📖 Project Description
The AI-Based Biological Pathway Simulation Framework is a full-stack web application that models biological pathways as directed graph networks, enables dynamic perturbation simulation, performs structural network analysis, and integrates AI-based reasoning for contextual interpretation.
The platform allows users to construct interaction networks, simulate node-level changes (e.g., knockout or overexpression), analyze structural impact using graph metrics, and receive AI-generated explanations of system-level effects.
Convert biological pathways into computational graph models
Simulate structural perturbations dynamically
Identify influential regulatory nodes
Provide quantitative network analysis
Integrate AI for contextual interpretation
Deliver interactive visualization in a user-friendly interface
1️⃣ Pathway Construction
Add nodes representing molecular entities
Define directed edges (activation/inhibition)
Real-time interactive graph rendering
2️⃣ Perturbation Simulation
Node knockout simulation
Node overexpression simulation
Automatic graph restructuring
3️⃣ Structural Network Analysis
Degree centrality calculation
Node influence ranking
Connectivity assessment
Before vs after structural comparison
4️⃣ AI-Based Interpretation
OpenAI API integration
Structured analysis output
Downstream effect prediction
Contextual explanation of network changes
5️⃣ Interactive Visualization
Dynamic graph visualization using Cytoscape.js
Node highlighting based on influence
Graphical metric representations
Frontend (React + Cytoscape.js) ↓ Backend REST API (Node.js + Express.js) ↓ Graph Simulation Engine ↓ Metric Computation Layer ↓ OpenAI API (AI Reasoning Layer) ↓ Structured Output → Dashboard
🔹 Languages
JavaScript
HTML
CSS
🔹 Frontend
React.js
Tailwind CSS
Cytoscape.js
Axios
🔹 Backend
Node.js
Express.js
MongoDB (Mongoose)
🔹 AI Integration
OpenAI API (GPT model)
🔹 Tools
Git & GitHub
MongoDB Atlas
Postman
🔄 Workflow
User constructs a pathway network.
System models it as a directed graph.
User selects a perturbation type.
Simulation engine updates network structure.
Structural metrics are recalculated.
OpenAI API generates contextual interpretation.
Results are visualized in the dashboard.
Clone Repository git clone https://github.com/your-username/bio-pathway-ai.git cd bio-pathway-ai Backend Setup cd server npm install
Create a .env file in /server:
PORT=5000 MONGO_URI=your_mongodb_connection_string OPENAI_API_KEY=your_openai_api_key
Run backend:
npm run dev Frontend Setup cd client npm install npm run dev 🌐 Environment Variables Variable Description PORT Backend server port MONGO_URI MongoDB connection string OPENAI_API_KEY OpenAI API key 📊 Example Use Case
Construct a signaling pathway
Perform knockout simulation
Observe connectivity reduction
Compare centrality changes
Review AI-generated interpretation
🛡 Disclaimer
This framework provides computational simulations and AI-assisted interpretations for exploratory and educational purposes. It does not replace experimental biological validation.