-                        LLM-powered entity extraction and process logic extraction, structured data storage (JSON metadata, Mermaid flowcharts, transcripts), and specialized databases for papers, processes, and media.
-                    </p>
+            <div class="grid md:grid-cols-2 gap-6 mb-6">
+                <div class="bg-white rounded-lg p-6">
+                    <h3 class="text-lg font-semibold text-gray-900 mb-3">🔬 Research Contributions</h3>
+                    <ul class="text-sm text-gray-700 space-y-2">
+                        <li>• <strong>Biological Process Visualization:</strong> 50+ processes mapped across 6 major categories</li>
+                        <li>• <strong>LLM-Powered Analysis:</strong> Automated extraction using Google Gemini 2.0 Flash</li>
+                        <li>• <strong>Interactive Visualization:</strong> Mermaid.js-based dynamic flowchart system</li>
+                        <li>• <strong>Knowledge Engine Integration:</strong> Links to CopernicusAI and Programming Framework</li>
+                    </ul>
                 </div>
                 
-                <div class="bg-purple-50 rounded-lg p-6">
-                    <h3 class="text-lg font-semibold text-gray-900 mb-3">🔍 Query & Output</h3>
-                    <p class="text-sm text-gray-700">
-                        Multiple access interfaces including RAG queries, vector search, knowledge graph visualization, API endpoints, and web interfaces, converging to unified knowledge output.
-                    </p>
+                <div class="bg-white rounded-lg p-6">
+                    <h3 class="text-lg font-semibold text-gray-900 mb-3">⚙️ Technical Achievements</h3>
+                    <ul class="text-sm text-gray-700 space-y-2">
+                        <li>• <strong>Structured Database:</strong> JSON format in Google Cloud Storage</li>
+                        <li>• <strong>Process Coverage:</strong> Central Dogma, Metabolism, Signaling, Proteins, Photosynthesis, DNA Repair</li>
+                        <li>• <strong>Scalable Architecture:</strong> GCS-based storage with web viewer integration</li>
+                        <li>• <strong>Metadata-Rich Format:</strong> Categories, versions, references, source papers</li>
+                    </ul>
                 </div>
             </div>
-        </div>
-    </section>
 
-    <!-- Prior Work: CopernicusAI Research Interface -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
-        <div class="bg-gradient-to-r from-purple-50 to-blue-50 rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-4">Prior Work & Current Status</h2>
-            
-            <div class="bg-white rounded-lg p-6 mb-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-3">Prior Work (2024-2025)</h3>
-                <p class="text-lg text-gray-700 leading-relaxed mb-4">
-                    CopernicusAI is an active research prototype exploring AI-generated audio briefings as an interface for assisted scientific research.
-                </p>
-                <p class="text-gray-700 mb-4">
-                    The system allows any user to generate, refine, and share AI-generated science podcasts based on structured prompts, enabling rapid orientation to a topic, iterative deepening, and personalized research briefings.
-                </p>
-                <p class="text-gray-700 mb-4">
-                    Rather than functioning as a static content platform, CopernicusAI supports collectively generated and shared research artifacts, analogous to community-driven knowledge platforms (e.g., discussion forums), but grounded in scientific sources and metadata-aware workflows.
+            <div class="bg-white rounded-lg p-6">
+                <h3 class="text-lg font-semibold text-gray-900 mb-3">🎯 Position Within CopernicusAI Knowledge Engine</h3>
+                <p class="text-gray-700 mb-3">
+                    GLMP serves as a <strong>specialized application component</strong> of the CopernicusAI Knowledge Engine, 
+                    demonstrating how the Programming Framework can be applied to domain-specific scientific visualization. It integrates with:
                 </p>
-                <div class="bg-blue-50 rounded-lg p-4 mt-4">
-                    <h3 class="font-semibold text-gray-900 mb-2">This work demonstrates technical feasibility for:</h3>
+                <div class="grid md:grid-cols-2 gap-4 text-sm mb-3">
                     <ul class="text-gray-700 space-y-1">
-                        <li>• AI-assisted research briefing and orientation</li>
-                        <li>• Iterative question refinement via conversational interfaces</li>
-                        <li>• Integration of text, audio, and metadata in research workflows</li>
+                        <li>• Programming Framework (meta-tool)</li>
+                        <li>• CopernicusAI (main knowledge engine)</li>
+                        <li>• Research Papers Metadata Database</li>
+                    </ul>
+                    <ul class="text-gray-700 space-y-1">
+                        <li>• Science Video Database</li>
+                        <li>• Multi-modal learning integration</li>
                     </ul>
                 </div>
-            </div>
-            
-            <div class="bg-green-50 border-2 border-green-200 rounded-lg p-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-3">Current Implementation (December 2025)</h3>
-                <p class="text-gray-700 mb-3">
-                    The Research Tools Dashboard is <strong>fully operational</strong> and deployed to Google Cloud Run, providing unified access to all components with interactive knowledge graph visualization, vector search, RAG queries, and content browsing.
-                </p>
-                <p class="text-sm text-gray-600">
-                    See the "Knowledge Engine Ecosystem" section below for details.
+                <p class="text-gray-600 text-sm italic">
+                    This work establishes a proof-of-concept for domain-specific applications of the Programming Framework, 
+                    demonstrating its utility in biological sciences and potential for extension to other scientific disciplines.
                 </p>
             </div>
         </div>
     </section>
 
-    <!-- Mission & Vision -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-4">🎯 Mission & Vision</h2>
-            <p class="text-lg text-gray-700 leading-relaxed mb-4">
-                Inspired by Nicolaus Copernicus who challenged accepted knowledge with evidence and rigorous analysis, 
-                <strong>CopernicusAI</strong> creates collaborative research tools that enable collective participation in 
-                scientific discovery. These platforms are instruments for exploring humanity's collective knowledge—tools for 
-                hypothesis formation, testing, and collaborative research, not just educational content.
-            </p>
-            <p class="text-gray-600">
-                Just as a microscope enables observation of the microscopic world, CopernicusAI tools enable observation and 
-                exploration of humanity's collective knowledge. Subscribers collaborate to prompt, generate, and refine research 
-                content—sharing discoveries publicly or keeping them private. As large language models (LLMs) and AI systems 
-                gain unprecedented knowledge, CopernicusAI provides the infrastructure for human-AI collaborative knowledge 
-                exploration, with evidence-based truth-seeking as our guiding principle.
-            </p>
+    <!-- Quick Stats -->
+    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 -mt-8">
+        <div class="grid md:grid-cols-4 gap-4">
+            <div class="bg-white rounded-lg shadow-lg p-6 text-center">
+                <div class="text-3xl font-bold text-green-600">50+</div>
+                <div class="text-sm text-gray-600">Biological Processes</div>
+            </div>
+            <div class="bg-white rounded-lg shadow-lg p-6 text-center">
+                <div class="text-3xl font-bold text-blue-600">JSON</div>
+                <div class="text-sm text-gray-600">Flowchart Format</div>
+            </div>
+            <div class="bg-white rounded-lg shadow-lg p-6 text-center">
+                <div class="text-3xl font-bold text-purple-600">LLM</div>
+                <div class="text-sm text-gray-600">AI-Powered Analysis</div>
+            </div>
+            <div class="bg-white rounded-lg shadow-lg p-6 text-center">
+                <div class="text-3xl font-bold text-orange-600">Mermaid</div>
+                <div class="text-sm text-gray-600">Visualization Engine</div>
+            </div>
         </div>
     </section>
 
