🧬 GeneStack – DNA Data Storage Research Platform

GeneStack is a research-driven DNA data storage platform that simulates how digital files can be converted into DNA nucleotide sequences and decoded back without data loss.

Inspired by real-world work from Microsoft Research, Harvard Wyss Institute, Scientific American, and recent biotechnology studies, this project demonstrates how DNA can become the future of sustainable archival storage.

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📌 Problem Statement

The global volume of digital data is increasing exponentially, while current storage systems such as HDDs, SSDs, and cloud data centers face critical limitations:

• limited lifespan
• high energy consumption
• large physical infrastructure
• expensive maintenance
• long-term sustainability issues

Research suggests DNA offers a highly dense, durable, and ultra-long-lasting alternative storage medium.

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💡 Solution

GeneStack simulates DNA-based digital archival storage.

The platform converts uploaded digital files into DNA nucleotide sequences using base-pair encoding:

• 00 → A
• 01 → T
• 10 → G
• 11 → C

The generated .dna file can later be decoded back into the original digital file.

This workflow models the same concept explored in Microsoft’s molecular storage research and Harvard’s enzyme-driven DNA writing systems.

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🔬 Research Foundation

This project is inspired by research and articles from:

• Microsoft Research – DNA Storage
• Harvard Wyss Institute – DNA Data Storage
• Scientific American – DNA: The Ultimate Data Storage Solution
• National Geographic – DNA Data Storage Biotechnology
• PMC Research Landscape and Future Prospects
• Micron – DNA’s Potential to Store Global Data

These sources emphasize DNA’s:

• extreme data density
• century-scale durability
• low energy requirements
• long-term archival capabilities

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🧠 Technologies Used

• HTML
• CSS
• JavaScript
• DNA Base Pair Encoding Logic
• GitHub Pages
• Canva Embedded Documentation
• Research-based comparison analytics

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🔄 Working Flow

1. User uploads file
2. File converts to binary
3. Binary pairs map into DNA bases
4. DNA sequence stored as .dna
5. Reverse decoding reconstructs file
6. Comparison analytics show storage benefits
7. Canva timeline explains methodology

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📊 Key Features

• Lossless DNA encoding & decoding
• DNA file generation
• Reverse file recovery
• Comparison analytics section
• Canva timeline documentation
• Team research showcase
• GitHub Pages deployment

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🚀 Future Scope

• AI-assisted DNA compression
• GC-content balancing
• biological mutation-safe encoding
• random-access DNA retrieval
• DNA cloud archival vaults
• genome-scale storage architecture

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👥 Team Members

• Akshara Andhale
  SAP ID: 70412500096
  MBA Tech IT A2

• Darika Vajpayee
  SAP ID: 70412500036
  MBA Tech IT A2

• Yoma Shah
  SAP ID: 70412500071
  MBA Tech IT A2