Genome Hackers

Home Page
Needleman-Wunsch Sequence Alignment Page
Sample Result

Inspiration

Manual sequence alignment is slow, error-prone, and frustrating for bioinformatics students. We wanted a faster, automated way to compare DNA, RNA, and protein sequences, so we built a Sequence Alignment Tool in Python and deployed it on Vercel for easy access.

What it does

Accepts two sequences (DNA, RNA, or protein) from the user.
Performs Needleman-Wunsch (global) and Smith-Waterman (local) alignment.
Outputs alignment score, aligned sequences, and visual representation.

How we built it

Language: Python 3
Algorithms: Needleman-Wunsch & Smith-Waterman
Deployment: Frontend built with HTML and JS; backend deployed on Vercel with Python serverless functions
Version control: GitHub repository linked to Vercel for CI/CD
Debugging: ChatGPT

Challenges we ran into

Difficulties of doing a web development project for the first time.
Displaying the results neatly.
Limitations of Vercel's free version.
Adapting Python scripts to serverless architecture on Vercel, which required restructuring functions.

Accomplishments that we're proud of

Successfully implemented both global and local alignment algorithms.
Built a fully automated, web-accessible tool usable by other students and researchers.
Made the tool fast and scalable, capable of handling long sequences without crashing.

What we learned

How to integrate Python backends with web deployments (Vercel).
Practical insights into sequence alignment algorithms and computational complexity.
Best practices for CI/CD pipelines, handling serverless functions, and managing dependencies.

What's next for Genome Hackers

Add support for multiple sequence alignment.
Implement interactive visualisation of alignments.
Expand to protein structure predictions and integration with external databases.
Optimise performance for large genomic datasets.
Create more tools to simplify the lives of Bioinformatics researchers.