-    <!-- Knowledge Engine Ecosystem -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-gradient-to-r from-purple-50 to-indigo-50 rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6 text-center">🧩 CopernicusAI Knowledge Engine</h2>
-            <p class="text-lg text-gray-700 mb-6 text-center max-w-4xl mx-auto">
-                An integrated ecosystem of research and collaboration tools designed to assist scientists in their workflow, 
-                from research discovery through knowledge synthesis to multi-format content generation. 
-                <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html" 
-                   target="_blank" rel="noopener noreferrer"
-                   class="text-blue-600 hover:underline font-medium">
-                    View Public Project Interface →
-                </a>
-            </p>
-            
-            <div class="grid md:grid-cols-2 lg:grid-cols-3 gap-6 mb-6">
-                <div class="bg-white rounded-lg p-6 card-hover border-2 border-purple-300">
-                    <div class="text-3xl mb-3">🎙️</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">CopernicusAI Podcast Generation</h3>
-                    <p class="text-sm text-gray-600 mb-3">Synthesis & distribution platform for AI-powered research briefing podcast generation</p>
-                    <a href="https://www.copernicusai.fyi" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Visit Website →</a>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6 card-hover">
-                    <div class="text-3xl mb-3">🛠️</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">Programming Framework</h3>
-                    <p class="text-sm text-gray-600 mb-3">Foundational meta-tool for universal process analysis across disciplines</p>
-                    <a href="https://huggingface.co/spaces/garywelz/programming_framework" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Explore →</a>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6 card-hover">
-                    <div class="text-3xl mb-3">🧬</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">Genome Logic Modeling Project</h3>
-                    <p class="text-sm text-gray-600 mb-3">Mermaid markdown format flowcharts modeling 100+ biochemical processes in Yeast and E. Coli</p>
-                    <a href="https://huggingface.co/spaces/garywelz/glmp" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Explore →</a>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6 card-hover">
-                    <div class="text-3xl mb-3">📚</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">Research Paper Database</h3>
-                    <p class="text-sm text-gray-600 mb-3">Core data infrastructure for research paper metadata and citation networks</p>
-                    <a href="https://huggingface.co/spaces/garywelz/metadata_database" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Explore →</a>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6 card-hover">
-                    <div class="text-3xl mb-3">🎬</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">Science Video Database</h3>
-                    <p class="text-sm text-gray-600 mb-3">Multi-modal content with transcript-based search for scientific videos</p>
-                    <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/videos-database-table.html" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Explore →</a>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6 card-hover border-2 border-green-300">
-                    <div class="text-3xl mb-3">🗺️</div>
-                    <h3 class="text-lg font-semibold text-gray-900 mb-2">Research Tools Dashboard</h3>
-                    <p class="text-sm text-gray-600 mb-3">✅ Prototype web interface for testing knowledge graph, vector search, RAG queries, and content browsing</p>
-                    <a href="https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine" target="_blank" rel="noopener noreferrer" class="text-xs text-blue-600 hover:underline">Live System →</a>
+    <!-- What is GLMP -->
+    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
+        <div class="bg-white rounded-xl shadow-lg p-8">
+            <h2 class="text-3xl font-bold text-gray-900 mb-6">🔬 What is GLMP?</h2>
+            <div class="prose max-w-none text-gray-700">
+                <p class="text-lg mb-4">
+                    The Genome Logic Modeling Project is the first specialized application of the 
+                    <a href="https://huggingface.co/spaces/garywelz/programming_framework" class="text-green-600 hover:text-green-700 font-semibold">Programming Framework</a> 
+                    to the domain of biology. It transforms complex biochemical processes into clear, visual flowcharts 
+                    that reveal the step-by-step logic underlying life's molecular machinery.
+                </p>
+                <div class="grid md:grid-cols-2 gap-6 mt-6">
+                    <div class="bg-green-50 rounded-lg p-4">
+                        <h3 class="font-semibold text-gray-900 mb-2">🎯 Purpose</h3>
+                        <p class="text-sm">Break down biological complexity into understandable visual logic, making advanced 
+                        biochemistry accessible to researchers, students, and AI systems.</p>
+                    </div>
+                    <div class="bg-blue-50 rounded-lg p-4">
+                        <h3 class="font-semibold text-gray-900 mb-2">⚙️ How It Works</h3>
+                        <p class="text-sm">LLMs analyze scientific literature to extract process steps, decision points, and 
+                        molecular interactions, then encode them as Mermaid flowcharts stored in JSON.</p>
+                    </div>
                 </div>
             </div>
         </div>
     </section>
 
-    <!-- Key Statistics -->
+    <!-- GLMP Database Table -->
     <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="grid md:grid-cols-2 lg:grid-cols-4 gap-6 mb-12">
-            <div class="bg-white rounded-lg shadow-md p-6 text-center">
-                <div class="stat-number mb-2">23,246</div>
-                <div class="text-gray-600 font-semibold">Research Papers</div>
-                <div class="text-sm text-gray-500 mt-1">Indexed in Knowledge Engine (As of January 2025)</div>
-            </div>
-            <div class="bg-white rounded-lg shadow-md p-6 text-center">
-                <div class="stat-number mb-2">314</div>
-                <div class="text-gray-600 font-semibold">Processes</div>
-                <div class="text-sm text-gray-500 mt-1">Visualized across 6 databases (As of January 2025)</div>
-            </div>
-            <div class="bg-white rounded-lg shadow-md p-6 text-center">
-                <div class="stat-number mb-2">753</div>
-                <div class="text-gray-600 font-semibold">Videos</div>
-                <div class="text-sm text-gray-500 mt-1">Science videos indexed (As of January 2025)</div>
-            </div>
+        <div class="bg-gradient-to-r from-green-50 to-blue-50 rounded-xl p-8">
+            <h2 class="text-3xl font-bold text-gray-900 mb-6">📊 GLMP Database</h2>
             <div class="bg-white rounded-lg shadow-md p-6 text-center">
-                <div class="stat-number mb-2">79</div>
-                <div class="text-gray-600 font-semibold">Podcasts</div>
-                <div class="text-sm text-gray-500 mt-1">Generated across 5 disciplines (As of January 2025)</div>
+                <p class="text-gray-700 mb-6">
+                    Access the interactive GLMP database table with all available biological processes, metadata, and analysis.
+                </p>
+                <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/glmp-database-table.html" 
+                   target="_blank"
+                   class="inline-flex items-center px-8 py-4 border border-transparent text-lg font-medium rounded-md text-white bg-green-600 hover:bg-green-700 transition-colors shadow-lg">
+                    🧬 Open GLMP Database Table
+                </a>
             </div>
         </div>
     </section>
 
-    <!-- Core Platform Capabilities -->
+    <!-- Process Database -->
     <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <h2 class="text-3xl font-bold text-gray-900 mb-8 text-center">🌟 Core Platform Capabilities</h2>
+        <h2 class="text-3xl font-bold text-gray-900 mb-6">📚 Process Database</h2>
         
