🧬 AI Bioinformatics Assistant

An intelligent AI-powered chatbot for bioinformatics education and sequence analysis. Built with FastAPI, Streamlit, and Openrouter API.

🎯 Features

• AI Chatbot: Ask questions about bioinformatics concepts, get expert explanations
• Sequence Analysis: Upload and analyze FASTA/FASTQ files
• GC Content Calculation: Understand nucleotide composition
• ORF Detection: Find open reading frames in sequences
• Chat History: Maintain conversation context
• Multi-file Support: Analyze multiple sequences at once
• Educational Focus: Designed as a learning assistant for students

🖥️ Tech Stack

• Frontend: Streamlit (modern chat-style UI)
• Backend: FastAPI (REST API)
• AI Model: Openrouter API
• Processing: Python with optional Biopython
• Format Support: FASTA, FASTQ, FA, FNA, FQ

📋 Project Structure

.
├── README.md
├── requirements.txt
├── .env.example
├── frontend/
│   └── app.py                 # Streamlit UI
├── backend/
│   └── main.py                # FastAPI server
├── utils/
│   ├── __init__.py
│   ├── parser.py              # FASTA/FASTQ parser
│   ├── analysis.py            # Sequence analysis
│   └── ai_utils.py            # Openrouter API integration
└── examples/
    └── sample_sequences.fasta # Example file

🚀 Quick Start

Prerequisites

• Python 3.8+
• Openrouter API key (get one at https://openrouter.ai/)

Installation

1. Clone/Navigate to the project

cd f:\Database\Bioinformatics\APIs

2. Create virtual environment (optional but recommended)

python -m venv venv
venv\Scripts\activate  # Windows
# or: source venv/bin/activate  # Linux/Mac

3. Install dependencies

pip install -r requirements.txt

4. Configure environment variables

# Copy .env.example to .env
copy .env.example .env

# Edit .env and add your Openrouter API key
# OPENROUTER_API_KEY=your_api_key_here

Running the Application

Option 1: Run both services locally

Terminal 1 - Start FastAPI Backend:

python backend/main.py
# or
uvicorn backend.main:app --reload --host 0.0.0.0 --port 8000

The backend will be available at http://localhost:8000

• Health check: http://localhost:8000/health
• Swagger docs: http://localhost:8000/docs

Terminal 2 - Start Streamlit Frontend:

streamlit run frontend/app.py

The frontend will open at http://localhost:8501

Option 2: Using PowerShell with concurrent execution

# Start both services in parallel
& python backend/main.py & streamlit run frontend/app.py

💡 Usage Guide

1. Analyzing Sequences

• Upload FASTA or FASTQ files using the sidebar uploader
• Click "Analyze Sequences" button
• View results: sequence count, length, GC content, nucleotide composition
• Optionally detect ORFs

2. Asking Questions

• Type any bioinformatics question in the chat input
• Examples:
  • "What is GC content?"
  • "Explain genome assembly"
  • "Analyze the uploaded sequence"
  • "What is CRISPR?"

3. Using Context

• Upload sequences first, then ask about them
• The AI will use sequence data to provide relevant explanations
• Example: "Analyze the uploaded sequence" or "What does this GC content indicate?"

🔌 API Endpoints

POST /chat

Chat with the AI bioinformatics expert

Request:

{
  "query": "What is GC content?",
  "chat_history": [],
  "sequence_context": null
}

Response:

{
  "response": "GC content is...",
  "error": false,
  "model": "openrouter/auto"
}

POST /analyze

Analyze biological sequences

Request:

{
  "content": ">sequence1\nATGC...",
  "file_format": "fasta",
  "detect_orfs": false
}

Response:

{
  "success": true,
  "analysis": {
    "total_sequences": 1,
    "total_length": 300,
    "average_length": 300,
    "average_gc_content": 45.5,
    "sequences": [...]
  },
  "orfs": null
}

GET /health

Health check and configuration status

Response:

{
  "status": "healthy",
  "api_key_configured": true,
  "endpoints": {
    "chat": "/chat",
    "analyze": "/analyze",
    "health": "/health"
  }
}

