Inspiration
Our inspiration for the project was based on Karthik's research with stem cells, specifically downstream analysis. An important part of the biotech field involves sequencing the genes of the cells and detecting proteins that we may expect to see produced by those genes. We wanted to make a streamlined, user-friendly app that not only does the protein matching but also provides a neat summary of the potential matches!
What it does
This app takes any human gene sequence as input, runs it through NCBI BLASTx, and returns the top 3 potential protein matches of the gene sequence.
How we built it
The backend was built on python using the BioPython package to access the BLAST API. The web app was built using React.
Challenges we ran into
Initially, the scope of our project was too big. The initial idea was to do a lot of the sequencing ourselves, but we quickly came to realize that was near impossible given our time constraints and computing capabilities. However, we were able to find programs like BLAST that would accomplish that for us.
Accomplishments that we're proud of
It was huge for us to figure out how to use the BLAST API, especially since many tutorials for it were significantly outdated and no longer worked. We're also incredibly proud of the web design and the high quality it has.
What we learned
We learned a lot about React, API usage, and biology. It was really fascinating to be able to integrate these completely different concepts to create a pretty nifty app!
What's next for Protein Peekaboo
We would love to add more options to widen scope of the app, such as allowing the user to use sequences from non-human species, or integrating the AlphaFold protein database to display simulated structures for the target protein.
Built With
- biopython
- bootstrap
- ebi-ncbi-blast
- python
- react
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