-        <div class="space-y-8">
-            <!-- AI Podcast Generation -->
-            <div class="bg-white rounded-xl shadow-lg p-8">
-                <div class="flex items-start mb-4">
-                    <span class="text-4xl mr-4">🎙️</span>
-                    <div class="flex-1">
-                        <h3 class="text-2xl font-bold text-gray-900 mb-3">AI-Powered Podcast Generation</h3>
-                        <p class="text-gray-600 mb-4">
-                            Collaborative research platform where subscribers prompt and generate multi-voice AI podcasts 
-                            (5-10 minutes) synthesizing research from multiple academic sources. Subscribers can share their 
-                            podcasts publicly or keep them private. Evidence-based content generation requiring minimum 3 
-                            research sources per episode.
-                        </p>
-                        <div class="grid md:grid-cols-2 gap-4 mt-4">
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Key Features:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>✓ Comprehensive research integration (8+ databases)</li>
-                                    <li>✓ Professional multi-speaker dialogue</li>
-                                    <li>✓ AI-generated scientific visualizations</li>
-                                    <li>✓ RSS feed distribution</li>
-                                    <li>✓ Quality scoring & relevance ranking</li>
-                                    <li>✓ Paradigm shift identification</li>
-                                </ul>
-                            </div>
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Research Integration:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>✓ Real-time discovery from 8+ APIs</li>
-                                    <li>✓ Parallel search across databases</li>
-                                    <li>✓ Automatic citation extraction</li>
-                                    <li>✓ Source validation & verification</li>
-                                    <li>✓ Interdisciplinary connection analysis</li>
-                                </ul>
-                            </div>
-                        </div>
-                    </div>
-                </div>
-            </div>
-
-            <!-- LLM Integration -->
-            <div class="bg-white rounded-xl shadow-lg p-8">
-                <div class="flex items-start mb-4">
-                    <span class="text-4xl mr-4">🤖</span>
-                    <div class="flex-1">
-                        <h3 class="text-2xl font-bold text-gray-900 mb-3">Advanced LLM Integration</h3>
-                        <p class="text-gray-600 mb-4">Multi-model architecture with intelligent model selection:</p>
-                        <div class="grid md:grid-cols-2 gap-4">
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Primary Models:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>• <strong>Google Gemini 3</strong> - Latest research analysis and content generation</li>
-                                    <li>• <strong>OpenAI GPT-4/GPT-3.5</strong> - Content synthesis and quality validation</li>
-                                    <li>• <strong>Anthropic Claude 3</strong> (Sonnet, Haiku) - Alternative reasoning paths</li>
-                                    <li>• <strong>ElevenLabs TTS</strong> - Multi-voice text-to-speech synthesis</li>
-                                </ul>
-                            </div>
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Capabilities:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>• Multi-paper analysis & synthesis</li>
-                                    <li>• Paradigm shift detection</li>
-                                    <li>• Entity extraction (genes, proteins, compounds)</li>
-                                    <li>• Citation tracking & cross-references</li>
-                                    <li>• Content quality scoring</li>
-                                </ul>
-                            </div>
-                        </div>
-                    </div>
-                </div>
+        <div class="grid md:grid-cols-2 lg:grid-cols-3 gap-6">
+            <!-- Central Dogma Processes -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🧬 Central Dogma</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• DNA Replication</li>
+                    <li>• Transcription</li>
+                    <li>• Translation</li>
+                    <li>• RNA Processing</li>
+                    <li>• Post-translational Modifications</li>
+                </ul>
             </div>
 
-            <!-- Research Resources -->
-            <div class="bg-white rounded-xl shadow-lg p-8">
-                <div class="flex items-start mb-4">
-                    <span class="text-4xl mr-4">📊</span>
-                    <div class="flex-1">
-                        <h3 class="text-2xl font-bold text-gray-900 mb-3">Research Resource Access</h3>
-                        <p class="text-gray-600 mb-4">
-                            Comprehensive academic database coverage with <strong>250+ million research papers</strong> accessible 
-                            through integrated APIs.
-                        </p>
-                        <div class="grid md:grid-cols-2 gap-4">
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Academic Databases:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>• PubMed/NCBI (~30+ million papers)</li>
-                                    <li>• arXiv (~2+ million preprints)</li>
-                                    <li>• NASA ADS (~15+ million papers)</li>
-                                    <li>• Zenodo (100K+ datasets)</li>
-                                    <li>• bioRxiv/medRxiv (preprints)</li>
-                                    <li>• CORE (~200+ million papers)</li>
-                                    <li>• Google Scholar (comprehensive)</li>
-                                    <li>• News API (current events)</li>
-                                    <li>• YouTube Data API (academic videos)</li>
-                                </ul>
-                            </div>
-                        </div>
-                    </div>
-                </div>
+            <!-- Metabolic Pathways -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">⚡ Metabolic Pathways</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• Glycolysis</li>
+                    <li>• Krebs Cycle (TCA)</li>
+                    <li>• Oxidative Phosphorylation</li>
+                    <li>• Gluconeogenesis</li>
+                    <li>• Pentose Phosphate Pathway</li>
+                </ul>
             </div>
 
-            <!-- Audio and Video Podcast Production -->
-            <div class="bg-white rounded-xl shadow-lg p-8">
-                <div class="flex items-start mb-4">
-                    <span class="text-4xl mr-4">🎙️</span>
-                    <div class="flex-1">
-                        <h3 class="text-2xl font-bold text-gray-900 mb-3">Audio and Video Podcast Production</h3>
-                        <p class="text-gray-600 mb-4">
-                            <strong>Operating Audio Podcast System:</strong> Full production and distribution platform for subscriber-generated 
-                            podcasts. Users can prompt, generate, publish, and distribute audio podcasts with RSS feed support for 
-                            Spotify, Apple Podcasts, and Google Podcasts.
-                        </p>
-                        <div class="bg-green-50 rounded-lg p-4 mb-4">
-                            <h4 class="font-semibold text-gray-800 mb-2">Current Audio Capabilities (Operational):</h4>
-                            <ul class="text-sm text-gray-700 space-y-1">
-                                <li>✓ Multi-voice AI podcast generation</li>
-                                <li>✓ Research-driven content creation</li>
-                                <li>✓ RSS feed distribution</li>
-                                <li>✓ Public and private podcast options</li>
-                                <li>✓ Professional audio quality</li>
-                            </ul>
-                        </div>
-                        <div class="bg-blue-50 rounded-lg p-4 mt-4">
-                            <h4 class="font-semibold text-gray-800 mb-2">Video Production (Future - Phase 2+):</h4>
-                            <p class="text-sm text-gray-700 mb-2">Advanced video features planned for future development:</p>
-                            <ul class="text-sm text-gray-700 space-y-2">
-                                <li>• <strong>Visual Content Integration:</strong> Automated extraction from papers, web scraping, JSON database integration</li>
-                                <li>• <strong>Dynamic Visualizations:</strong> Scientific animations, real-time charts, LaTeX rendering</li>
-                                <li>• <strong>External Video Quoting:</strong> YouTube segment extraction with attribution & fair use compliance</li>
-                                <li>• <strong>Advanced Composition:</strong> Multi-layer video, auto subtitles, text overlays, professional transitions</li>
-                            </ul>
-                            <p class="text-xs text-gray-600 mt-2">
-                                See: <a href="https://huggingface.co/spaces/garywelz/sciencevideodb" class="text-blue-600 hover:underline">Science Video Database</a> - Companion project for research video content management.
-                            </p>
-                        </div>
-                    </div>
-                </div>
+            <!-- Cell Signaling -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">📡 Cell Signaling</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• MAPK Pathway</li>
+                    <li>• PI3K/AKT Pathway</li>
+                    <li>• Wnt Signaling</li>
+                    <li>• Notch Pathway</li>
+                    <li>• JAK-STAT Pathway</li>
+                </ul>
             </div>
 