📊 Example Analysis Output

When you analyze sequences, you'll see:

📊 Sequence Analysis Results
───────────────────────────
📄 sample_sequences.fasta

Sequences: 4
Total Length: 3,245 bp
Avg Length: 811.25 bp
Avg GC%: 47.32%

📋 Detailed Sequence Info
- human_beta_globin: 146 bp, GC: 48.6%, AT: 51.4%
- mouse_beta_globin: 141 bp, GC: 47.5%, AT: 52.5%
- ecoli_dnaA: 1,290 bp, GC: 50.5%, AT: 49.5%
- salmonella_flagellin: 1,668 bp, GC: 45.2%, AT: 54.8%

🔧 Configuration

Environment Variables

# Openrouter API key (required)
OPENROUTER_API_KEY=sk_xxxxxxxxxx

# Backend URL (optional, defaults to localhost:8000)
BACKEND_URL=http://localhost:8000

File Formats Supported

Format	Extensions	Description
FASTA	.fasta, .fa, .fna	Sequence with headers starting with >
FASTQ	.fastq, .fq	Sequence with quality scores
Text	.txt	Plain text (auto-detect format)

📚 Example Questions

Concept Questions

• "What is GC content?"
• "Explain RNA-seq"
• "What is genome assembly?"
• "How does CRISPR work?"
• "What is BLAST?"

Sequence Analysis

• "Analyze this sequence"
• "Why is this GC content high?"
• "What organism might have this composition?"
• "Explain these results"

Learning

• "I'm learning bioinformatics, where should I start?"
• "What's the difference between DNA and RNA?"
• "Explain nucleotides"
• "What is a gene?"

🚨 Troubleshooting

"Cannot connect to backend"

• Make sure FastAPI is running: python backend/main.py
• Check that port 8000 is not in use: netstat -ano | findstr :8000

"API key not configured"

• Create .env file with OPENROUTER_API_KEY=your_key
• Restart the application
• Get an API key at https://openrouter.ai/

"File format not recognized"

• Supported extensions: .fasta, .fa, .fna, .fastq, .fq, .txt
• Ensure file starts with > for FASTA or @ for FASTQ

"API request timed out"

• Check internet connection
• Verify Openrouter API key is valid
• Try again (might be a temporary issue)

📖 Sequence File Examples

FASTA Format

>sequence_1 description here
ATGCGATCGATCGATCGATCG
ATGCGATCGATCGATCGATCG
>sequence_2 another description
GCTAGCTAGCTAGCTAGCTAG

FASTQ Format

@sequence_1
ATGCGATCGATCGATCGATCG
+
IIIIIIIIIIIIIIIIIIII
@sequence_2
GCTAGCTAGCTAGCTAGCTAG
+
IIIIIIIIIIIIIIIIIIII

🧬 Bioinformatics Concepts

GC Content

• Formula: (G + C) / Total Length × 100%
• Significance:
  • Indicates organism type and genomic stability
  • High GC = thermostable, often in extreme environments
  • Low GC = found in AT-rich organisms

Nucleotide Composition

• A (Adenine): Purine, pairs with T
• T (Thymine): Pyrimidine, pairs with A
• G (Guanine): Purine, pairs with C
• C (Cytosine): Pyrimidine, pairs with G

ORF (Open Reading Frame)

• Sequence between start (ATG) and stop (TAA, TAG, TGA) codons
• Potential protein-coding region
• Multiple reading frames possible

🤝 Contributing

Found a bug or have a feature request? Please open an issue or submit a PR!

📄 License

This project is open source and available under the MIT License.

🙋 Support

• Issues: Open an issue on GitHub
• Questions: Check the FAQ in the sidebar
• API Docs: Visit http://localhost:8000/docs when backend is running

📞 Contact

For more information about Openrouter API, visit: https://openrouter.ai/

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Version: 1.0.0
Last Updated: June 2026

Streamlit_-BioGenius

AI-Powered Bioinformatics Education & Sequence Analysis Platform for assisting patients