README.md

metadata

title: Bioinformatics Classification
emoji: 🧬
colorFrom: blue
colorTo: green
sdk: docker
app_file: app.py
pinned: false

🧬 Bioinformatics Classification App

A Flask-based web application for genomic SNP classification and natural product analysis using machine learning.

Features

• SNP-based Classification - Genomic sequence analysis and classification
• ML Model Integration - Scikit-learn Logistic Regression for predictions
• BLAST Database Support - Sequence alignment against pathway databases
• Interactive Web UI - Flask + HTML/CSS/JS frontend

Quick Start

The application starts automatically. Just interact with the web interface!

Project Structure

├── app.py # Main Flask application ├── best_model_LR.sav # Trained ML model ├── label_encoder.pkl # Feature encoder ├── pathway_db.* # BLAST sequence databases ├── static/ # CSS, JavaScript, images ├── templates/ # HTML templates └── data/ # Reference data

Model Details

• Classifier: Scikit-learn Logistic Regression
• Input: SNP features (genomic sequences)
• Output: Classification predictions
• Framework: Flask + Python 3.10

API Endpoints

• GET / - Main web interface
• POST /api/predict - Make predictions
• POST /api/upload - Upload sequences
• GET /api/results - Retrieve results

Author

Snehazs - Bioinformatics Researcher

License

MIT License