-            <!-- Research Papers Metadata Database -->
-            <div class="bg-white rounded-xl shadow-lg p-8">
-                <div class="flex items-start mb-4">
-                    <span class="text-4xl mr-4">📚</span>
-                    <div class="flex-1">
-                        <h3 class="text-2xl font-bold text-gray-900 mb-3">Research Papers Metadata Database (Phase 2)</h3>
-                        <p class="text-gray-600 mb-4">
-                            A centralized <strong>metadata repository</strong> (not a file archive) providing structured JSON objects 
-                            with AI-powered preprocessing.
-                        </p>
-                        <div class="grid md:grid-cols-2 gap-4">
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">Structured JSON Objects:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>• DOI, arXiv ID, publication info</li>
-                                    <li>• Abstracts & key findings</li>
-                                    <li>• Extracted entities (genes, proteins, compounds, equations)</li>
-                                    <li>• Citation networks & cross-references</li>
-                                    <li>• Paradigm shift indicators</li>
-                                    <li>• Quality scores & relevance metrics</li>
-                                </ul>
-                            </div>
-                            <div>
-                                <h4 class="font-semibold text-gray-800 mb-2">AI-Powered Preprocessing:</h4>
-                                <ul class="text-sm text-gray-600 space-y-1">
-                                    <li>• LLM-based entity extraction</li>
-                                    <li>• Automatic categorization</li>
-                                    <li>• Keyword extraction & semantic tagging</li>
-                                    <li>• Citation tracking & mapping</li>
-                                    <li>• Quality assessment</li>
-                                    <li>• RESTful API access</li>
-                                </ul>
-                            </div>
-                        </div>
-                    </div>
-                </div>
+            <!-- Protein Processes -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🔄 Protein Processes</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• Protein Folding</li>
+                    <li>• Ubiquitination</li>
+                    <li>• Autophagy</li>
+                    <li>• Proteasome Degradation</li>
+                    <li>• Chaperone Systems</li>
+                </ul>
             </div>
-        </div>
-    </section>
 
-    <!-- Methodological Details -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">🔬 Methodology & System Design</h2>
-            
-            <div class="grid md:grid-cols-2 gap-6 mb-6">
-                <div class="bg-blue-50 rounded-lg p-6">
-                    <h3 class="text-xl font-semibold text-gray-900 mb-4">Multi-Source Validation Process</h3>
-                    <p class="text-gray-700 mb-3">
-                        The system requires a <strong>minimum of 3 research sources</strong> per podcast episode. Each source is:
-                    </p>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• Retrieved from authoritative academic databases (PubMed, arXiv, NASA ADS, etc.)</li>
-                        <li>• Validated for authenticity and publication status</li>
-                        <li>• Scored for quality and relevance to the research topic</li>
-                        <li>• Cross-referenced to verify consistency and eliminate conflicting information</li>
-                        <li>• Processed through parallel API queries for comprehensive coverage</li>
-                    </ul>
-                </div>
-                
-                <div class="bg-green-50 rounded-lg p-6">
-                    <h3 class="text-xl font-semibold text-gray-900 mb-4">Quality Assurance Mechanisms</h3>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• <strong>Source Verification:</strong> Automated checking of DOI, arXiv IDs, and publication metadata</li>
-                        <li>• <strong>Relevance Scoring:</strong> LLM-based assessment of paper relevance to query</li>
-                        <li>• <strong>Paradigm Shift Detection:</strong> Identification of revolutionary vs. incremental research</li>
-                        <li>• <strong>Citation Extraction:</strong> Automatic extraction and formatting of citations</li>
-                        <li>• <strong>Content Validation:</strong> Multi-model verification (Gemini, GPT-4, Claude) for accuracy</li>
-                    </ul>
-                </div>
-            </div>
-            
-            <div class="bg-purple-50 rounded-lg p-6 mb-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Citation Extraction & Verification</h3>
-                <p class="text-gray-700 mb-3">
-                    The system automatically extracts and formats citations from research papers:
-                </p>
-                <ul class="text-sm text-gray-700 space-y-2">
-                    <li>• DOI resolution and metadata enrichment</li>
-                    <li>• arXiv ID parsing and preprint identification</li>
-                    <li>• Author, title, and publication information extraction</li>
-                    <li>• Cross-reference linking between related papers</li>
-                    <li>• Citation network analysis for relationship mapping</li>
+            <!-- Photosynthesis -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🌱 Photosynthesis</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• Light Reactions</li>
+                    <li>• Calvin Cycle</li>
+                    <li>• C4 Pathway</li>
+                    <li>• CAM Photosynthesis</li>
+                    <li>• Photorespiration</li>
                 </ul>
             </div>
-            
-            <div class="bg-orange-50 rounded-lg p-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Paradigm Shift Detection Implementation</h3>
-                <p class="text-gray-700 mb-3">
-                    The system uses LLM analysis to identify paradigm-shifting research by:
-                </p>
-                <ul class="text-sm text-gray-700 space-y-2">
-                    <li>• Analyzing citation patterns and impact metrics</li>
-                    <li>• Detecting novel methodologies or breakthrough discoveries</li>
-                    <li>• Comparing against established knowledge frameworks</li>
-                    <li>• Identifying interdisciplinary connections and cross-domain insights</li>
-                    <li>• Flagging research that challenges existing paradigms</li>
+
+            <!-- DNA Repair -->
+            <div class="bg-white rounded-lg shadow-md p-6 process-card card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🔧 DNA Repair</h3>
+                <ul class="space-y-2 text-sm text-gray-600">
+                    <li>• Base Excision Repair</li>
+                    <li>• Nucleotide Excision Repair</li>
+                    <li>• Mismatch Repair</li>
+                    <li>• Double-strand Break Repair</li>
+                    <li>• Direct Repair</li>
                 </ul>
             </div>
         </div>
-    </section>
 
-    <!-- Technology Stack -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">⚙️ Technology Stack</h2>
-            
-            <div class="grid md:grid-cols-3 gap-6 mb-6">
-                <div>
-                    <h3 class="text-lg font-semibold text-gray-800 mb-3">AI & Machine Learning</h3>
-                    <ul class="text-sm text-gray-600 space-y-1">
-                        <li>• Google Gemini 3</li>
-                        <li>• Google Vertex AI (model orchestration)</li>
-                        <li>• OpenAI GPT-4/GPT-3.5</li>
-                        <li>• Anthropic Claude 3</li>
-                        <li>• ElevenLabs TTS</li>
-                        <li>• DALL-E 3</li>
-                        <li>• Cloud Vision API</li>
-                        <li>• Video Intelligence API</li>
-                    </ul>
-                </div>
-                
-                <div>
-                    <h3 class="text-lg font-semibold text-gray-800 mb-3">Backend Infrastructure</h3>
-                    <ul class="text-sm text-gray-600 space-y-1">
-                        <li>• FastAPI (Python)</li>
-                        <li>• Google Cloud Run</li>
-                        <li>• Firestore (NoSQL)</li>
-                        <li>• Cloud Storage</li>
-                        <li>• Cloud Functions</li>
-                        <li>• Cloud Tasks</li>
-                        <li>• Secret Manager</li>
-                    </ul>
-                </div>
-                
-                <div>
-                    <h3 class="text-lg font-semibold text-gray-800 mb-3">Frontend</h3>
-                    <ul class="text-sm text-gray-600 space-y-1">
-                        <li>• Next.js 15.5.7</li>
-                        <li>• Alpine.js</li>
-                        <li>• Tailwind CSS</li>
-                        <li>• Vercel</li>
-                    </ul>
-                </div>
-            </div>
+        <div class="mt-6 text-center">
+            <a href="#archive" class="text-green-600 hover:text-green-700 font-semibold">
+                📦 View Archived Processes (v1.0) →
+            </a>
         </div>
     </section>
 
-    <!-- Limitations & Future Work -->
+    <!-- How to Use -->
     <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">🔍 Limitations & Future Directions</h2>
+        <div class="bg-gradient-to-r from-blue-50 to-purple-50 rounded-xl p-8">
+            <h2 class="text-3xl font-bold text-gray-900 mb-6">🚀 How to Use GLMP</h2>
             
-            <div class="grid md:grid-cols-2 gap-6">
-                <div class="bg-yellow-50 rounded-lg p-6 border-l-4 border-yellow-400">
-                    <h3 class="text-xl font-semibold text-gray-900 mb-4">Current Limitations</h3>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• <strong>Discipline Coverage:</strong> Currently indexing 23,246 papers across multiple disciplines; expansion to additional disciplines in progress</li>
-                        <li>• <strong>Source Bias:</strong> Coverage depends on database API availability and open access policies</li>
-                        <li>• <strong>LLM Accuracy:</strong> Content generation relies on LLM accuracy; multi-source validation mitigates but doesn't eliminate errors</li>
-                        <li>• <strong>Real-Time Updates:</strong> Knowledge graph updates require manual or scheduled processing cycles</li>
-                        <li>• <strong>Language:</strong> Currently optimized for English-language research papers</li>
-                    </ul>
+            <div class="grid md:grid-cols-3 gap-6">
+                <div class="bg-white rounded-lg p-6">
+                    <div class="text-3xl mb-3">1️⃣</div>
+                    <h3 class="font-semibold text-gray-900 mb-2">Select Process</h3>
+                    <p class="text-sm text-gray-600">Choose a biological process from the viewer above or browse the database</p>
                 </div>
-                
-                <div class="bg-blue-50 rounded-lg p-6 border-l-4 border-blue-400">
-                    <h3 class="text-xl font-semibold text-gray-900 mb-4">Future Development</h3>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• <strong>Multi-Discipline Expansion:</strong> Expanding knowledge graph to Biology, Chemistry, Physics, Computer Science</li>
-                        <li>• <strong>Process Databases:</strong> Creating comprehensive flowchart databases for all 5 disciplines (~50 processes each)</li>
-                        <li>• <strong>Advanced Video Features:</strong> Dynamic visualizations, animations, and multi-layer composition</li>
-                        <li>• <strong>Multi-Language Support:</strong> Extending to non-English research papers</li>
-                        <li>• <strong>Enhanced Validation:</strong> Peer review mechanisms and user feedback integration</li>
-                        <li>• <strong>Real-Time Updates:</strong> Automated continuous knowledge graph updates</li>
-                    </ul>
+
+                <div class="bg-white rounded-lg p-6">
+                    <div class="text-3xl mb-3">2️⃣</div>
+                    <h3 class="font-semibold text-gray-900 mb-2">View Flowchart</h3>
+                    <p class="text-sm text-gray-600">Explore the interactive Mermaid visualization showing each step and decision point</p>
+                </div>
+
+                <div class="bg-white rounded-lg p-6">
+                    <div class="text-3xl mb-3">3️⃣</div>
+                    <h3 class="font-semibold text-gray-900 mb-2">Learn & Integrate</h3>
+                    <p class="text-sm text-gray-600">Use for education, research, or integrate with CopernicusAI podcasts</p>
                 </div>
             </div>
         </div>
     </section>
 
-    <!-- Research & Collaborative Tools -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-gradient-to-r from-green-50 to-blue-50 rounded-xl p-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">🔬 Collaborative Research Tools</h2>
-            
-            <div class="grid md:grid-cols-2 gap-6 mb-6">
-                <div>
-                    <h3 class="text-xl font-semibold text-gray-800 mb-3">Collaborative Research Tools</h3>
-                    <p class="text-gray-700 mb-3">
-                        These platforms enable collective participation and collaboration across diverse user communities:
-                    </p>
-                    <ul class="text-gray-700 space-y-2">
-                        <li>• <strong>Researchers</strong> - Tools for hypothesis formation and testing, cross-disciplinary synthesis</li>
-                        <li>• <strong>Collaborators</strong> - Collective knowledge exploration and refinement</li>
-                        <li>• <strong>Subscribers</strong> - Prompt, generate, and share podcasts (public or private)</li>
-                        <li>• <strong>Community</strong> - User suggestions, comments, and collaborative flowchart improvement (GLMP)</li>
-                    </ul>
-                    <p class="text-gray-600 mt-4 italic">
-                        Like a microscope enables observation of the microscopic world, these tools enable observation and 
-                        exploration of humanity's collective knowledge.
-                    </p>
-                </div>
-                
-                <div>
-                    <h3 class="text-xl font-semibold text-gray-800 mb-3">Key Innovations</h3>
-                    <ul class="text-gray-700 space-y-2">
-                        <li>• Multi-source validation (min 3 sources)</li>
-                        <li>• Evidence-based generation</li>
-                        <li>• Paradigm shift detection</li>
-                        <li>• Interdisciplinary connections</li>
-                        <li>• Multiple expertise levels</li>
-                        <li>• Full citation tracking</li>
-                    </ul>
-                </div>
-            </div>
+    <!-- Archive Link -->
+    <section id="archive" class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
+        <div class="bg-gray-100 rounded-lg p-6 text-center">
+            <h3 class="text-xl font-semibold text-gray-900 mb-2">📦 Archived Versions</h3>
+            <p class="text-gray-600 mb-4">Earlier versions of GLMP processes and experimental visualizations</p>
+            <a href="/archive.html" class="inline-block bg-green-600 text-white px-6 py-2 rounded-lg hover:bg-green-700 transition">
+                View Archive
+            </a>
         </div>
     </section>
 
-    <!-- Prior Work & Research Contributions -->
+    <!-- Related Projects -->
     <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-gradient-to-r from-purple-50 to-blue-50 rounded-xl shadow-lg p-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">📚 Prior Work & Research Contributions</h2>
-            
-            <div class="bg-white rounded-lg p-6 mb-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Overview</h3>
-                <p class="text-gray-700 mb-4">
-                    This platform represents <strong>prior work</strong> that demonstrates foundational research and development 
-                    achievements in AI-powered scientific knowledge synthesis, collaborative research tools, and multi-modal content 
-                    generation. These contributions establish the technical foundation and proof-of-concept for the broader 
-                    <strong>CopernicusAI Knowledge Engine</strong> initiative.
-                </p>
-            </div>
-
-            <div class="grid md:grid-cols-2 gap-6 mb-6">
-                <div class="bg-white rounded-lg p-6">
-                    <h3 class="text-lg font-semibold text-gray-900 mb-3">🔬 Research Contributions</h3>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• <strong>AI-Powered Research Synthesis:</strong> Production system for multi-source research synthesis using LLMs</li>
-                        <li>• <strong>Multi-Model Architecture:</strong> Intelligent model selection with Gemini 3, GPT-4, Claude 3</li>
-                        <li>• <strong>Collaborative Platform:</strong> Subscriber-driven content generation with public/private sharing</li>
-                        <li>• <strong>Knowledge Engine Integration:</strong> Architecture for Research Papers DB, Video DB, GLMP, Framework</li>
-                    </ul>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6">
-                    <h3 class="text-lg font-semibold text-gray-900 mb-3">⚙️ Technical Achievements</h3>
-                    <ul class="text-sm text-gray-700 space-y-2">
-                        <li>• <strong>250+ Million Papers:</strong> Accessible via 8+ integrated academic databases</li>
-                        <li>• <strong>79 Episodes:</strong> Generated across 5 scientific disciplines</li>
-                        <li>• <strong>Production Deployment:</strong> Live platform with operational API and RSS distribution</li>
-                        <li>• <strong>Scalable Architecture:</strong> Serverless microservices on Google Cloud</li>
-                    </ul>
-                </div>
-            </div>
-
-            <div class="bg-white rounded-lg p-6 mb-6">
-                <h3 class="text-lg font-semibold text-gray-900 mb-3">🎯 Position Within CopernicusAI Knowledge Engine</h3>
-                <p class="text-gray-700 mb-3">
-                    This platform serves as the <strong>core synthesis and distribution component</strong> of the CopernicusAI Knowledge Engine. 
-                    The Knowledge Engine is an integrated ecosystem of research and collaboration tools that work together to assist scientists 
-                    in their workflow, from research discovery through knowledge synthesis to multi-format content generation.
+        <h2 class="text-3xl font-bold text-gray-900 mb-6 text-center">🔗 Related Projects</h2>
+        
+        <div class="grid md:grid-cols-2 gap-6">
+            <div class="bg-white rounded-lg shadow-md p-6 card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🛠️ Programming Framework</h3>
+                <p class="text-gray-600 mb-4">
+                    The meta-tool that powers GLMP. A universal method for process analysis across any discipline.
                 </p>
-                <div class="bg-blue-50 rounded-lg p-4 mb-3">
-                    <h4 class="font-semibold text-gray-900 mb-2">Current Components:</h4>
-                    <div class="grid md:grid-cols-2 gap-4 text-sm">
-                        <ul class="text-gray-700 space-y-1">
-                            <li>1. <strong>CopernicusAI</strong> (This platform) - Core synthesis & distribution</li>
-                            <li>2. <strong>Programming Framework</strong> - Foundational meta-tool</li>
-                            <li>3. <strong>GLMP</strong> - Biological process visualization</li>
-                        </ul>
-                        <ul class="text-gray-700 space-y-1">
-                            <li>4. <strong>Research Paper Metadata Database</strong> - Data infrastructure</li>
-                            <li>5. <strong>Science Video Database</strong> - Multi-modal content</li>
-                        </ul>
-                    </div>
-                </div>
-                <div class="bg-purple-50 rounded-lg p-4">
-                    <h4 class="font-semibold text-gray-900 mb-2">Future Development:</h4>
-                    <p class="text-gray-700 text-sm">
-                        The Knowledge Engine is designed to grow and evolve. Additional tools, databases, and collaboration components 
-                        will be added as the project develops, expanding capabilities for AI-assisted scientific research and knowledge discovery.
-                    </p>
-                </div>
+                <a href="https://huggingface.co/spaces/garywelz/programming_framework" 
+                   class="text-green-600 hover:text-green-700 font-semibold"
+                   target="_blank" rel="noopener noreferrer">
+                    Explore Framework →
+                </a>
             </div>
 
-            <div class="bg-blue-50 rounded-lg p-6">
-                <h3 class="text-lg font-semibold text-gray-900 mb-3">📖 Citation Information</h3>
-                <p class="text-sm text-gray-700 mb-3">
-                    <strong>For Grant Proposals (NSF/DOE):</strong>
+            <div class="bg-white rounded-lg shadow-md p-6 card-hover">
+                <h3 class="text-xl font-semibold text-gray-900 mb-3">🔬 CopernicusAI</h3>
+                <p class="text-gray-600 mb-4">
+                    Knowledge engine that integrates GLMP visualizations with AI-generated scientific podcasts.
                 </p>
-                <div class="bg-white rounded p-4 font-mono text-sm text-gray-800 mb-4">
-                    <p class="mb-2">Welz, G. (2025). CopernicusAI: Knowledge Engine for Scientific Discovery.</p>
-                    <p class="mb-2">Hugging Face Space. https://huggingface.co/spaces/garywelz/copernicusai</p>
-                    <p>Live Platform: https://www.copernicusai.fyi</p>
-                </div>
-                <div class="bg-white rounded p-4 mb-4">
-                    <p class="text-sm font-semibold text-gray-700 mb-2">BibTeX Format:</p>
-                    <pre class="bg-gray-900 text-green-400 p-3 rounded text-xs overflow-x-auto"><code>@misc{welz2025copernicusai,
-  title={CopernicusAI: Knowledge Engine for Scientific Discovery},
-  author={Welz, Gary},
-  year={2025},
-  url={https://huggingface.co/spaces/garywelz/copernicusai},
-  note={Hugging Face Space, Live Platform: https://www.copernicusai.fyi}
-}</code></pre>
-                </div>
-            </div>
-        </div>
-    </section>
-
-    <!-- Data Availability Statement -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8 mb-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">📊 Data Availability Statement</h2>
-            
-            <div class="bg-blue-50 rounded-lg p-6 mb-4">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Platform Access</h3>
-                <ul class="text-gray-700 space-y-2">
-                    <li>• <strong>Live Platform:</strong> <a href="https://www.copernicusai.fyi" target="_blank" class="text-blue-600 hover:underline">https://www.copernicusai.fyi</a> (opens in new tab)</li>
-                    <li>• <strong>Public Project Interface:</strong> <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html" target="_blank" class="text-blue-600 hover:underline">https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html</a> (opens in new tab)</li>
-                    <li>• <strong>Research Tools Dashboard:</strong> <a href="https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine" target="_blank" class="text-blue-600 hover:underline">https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine</a> (opens in new tab)</li>
-                    <li>• <strong>API Base URL:</strong> <code class="bg-gray-100 px-2 py-1 rounded">https://copernicus-podcast-api-phzp4ie2sq-uc.a.run.app</code></li>
-                    <li>• <strong>RSS Feed:</strong> <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/feeds/copernicus-mvp-rss-feed.xml" target="_blank" class="text-blue-600 hover:underline">Available for public access</a> (opens in new tab)</li>
-                </ul>
-            </div>
-            
-            <div class="bg-green-50 rounded-lg p-6 mb-4">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Data & Code Availability</h3>
-                <ul class="text-gray-700 space-y-2">
-                    <li>• <strong>Hugging Face Spaces:</strong> All components accessible at <a href="https://huggingface.co/garywelz" target="_blank" class="text-blue-600 hover:underline">https://huggingface.co/garywelz</a> (opens in new tab)</li>
-                    <li>• <strong>Process Flowcharts (GLMP):</strong> JSON files stored in Google Cloud Storage, accessible via <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/glmp-database-table.html" target="_blank" class="text-blue-600 hover:underline">GLMP Database Table</a> (opens in new tab)</li>
-                    <li>• <strong>Research Paper Metadata:</strong> 23,246 indexed papers with metadata accessible through Research Tools Dashboard</li>
-                    <li>• <strong>API Documentation:</strong> RESTful API endpoints available for programmatic access (see API Documentation section)</li>
-                </ul>
-            </div>
-            
-            <div class="bg-purple-50 rounded-lg p-6">
-                <h3 class="text-xl font-semibold text-gray-900 mb-4">Reproducibility Information</h3>
-                <ul class="text-gray-700 space-y-2">
-                    <li>• <strong>Technology Stack:</strong> All technologies and versions documented in Technology Stack section</li>
-                    <li>• <strong>LLM Models:</strong> Google Gemini 3, OpenAI GPT-4/GPT-3.5, Anthropic Claude 3 (versions specified in documentation)</li>
-                    <li>• <strong>Source Citations:</strong> All podcast episodes include full citations to source papers</li>
-                    <li>• <strong>Metadata:</strong> Complete metadata for all generated content available through API</li>
-                    <li>• <strong>License:</strong> MIT License - see license information in space metadata</li>
-                </ul>
+                <a href="https://www.copernicusai.fyi" 
+                   class="text-green-600 hover:text-green-700 font-semibold"
+                   target="_blank" rel="noopener noreferrer">
+                    Visit CopernicusAI →
+                </a>
             </div>
         </div>
     </section>
@@ -744,243 +326,17 @@
             <h2 class="text-3xl font-bold text-gray-900 mb-6">How to Cite This Work</h2>
             <div class="bg-gray-50 rounded-lg p-6 mb-4">
                 <p class="text-gray-800 font-mono text-lg leading-relaxed mb-4">
-                    Welz, G. (2024–2025). <em>CopernicusAI: AI-Generated Audio Briefings as a Research Interface</em>.<br>
-                    Hugging Face Spaces. https://huggingface.co/spaces/garywelz/copernicusai
+                    Welz, G. (2024–2025). <em>Genome Logic Modeling Project (GLMP)</em>.<br>
+                    Hugging Face Spaces. https://huggingface.co/spaces/garywelz/glmp
                 </p>
-                
-                <div class="border-t border-gray-300 pt-4 mt-4">
-                    <p class="text-sm font-semibold text-gray-700 mb-2">BibTeX Format:</p>
-                    <pre class="bg-gray-800 text-green-400 p-4 rounded text-sm overflow-x-auto"><code>@misc{welz2025copernicusai,
-  title={CopernicusAI: AI-Generated Audio Briefings as a Research Interface},
-  author={Welz, Gary},
-  year={2024--2025},
-  url={https://huggingface.co/spaces/garywelz/copernicusai},
-  note={Hugging Face Space}
-}</code></pre>
-                </div>
             </div>
-        </div>
-    </section>
-
-    <!-- Grant Support & Collaboration -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-white rounded-xl shadow-lg p-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6">🌐 Grant Support & Collaboration</h2>
-            
-            <div class="mb-6">
-                <h3 class="text-xl font-semibold text-gray-800 mb-3">Grant Applications Supported</h3>
-                <p class="text-gray-700 mb-4">
-                    This platform is designed to support grant applications to:
+            <div class="bg-green-50 rounded-lg p-4">
+                <p class="text-gray-700 mb-2">
+                    This project serves as a testbed for integrating AI systems into scientific reasoning pipelines, enabling both human and AI agents to analyze, compare, and extend biological knowledge structures.
+                </p>
+                <p class="text-gray-700 font-semibold">
+                    GLMP is designed as infrastructure for AI-assisted science, not as a static visualization collection.
                 </p>
-                <div class="grid md:grid-cols-3 gap-4">
-                    <div class="bg-blue-50 rounded-lg p-4">
-                        <h4 class="font-semibold text-gray-800 mb-2">NSF</h4>
-                        <p class="text-sm text-gray-600">National Science Foundation - Science education and research infrastructure</p>
-                    </div>
-                    <div class="bg-green-50 rounded-lg p-4">
-                        <h4 class="font-semibold text-gray-800 mb-2">DOE</h4>
-                        <p class="text-sm text-gray-600">Department of Energy - Scientific computing and data science</p>
-                    </div>
-                    <div class="bg-purple-50 rounded-lg p-4">
-                        <h4 class="font-semibold text-gray-800 mb-2">SAIR Foundation</h4>
-                        <p class="text-sm text-gray-600">AI research and development initiatives</p>
-                    </div>
-                </div>
-            </div>
-            
-            <div>
-                <h3 class="text-xl font-semibold text-gray-800 mb-3">Collaboration Opportunities</h3>
-                <ul class="text-gray-700 space-y-2">
-                    <li>• Integration with academic institutions</li>
-                    <li>• Partnership with research organizations</li>
-                    <li>• Open data initiatives</li>
-                    <li>• Educational program development</li>
-                </ul>
-            </div>
-        </div>
-    </section>
-
-    <!-- Links & Resources -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
-        <div class="bg-gradient-to-r from-blue-50 to-purple-50 rounded-xl p-8">
-            <h2 class="text-3xl font-bold text-gray-900 mb-6 text-center">🔗 Live Platform & Resources</h2>
-            
-            <div class="grid md:grid-cols-2 gap-6">
-                <div class="bg-white rounded-lg p-6">
-                    <h3 class="text-xl font-semibold text-gray-800 mb-4">🌐 Production Deployment</h3>
-                    <ul class="space-y-2">
-                        <li>
-                            <a href="https://www.copernicusai.fyi" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                🏠 Homepage - Browse Podcasts (opens in new tab)
-                            </a>
-                        </li>
-                        <li>
-                            <a href="https://www.copernicusai.fyi/subscriber-dashboard.html" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                📊 Creator Dashboard (opens in new tab)
-                            </a>
-                        </li>
-                        <li>
-                            <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/feeds/copernicus-mvp-rss-feed.xml" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                📡 RSS Feed (opens in new tab)
-                            </a>
-                        </li>
-                    </ul>
-                </div>
-                
-                <div class="bg-white rounded-lg p-6">
-                    <h3 class="text-xl font-semibold text-gray-800 mb-4">🧩 Knowledge Engine Components</h3>
-                    <p class="text-sm text-gray-600 mb-4">
-                        The CopernicusAI Knowledge Engine is an integrated ecosystem of research and collaboration tools. 
-                        The <strong>Research Tools Dashboard is now fully operational</strong> (December 2025) with a working web interface providing unified access to all components.
-                    </p>
-                    <div class="bg-green-50 rounded-lg p-4 mb-4">
-                        <h4 class="font-semibold text-gray-800 mb-2">✅ Research Tools Dashboard (Implemented)</h4>
-                        <p class="text-sm text-gray-700 mb-2">
-                            Fully operational web interface with knowledge graph visualization (23,246 papers), vector search, RAG queries, and content browsing.
-                        </p>
-                        <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/copernicusai-public-reviewer.html" 
-                           target="_blank" rel="noopener noreferrer"
-                           class="text-blue-600 hover:underline text-sm font-medium">
-                            Public Project Interface → (opens in new tab)
-                        </a>
-                        <br>
-                        <a href="https://copernicus-frontend-phzp4ie2sq-uc.a.run.app/knowledge-engine" 
-                           target="_blank" rel="noopener noreferrer"
-                           class="text-blue-600 hover:underline text-sm font-medium">
-                            Research Tools Dashboard → (opens in new tab)
-                        </a>
-                    </div>
-                    <ul class="space-y-3">
-                        <li>
-                            <a href="https://huggingface.co/spaces/garywelz/programming_framework" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                🛠️ Programming Framework (opens in new tab)
-                            </a>
-                            <p class="text-sm text-gray-600 mt-1 ml-6">
-                                Foundational meta-tool for universal process analysis across any discipline
-                            </p>
-                        </li>
-                        <li>
-                            <a href="https://huggingface.co/spaces/garywelz/glmp" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                🧬 GLMP - Genome Logic Modeling Project (opens in new tab)
-                            </a>
-                            <p class="text-sm text-gray-600 mt-1 ml-6">
-                                First application of Programming Framework to biology - 50+ biological processes visualized
-                            </p>
-                        </li>
-                        <li>
-                            <a href="https://huggingface.co/spaces/garywelz/metadata_database" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                📚 Research Paper Metadata Database (opens in new tab)
-                            </a>
-                            <p class="text-sm text-gray-600 mt-1 ml-6">
-                                Core data infrastructure for structured research paper metadata and citation networks
-                            </p>
-                        </li>
-                        <li>
-                            <a href="https://huggingface.co/spaces/garywelz/sciencevideodb" target="_blank" rel="noopener noreferrer"
-                               class="text-blue-600 hover:text-blue-800 font-medium">
-                                🎬 Science Video Database (opens in new tab)
-                            </a>
-                            <p class="text-sm text-gray-600 mt-1 ml-6">
-                                Multi-modal content component with transcript-based search for scientific videos
-                            </p>
-                        </li>
-                    </ul>
-                </div>
-            </div>
-        </div>
-    </section>
-
-    <!-- API Endpoints -->
-    <section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        <div class="bg-gray-900 text-white rounded-xl p-8">
-            <h2 class="text-3xl font-bold mb-6">🔌 API Documentation</h2>
-            <p class="text-gray-300 mb-6">Base URL: <code class="bg-gray-800 px-2 py-1 rounded">https://copernicus-podcast-api-phzp4ie2sq-uc.a.run.app</code></p>
-            
-            <div class="grid md:grid-cols-3 gap-4 text-sm mb-8">
-                <div>
-                    <h4 class="font-semibold text-blue-300 mb-2">Podcast Generation</h4>
-                    <ul class="space-y-1 text-gray-400">
-                        <li>POST /generate-podcast-with-subscriber</li>
-                        <li>GET /api/subscribers/podcasts/{id}</li>
-                        <li>POST /api/subscribers/podcasts/submit-to-rss</li>
-                    </ul>
-                </div>
-                
-                <div>
-                    <h4 class="font-semibold text-blue-300 mb-2">Research Endpoints</h4>
-                    <ul class="space-y-1 text-gray-400">
-                        <li>POST /api/papers/upload</li>
-                        <li>GET /api/papers/{paper_id}</li>
-                        <li>POST /api/papers/query</li>
-                        <li>POST /api/papers/{id}/link-podcast/{id}</li>
-                    </ul>
-                </div>
-                
-                <div>
-                    <h4 class="font-semibold text-blue-300 mb-2">Admin Endpoints</h4>
-                    <ul class="space-y-1 text-gray-400">
-                        <li>GET /api/admin/subscribers</li>
-                        <li>POST /api/admin/podcasts/fix-missing-titles</li>
-                        <li>GET /api/admin/podcasts/catalog</li>
-                    </ul>
-                </div>
-            </div>
-
-            <div class="border-t border-gray-700 pt-6 mt-6">
-                <h3 class="text-xl font-semibold text-blue-300 mb-4">📝 Example Request</h3>
-                <div class="bg-gray-800 rounded-lg p-4 mb-4">
-                    <p class="text-gray-400 text-xs mb-2">POST /api/papers/query</p>
-                    <pre class="text-green-400 text-xs overflow-x-auto"><code>{
-  "discipline": "biology",
-  "keywords": ["DNA replication", "cell cycle"],
-  "date_range": {
-    "start": "2020-01-01",
-    "end": "2025-01-01"
-  },
-  "limit": 10
-}</code></pre>
-                </div>
-                
-                <h3 class="text-xl font-semibold text-blue-300 mb-4 mt-6">📤 Example Response</h3>
-                <div class="bg-gray-800 rounded-lg p-4 mb-4">
-                    <pre class="text-green-400 text-xs overflow-x-auto"><code>{
-  "status": "success",
-  "count": 10,
-  "papers": [
-    {
-      "id": "pmid_12345678",
-      "title": "Mechanisms of DNA Replication...",
-      "authors": ["Smith, J.", "Doe, A."],
-      "journal": "Nature",
-      "year": 2023,
-      "doi": "10.1038/s41586-023-01234",
-      "abstract": "..."
-    }
-  ]
-}</code></pre>
-                </div>
-
-                <div class="bg-gray-800 rounded-lg p-4 mt-4">
-                    <h4 class="font-semibold text-blue-300 mb-2 text-sm">🔐 Authentication</h4>
-                    <p class="text-gray-400 text-xs mb-2">API uses Bearer token authentication. Include in request headers:</p>
-                    <pre class="text-green-400 text-xs"><code>Authorization: Bearer YOUR_API_TOKEN</code></pre>
-                </div>
-
-                <div class="bg-gray-800 rounded-lg p-4 mt-4">
-                    <h4 class="font-semibold text-blue-300 mb-2 text-sm">⚡ Rate Limits</h4>
-                    <p class="text-gray-400 text-xs">Standard rate limits apply: 100 requests/minute per API key. Contact for higher limits.</p>
-                </div>
-
-                <div class="bg-gray-800 rounded-lg p-4 mt-4">
-                    <h4 class="font-semibold text-blue-300 mb-2 text-sm">📚 API Version</h4>
-                    <p class="text-gray-400 text-xs">Current version: v1.0. API is stable and backward-compatible.</p>
-                </div>
             </div>
         </div>
     </section>
@@ -988,10 +344,16 @@
     <!-- Footer -->
     <footer class="gradient-bg text-white py-8 mt-12">
         <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
-            <p class="text-lg font-semibold mb-2">CopernicusAI - Advancing Scientific Knowledge</p>
-            <p class="text-sm opacity-75">Built with Google Cloud, Gemini AI, OpenAI, Anthropic Claude, and ElevenLabs</p>
-            <p class="text-xs opacity-50 mt-4">&copy; 2025 CopernicusAI. All rights reserved.</p>
+            <p class="text-lg font-semibold mb-2">GLMP - Genome Logic Modeling Project</p>
+            <p class="text-sm opacity-75">Part of the CopernicusAI Knowledge Engine</p>
+            <p class="text-xs opacity-50 mt-4">&copy; 2025 Gary Welz. All rights reserved.</p>
         </div>
     </footer>
+
+    <script>
+        // Simple script for any interactive elements if needed
+        console.log('GLMP Space loaded - using direct GCS viewer integration');
+    </script>
 </body>
 </html>
+